Graph Neural Networks (GNNs) often suffer from degraded performance when encountering out-of-distribution (OOD) samples, particularly in multi-domain graph scenarios. Existing graph OOD detection methods typically require extensive modifications to data or model architectures, resulting in high computational costs and limited generalization. Moreover, prior approaches largely overlook local structural semantics and community-level patterns, leading to biased representations and suboptimal detection performance. To overcome these limitations, we propose community enhanced graph out-of-distribution detection (CEGOOD), a novel framework that incorporates community structure into GNN-based OOD detection. Specifically, we propose two community-aware view generation strategies: intra-community attribute aggregation (ICAA) to distill fine-grained feature coherence and inter-community edge dropping (ICED) to fortify structural robustness by pruning non-critical cross-community edges. Furthermore, We also design three community-level loss functions (compactness, separability, and balance) to optimize community hierarchical structures and improve community representation. Experimental results on various datasets show that CEGOOD outperforms state-of-the-art baselines by an average of 1.8% AUC, with notable gains of 2.4% on AIDS+DHFR and 2.8% on BBBP+BACE, demonstrating superior adaptability and effectiveness in graph OOD detection tasks.

This paper studies movable pinching-antenna (PA) assisted communications, where a single PA can be dynamically placed along a dielectric waveguide to serve multiple users via orthogonal or non-orthogonal multiple access (OMA/NOMA). In contrast to the ideal-lossless waveguide model commonly assumed, our work explicitly incorporates waveguide-power loss, thereby introducing a fundamental trade-off with free-space path loss that jointly determines system performance. By deriving the lower-bound-based suboptimal PA position for two- and three-user scenarios under both with and without waveguide-power loss, we establish a general positioning guideline applicable to multi-user scenarios. Furthermore, we perform a comparative analysis between the proposed single-PA scheme and a static multi-PA scheme. Analytical and simulation results derive the conditions determining which scheme is superior, revealing that the trade-off is fundamentally governed by the relative dominance between the waveguide-power loss and the free-space path loss. Simulation results validating our analytical derivations also confirm that the proposed PA positioning rule in NOMA-based PASS holds for both successive interference cancellation (SIC) decoding orders, demonstrating its robustness regardless of whether the near user decodes the far user’s signal first or vice versa.

The reconfigurable intelligent surface (RIS) has been widely studied in far-field communications (FFC), and further extended to near-field communications (NFC). With the distinct electromagnetic properties in FFC and NFC, it remains debatable whether the RIS deployment strategies established for FFC are still applicable to NFC. To bridge this gap, we examine RIS-aided cooperative relaying in NFC through two representative configurations, single-RIS and multi-RIS relaying, in which a decode-and-forward relay forwards data from the source to the user with the assistance of RIS For the single RIS deployment, we show that the achievable rates with RIS deployed near the base station (BS) or near relay are completely different. It is revealed that, with a single-antenna relay, the multi-RIS is significantly preferable over the single RIS in NFC without the requirement of massive RIS reflection elements, which is completely different from that of FFC. Furthermore, we derive closed-form expressions for the achievable rates under both single-antenna and multi-antenna relay configurations to explicitly determine the distance threshold. The presented analytical results demonstrate that locating RIS near the relay yields substantial performance gains when the transmission distance exceeds a certain threshold. This conclusion is validated by numerical simulations, which systematically illustrates the distinct impact of RIS deployment strategies in near-field versus far-field regions.

Wildfire incidents have surged in frequency and severity in recent years highlighting the need for advanced technologies to predict wildfire behavior early and mitigate its impact. Recent strides in machine learning research, the increased availability of wildfire data, and computational resources have fueled the rise of data-driven approaches in wildfire management. This study aims to advance data-driven methods for predicting wildfire behavior and aid in timely decision-making and resource allocation efforts by adopting a Graph Neural Network (GNN)-based framework for predicting the burned area resulting from a wildfire ignition. GNNs have shown success in handling irregular-sized inputs and capturing the long-range dependencies inherent in geospatial data, such as wildfires, making them a viable alternative to CNNs which impose limitations on geospatial data due to their reliance on fixed-size inputs and local receptive fields. A framework is developed to represent spatial wildfire data and its influencing factors as graphs followed by the development of three distinct GNN models based on different message-passing mechanisms to process the graph-structured data. GNN models outperform CNN-based segmentation models in wildfire prediction, achieving higher AUPRC (0.4787), precision (0.4536), and AUROC (0.9377), and illustrating the efficacy of GNNs in modeling wildfire behavior by effectively capturing spatial dependencies.

In response to the growing incidence and severity of wildfires, this paper presents Vi-Net, a novel hybrid deep learning framework for next-day wildfire spread prediction. By integrating U-Net’s fine-grained spatial segmentation with the global contextual modeling of Vision Transformers (ViT), Vi-Net formulates wildfire spread prediction as a semantic segmentation task. The model is trained on a decade-long (2012–2020) multimodal wildfire dataset that integrates meteorological, topographical, and vegetation features. To address the severe class imbalance inherent in wildfire data, Vi-Net employs a Focal Tversky loss function. Experimental results show that Vi-Net achieves an F1-score of ∼97% and an Intersection over Union (IoU) of ∼94% on test data, significantly outperforming standalone U-Net and ViT models. These findings underscore Vi-Net’s potential to improve wildfire mitigation planning, resource allocation, and emergency response.

In this letter, we investigate the wireless communication system assisted by hybrid intelligent reflecting surface (RIS), which is composed of both passive and active elements integrated reflection-type amplifiers. Different from conventional hybrid RIS system, the amplifying power used at active RIS is considered as one part of the total power for overall system. Under this condition, we present the exact closed-form expression of the outage probability (OP) and investigate the optimal allocations of the RIS elements and power budget for signal-to-interference-plus-noise ratio (SINR) maximization. In addition, we analyze the amplification factor and corresponding dynamic noise, as well as derive the threshold of the amplification factor for the proposed scheme. Finally, simulation and numerical results show that the proposed hybrid RIS scheme is significantly preferable over the conventional RIS scheme if the amplification factor of the proposed scheme is smaller than that of the threshold.

With the flourishing development of sixth-generation wireless networks, the demand of spectrum efficiency rapidly increases, in order to support the demands of high-quality data transmission and connections of massive users. Among various promising technologies, the technology of near-field communications provides a great potential to address such an issue due to the unique spherical-wave channels for electromagnetic (EM) propagation. In this article, multiple-input-single-output (MISO) near-field communications is comprehensively studied to clarify the influences of the shape and structure of uniform planar array (UPA) on the system performance, considering three cases with uniform linear array (ULA), rectangular UPA, and circular UPA. In particular, we reveal the properties of rapid deterioration for signal-to-noise ratio (SNR) from the reduced projection aperture in near-field communications and investigate the single spherical crown antenna design and spherical crown antenna array design in order to address this issue. Moreover, we also characterize the role of antenna projection aperture in detail, and theoretically analyze the shape of UPA, yielding the corresponding exact closed-form expressions for SNR and outage probability (OP). Based on these above analytical results, we find out that adjusting the spacing between adjacent antennas to control the relative angle between user and selected antennas is an efficient way to improve the projection aperture of antenna and SNR. Simulation results are shown to well match analytical results, which validate the correctness of our analysis, clarifying that our proposed designs outperform the conventional works and illustrating a better stability for angle variations.

International audience

In this article, we propose a deep reinforcement learning (DRL)-based multipoint localization scheme (MLS) to efficiently localize Internet of Things (IoT) devices using a single autonomous aerial vehicle (AAV) equipped with a large-scale multiantenna configuration in near-field communication (NFC). By utilizing the spherical wave-based near-field steering vector, the multiantenna array on the AAV captures both the Angle of Arrival (AoA) and received signal strength indicator (RSSI) measurements from IoT devices to estimate their locations relative to the position of the AAV. This approach eliminates the need for multiple hovering points required by a single-antenna AAV (SA-AAV) or the deployment of multiple SA-AAVs. To enhance localization accuracy, key hovering points for the multiantenna AAV (MA-AAV) are strategically selected, with weights assigned based on signal strength to prioritize stronger and more reliable signals. Furthermore, DRL dynamically adjusts the position of the MA-AAV to optimize the tradeoff between localization accuracy and energy consumption. Extensive simulations conducted across rural, urban, and dense urban scenarios demonstrate that the proposed DRL-based MLS significantly improves localization accuracy while reducing the energy consumption of the AAV.

Fast reroute (FRR) is among the fastest survivable routing approaches in packet-switched networks, because the routers are equipped with a resilient routing table in advance such that the packets can be rerouted instantly upon failures solely relying on local information, i.e., without notification messages. However, designing the routing algorithm for FRR is challenging as the number of possible sets of failed network links can be extremely high, while the algorithm should keep track of which routers are aware of the failure. Therefore, FRR methods often rely on spanning arborescences, which provide multiple disjoint failover paths up to the global connectivity of the network. In this paper, we propose a generic algorithmic framework that theoretically increases the number of failover paths to the local connectivity between each node and the root by extending an efficient connectivity preserving operation from graph theory – called edge splitting-off – to decompose the network topology node-by-node, and use Integer Linear Programs (ILPs) on these partial subproblems to build routing arborescences in the reverse direction for the original topology. Although our practical implementation cannot reach the local connectivity in all instances, we demonstrate through simulations that it still outperforms the state-of-the-art FRR mechanisms and provides better resilience with shorter paths in the arborescences.

This paper proposes a blockchain-integrated federated learning (FL) framework tailored for secure, efficient, and energy-aware model training in edge computing environments. The framework follows an offload-train-aggregate paradigm where edge devices transmit local datasets to proximate servers for localized model updates. A reputation-driven RAFT consensus protocol is incorporated to achieve reliable, low-latency, and lightweight blockchain coordination while preserving privacy and accountability. To overcome the inherent mixed-integer nonlinear programming (MINLP) complexity, we develop a two-stage cross-layer optimization strategy. In the first stage, an alternating direction method of multipliers (ADMM)-based feedback control scheme jointly allocates bandwidth and computation resources under energy and delay constraints. In the second stage, server selection and sub-band assignment are modeled as a bipartite matching problem and solved via the Hungarian algorithm, guided by a convergence-aware performance bound. Extensive simulations demonstrate that our framework significantly improves learning accuracy, uplink throughput, and energy efficiency over state-of-the-art FL baselines. It also exhibits strong robustness to network fragmentation and resource heterogeneity, making it well suited for practical edge environments.

This paper explores the usage of low-voltage Power-Line Communication (PLC) links for Enhanced Common Public Radio Interface (eCPRI)-based front-hauling in 5G Internet of Things (IoT) indoor mobile coverage environments, using a split Centralized Radio Access Network (C-RAN) architecture. This research aims to analyze how parameters such as wireless IoT device count, bandwidth, and transmission technology affect the delay performance of the proposed system. To achieve this goal, we develop detailed mathematical models that draw insights from queuing theory, stochastic geometry, and Markov models. Extensive system-level simulations verify these models’ accuracy, and the analytical results cover radio and access delay performance. We validate the system’s efficiency in supporting IoT indoor cellular applications and assess the feasibility of the proposed PLC-based front-hauling system, considering the strict delay requirements of the eCPRI standard.

With the further investigation and utilization of the extremely large-scale antenna array (ELAA) and Terahertz (THz) band, as well as the increasingly stringent standards of regulatory agencies, the near-field communications are evolving into the norm of intelligent transportation systems. In this work, we propose a novel beamfocusing scheme to improve the system performance for the reconfigurable intelligent surface (RIS)-aided hybrid near- and far-field communications with multi-unmanned aerial vehicle (UAV). Compared to conventional schemes without considering the near-field beam pattern with a finite depth, in our proposed scheme, the RIS only serves one UAV, while other UAVs are within the radiation range of the concentrated signal energy by beamfocusing. Specifically, we study the polar radius and angular deviations between UAVs with a given beamfocusing gain, aiming to reveal the impact of RIS structure on beamfocusing gain. We also make a fair comparison between the proposed scheme and allocated RIS scheme, deriving the feasible reference distance. In addition, we study the feasibility for different RIS structures focusing on the beamfocusing gain, which has the potential to improve the system performance. Simulation results demonstrate that the proposed scheme is always superior than that of the allocated RIS scheme within the feasible reference distance.

The increasing connectivity and automation in the Internet of vehicles (IoV) have significantly heightened the risk of network attacks, making intrusion detection systems (IDS) a crucial component of security measures in intelligent transportation systems (ITS). To address this challenge, we propose an advanced intrusion detection method integrating knowledge graph (KG) and artificial intelligence (AI) techniques, termed IDS-IKGAI, to enhance the security of IoV infrastructures. In our proposed scheme, we first preprocess an intrusion detection dataset specific to IoV, i.e., feature selection and extraction, that can be represented as triples using the resource description framework (RDF). These RDF triples are used to construct a knowledge graph, capturing the semantic relationships among the features. Next, we map the knowledge graph to a vector space, to build a labeled dataset for machine learning. To train and predict potential intrusions, the random forest (RF) and light gradient boosting machine learning (LightGBM) algorithms are investigated. Experimental evaluations demonstrate the effectiveness of our proposed scheme, with around F1 scores of 99.99% for RF and 99.93% for LightGBM, outperforming conventional benchmark models.

In the rapidly evolving field of wireless communications, the emergence of 5G and the progression towards 6G technologies highlight the demands for innovative frameworks capable of enhancing network performance under complex environmental factors. According to this trend, this work introduces a novel system model for aerial reconfigurable intelligent surface (ARIS)-assisted wireless communications, engineered to adeptly manage dynamic environmental influences such as fluctuating wind patterns and variable weather conditions. By treating these influences as random variables, we further introduce unpredictable variations in ARIS orientation (roll, yaw, and pitch), affecting network efficiency and reliability. To mitigate these environmental perturbations and uncertainties in the channel state information (CSI), we propose a robust beamforming strategy to reshape the original optimization problem into a form that is easier to analyze and solve, by employing stochastic optimization, successive convex approximation (SCA), and block coordinate descent (BCD) techniques to optimize active beamforming vectors and ARIS phase shifts. Comprehensive simulations rigorously evaluate the performance of our proposed algorithms across diverse conditions, including aerial disturbances, varying channel states, and different RIS element configurations. The results underscore the efficacy of our beamforming design in boosting the resilience and dependability of ARIS-enhanced wireless networks.

Quantum key distribution (QKD)-enabled optical networks utilize quantum mechanics to secure communications by establishing secure quantum channels. A critical criterion for QKD-enabled optical networks is ensuring network availability, which requires each quantum key service to adhere to a maximum unavailability constraint to maintain the network availability. This paper addresses the challenge of offering dedicated path protection for quantum key services in QKD-enabled optical networks. It ensures that the unavailability gap between the working and protection paths remains within the allowable limit for each quantum key service, adhering to specific unavailability constraints. Considering the constraints of the limited timeslot resources and network availability, we proposed quantum key service approach named a maximum availability (MA) algorithm. Simulation results indicate that the MA algorithm surpasses both the traditional dedicated-path protection (TDP) and fixed dedicated-path routing (FDR) algorithms in reducing total timeslot consumption and enhancing average availability.

Unmanned aerial vehicles (UAVs) have been adopted in various applications, including agriculture, public safety, surveillance, and crucial military missions. However, alongside their advantageous nature, UAVs have also been employed for malicious activities, leading to an increased requirement for timely detection and identification. Despite significant progress in UAV detection, challenges persist, particularly concerning various types of UAVs, the payload carried by UAVs, and the traits of their flight. Employing single machine learning for detection and identification has limitations due to the inability to handle diverse datasets and acquire complex relationships. Therefore, in this paper, we introduce a novel integration of the Visual Geometry Group-based convolutional neural network (VGG-CNN) framework employed for detection with the Mask Region-based convolutional neural network (MR-CNN) for identification of UAVs (jointly termed MR-DCNN). For efficient deployment of MR-DCNN, we add diversity to the dataset by performing data augmentation of new images in the training dataset for the detection of various types of UAVs, payload categories, and flight characteristics. The performance evaluation of the MR-DCNN approach was conducted via simulations, revealing superior detection capabilities for malicious UAVs compared to existing methods.

Multihop communication has gained prominence within the realm of the Internet of Underwater Things (IoUT) owing to its exceptional reliability amidst the challenges posed by the underwater acoustic environment. Despite this, the persistence of limitations caused by propagation delay, high collision rate, and limited energy in underwater communication remains, representing the most formidable hurdles in ensuring the successful transmission of data gathered by sensor nodes. To address these challenges, we employ a machine learning (ML)-based optimal cooperating node selection for each hop, considering the Shortest propagation delay, minimal residual Energy, and a low Collision rate (referred to as SEC). For this purpose, we initially assemble the sensor nodes to create a list of cooperative nodes, considering the aspect of SEC. Then, using an assembled list of cooperating sensor nodes, we employ ML-based algorithms, such as reinforcement learning (RL-SEC), deep Q-networks (DQN-SEC), and deep deterministic policy gradient (DDPG-SEC), to predict the optimal cooperating node for each hop. The simulation results of the DDPG-SEC demonstrate a significant improvement of approximately 56% when compared with RL-SEC, DQN-SEC, and other state-of-the-art techniques.

Cybertwin technology introduces a novel paradigm employing digital twins to model complex physical systems within a cyber environment, thus enhancing communication, collaboration, and decision-making capabilities. By harnessing advanced technologies, such as reconfigurable intelligent surfaces (RISs) and multiaccess edge computing (MEC), seamless interaction between physical and virtual entities is facilitated. In this article, we propose a cybertwin-driven edge computing framework that leverages RIS technology, complemented by an efficient computing offloading strategy to support large-scale Internet of Everything (IoE) applications. Specifically, the proposed strategy focuses on a multicell system where numerous randomly distributed end users have the option to offload delay-sensitive and computing-intensive tasks to edge computing nodes. The offloading channels are enhanced by RISs through passive beamforming, while cybertwin technology directs resource cooperation among multicells and allocates computing and communication resources. Our main objective is to optimize the system’s utility with respect to task completion latency and energy consumption reduction. To achieve this goal, we conduct the joint optimization of task offloading and resource allocation. Furthermore, we develop a joint task offloading and resource allocation (JTORA) algorithm to derive optimal solutions for passive beamforming design, computing offloading decisions, communication resource scheduling, and computing capacity allocation. The simulation results demonstrate the superiority of the proposed algorithm over benchmark schemes in terms of edge computing efficiency. Furthermore, the system utility can be further enhanced by increasing the number of embedded RIS elements.

Space-air-ground integrated networks (SAGINs) hold immense potential for improved network coverage and dynamic service delivery. Yet, current methods often depend on separate, uncoordinated unmanned aerial vehicles (UAVs), leading to scalability issues and limited energy efficiency – challenges that persist even when applying intelligent machine learning (ML) methods. This paper discusses a four-tier aerial computing (AC) system, leveraging the collective capabilities of low-altitude UAVs (LAUs), high-altitude UAVs (HAUs), and satellites to fully realize the potential of SAGINs within AC. Incorporating advancements in tiny machine learning (TinyML), this system boosts onboard intelligence for immediate data processing and adaptive decision-making. Specifically, by utilizing the robust computational resources of higher-layer SAGIN entities, we introduce a tiny federated deep reinforcement learning (TinyFDRL) algorithm across multiple tiers to achieve energy-efficient trajectories for multiple LAUs. This proposed TinyFDRL algorithm independently plans multi-LAU trajectories in unpredictable environments by combining the strengths of federated learning (FL) and deep reinforcement learning (DRL). Extensive simulations validate the algorithm, confirming its efficiency in creating energy-saving paths for LAUs in the integrated AC network.

This article investigates physical-layer security (PLS) for an energy-harvesting cognitive network with nonorthogonal multiple access (EHCN-NOMA), where a cognitive base station (CBS) communicates with two cognitive users named cognitive near user (CNU) and cognitive far user (CFU) by adopting the NOMA principle under an active or passive eavesdropper (Eve) attack. By means of energy harvesters, the CBS collects the radio frequency energy from the primary source (PS) by a time-switching protocol; meanwhile, the cognitive transmit power is limited by the interference threshold of primary destination (PD) to guarantee the Quality of Service (QoS) of primary transmissions. To evaluate the impact of active and/or passive eavesdroppings on system performance, we derive closed-form expressions in terms of outage probabilities (OPs), intercept probabilities (IPs), as well as effective secrecy throughputs (ESTs). The numerical results verify the correctness of our theoretical derivations and confirm that there exists a tradeoff between security and reliability for the EHCN-NOMA transmissions. Moreover, the EST improvement depends on the competition between security and reliability. Furthermore, the maximum EST performance can be achieved for both eavesdropping scenarios by adjusting the time allocation between that of the energy transfer phase and the information transmission phase.

This letter investigates secrecy performance for cognitive transmissions, where a secondary user (SU) shares same spectrum with a primary user (PU) simultaneously ensuring the Quality of Service (QoS) of primary transmissions. Additionally, an eavesdropper (Eve) overhears cognitive transmissions from SU to base station (BS). To against eavesdropping attacks, a novel artificial noise-aided rate splitting (ANRS) scheme is proposed, where PU emits artificial noise to confuse Eve and SU adopts rate splitting (RS). The numerical results of secrecy outage probability indicates that the ANRS scheme achieves better secrecy performance than that of AN without RS (ANWRS) and of RS without AN (RSWAN) schemes.

This paper addresses the virtual network (VN) mapping problems for the network profit optimization in space-division-multiplexing optical data center networks (SDM-ODCNs). We first define both link resource availability (LRA) and node resource availability (NRA) for the VN mapping optimization, by which an integer linear program (ILP) model and two VN mapping approaches are proposed to achieve the high network profit. Simulation results verify that our proposed LRA VN mapping approach achieves greatly close network performance to that by solving solutions of the integer linear program model and significantly outperforms its counterpart approaches. The improved network profits out of the VN mapping is as a result of well suppressed average crosstalk, rejection ratio of VNs, and spectrum fragmentation ratio in SDM-ODCNs.

This paper presents a novel framework called Failure-Alarm Correlation Tree based Failure Localization (FACT-FL), designed to localize failed optical layer device boards in an Optical Transport Network (OTN). Specifically, FACT-FL aims to construct a set of FACTs by correlating the failed boards and alarms, where each FACT takes one failed board and its correlated alarms as the root and leaves, respectively. Furthermore, a FACT consists of a suite of kth order Failure-Alarm Correlation Chains (k-FACCs) with different order values of k. Each k-FACC indicates the chain-like correlation established by k alarms due to one common failed board. To identify all previously undetected k-FACCs, a set of binary classifiers is trained that characterizes each k-FACC from various dimensions, including time, network topology, traffic distribution, and board/alarm attributes. Eventually, an integer linear programming (ILP) problem is formulated to extract the most likely FACT(s) from those k-FACCs. Extensive case studies demonstrate the superior results of FACT-FL in terms of metrics evaluating the identified failed boards and root alarms. We also analyze its performance under different maximum order values of k and environmental changes, including failure scenarios, network topologies, traffic distributions, and noise alarms.

To fully exploit the potential of reconfigurable intelligent surface (RIS), the controllable channel state information (CSI) should be accurate for its future applications. Unfortunately, in vehicular communications, obtaining exact instantaneous CSI presents substantial challenges. Moreover, even with an instantaneous CSI acquisition, a processing latency for RIS phase shift adaption might occur before the vehicular system reacts to the instantaneous CSI information. To effectively introduce RIS into Internet of vehicle (IoV) networks, we employ a more realistic statistical CSI approach in designing RIS-assisted vehicular communication systems that are robust to the general characteristics of the channel, rather than its instantaneous fluctuations. We present a practical system framework, where a roadside unit employs an RIS to facilitate indirect wireless communications for vehicle-to-vehicle (V2V) communications. Particularly, the direct links between vehicles are susceptible to blockages caused by surrounding obstacles/vehicles. The deployment of RIS is to establish supplementary communication links between a multi-antenna vehicle source (VS) and multiple vehicular users (VUs) as they traverse areas with a poor service coverage. With the objective to maximize the time-averaged sum-rate of VUs, instead of instantaneous CSI, we rely on the delayed statistical CSI feedback to design active beamforming at the VS and passive beamforming at RIS. Moreover, we develop an efficient algorithm, named JAPBNB, which leverages the fractional programming technique to find a stationary solution for the formulated sum-of-logarithms-of-ratio problem. Specifically, a non-convex block coordinate descent (BCD) approach, collaborating with the alternating direction method of multipliers (ADMM), is applied for the joint optimization of active and passive beamforming. Finally, the complexity and convergence of the proposed JAPBNB algorithm are thoroughly discussed and validated. Simulation results demonstrate that the time-averaged sum-rate obtained by the proposed JAPBNB algorithm approaches that obtained by the instantaneous CSI scheme, when the delayed statistical CSI feedback interval is adequately small.

Fast reroute (FRR) mechanisms that can instantly handle network failures in the data plane are gaining attention in packet-switched networks. In FRR no notification messages are required as the nodes adjacent to the failure are prepared with a routing table such that the packets are re-routed only based on local information. However, designing the routing algorithm for FRR is challenging because the number of possible sets of failed network links and nodes can be extremely high, while the algorithm should keep track of which nodes are aware of the failure. In this paper, we propose a generic algorithmic framework that combines the benefits of Integer Linear Programming (ILP) and an effective approach from graph theory related to constructive graph characterization of k-connected graphs, i.e., edge splitting-off. We illustrate these benefits through arborescence design for FRR and show that (i) due to the ILP we have great flexibility in defining the routing problem, while (ii) the problem can still be solved very fast. We demonstrate through simulations that our framework outperforms state-of-the-art FRR mechanisms andvprovides better resilience with shorter paths in the arborescences.

This article investigates energy-efficient secure communication design with the help of multiple phase-adjustable intelligent reflecting surfaces (IRSs). By creating desirable radiation patterns of wireless environment, the IRSs are used to significantly improve the number of bits securely delivered to the destination per energy consumption in Joule, also known as the secrecy energy efficiency (SEE). By manipulating the discrete reflecting coefficients of multiple IRSs and taking advantage of the active beamforming, this article develops an efficient alternating optimization algorithm based on successive convex approximation and penalty-based techniques to effectively fight against multiple eavesdroppers. Simulation results characterize the graceful tradeoff between conflicting performance metrics, i.e., total power consumption and secrecy rate in the multi-IRS-aided secure communication system, and corroborate that incorporating multiple IRSs is beneficial to both the SEE and secrecy rate enhancement compared to existing related benchmarks.

This paper addresses the problems of core and spectrum assignment (CSA) in space-division-multiplexing (SDM) elastic optical networks (EONs) with multi-core fiber (MCF). We first present spectrum sensitivity (SS) of the crosstalk-sensitive core matrix to evaluate inter-core crosstalk (XT) in trench-assisted (TA) MCF. We then propose the XT-sensitive spectrum assignment to suppress XT. We consider both static and dynamic network planning based on the spectrum sensitivity. In the static scenario, an integer linear programming (ILP) model along with effective heuristic CSA algorithms are developed to suppress XT and improve the spectrum efficiency. In the dynamic scenario, two heuristic CSA algorithms are proposed aiming to initiate a graceful tradeoff between average crosstalk and spectrum efficiency. Simulation results demonstrate the superiority of the proposed CSA algorithms compared with the existing CSA algorithm in MCF-based SDM-EONs.

This article introduces a novel physical-layer (PHY-layer) authentication scheme, called transfer learning-based PHY-layer authentication (TL-PHA), aiming to achieve fast online user authentication that is highly desired for latency-sensitive applications such as edge computing. The proposed TL-PHA scheme is characterized by incorporating with a novel convolutional neural network architecture, namely, the triple-pool network (TP-Net), for achieving lightweight and online classification, as well as effective data augmentation methods for generation of data set samples for the network model training. To assess the performance of the proposed scheme, we conducted two sets of experiments, including the one using computer-simulated channel data and the other utilizing real experiment data generated by our wireless testbed. The results demonstrate the superiority of the proposed scheme in terms of authentication accuracy, detection rate, and training complexity compared to all the considered counterparts.

The spectrum efficiency is a greatly important issue when we establish connection requests in elastic optical data center networks (EODCNs). In this article, we address the spectrum efficiency problems of the shared-path protection with spectrum-sharing-maximized approaches for the optical network survivability. Two integer linear program (ILP) models, i.e., flow-based and path-based ILP models, named FB-ILP and PB-ILP, are developed to minimize the frequency slots (FSs) occupied with the spectrum-sharing-maximized protection, and two heuristic approaches with the spectrum-sharing-maximized protection (HA-SSMP) and with the general spectrum-sharing protection (HA-GSSP) are also proposed to improve spectrum efficiency in EODCNs. For comparison, we introduce a heuristic approach with the existing shared-path protection (HA-ESPP) in EODCNs. On the one hand, simulation results show that FB-ILP can minimize the number of FSs occupied, but leads to the higher average number of hops and longer running time compared to PB-ILP, HA-SSMP, HA-GSSP, and HA-ESPP in static traffic scenario in EODCNs. On the other hand, the simulation results of our proposed HA-SSMP are very close to the solutions of FB-ILP. In dynamic traffic scenario, simulation results show that HA-SSMP significantly improves the spectrum efficiency and effectively suppresses the blocking probability, but leads to the higher average number of hops compared to HA-GSSP and HA-ESPP in EODCNs.

Unmanned aerial vehicles (UAVs) are widely applied for service provisioning in many domains, such as topographic mapping and traffic monitoring. These applications are complicated with huge computational resources and extremely low-latency requirements. However, the moderate computational capability and limited energy restrict the local data processing for the UAV. Fortunately, this impediment may be mitigated by utilizing wireless power transfer (WPT) and employing the multiaccess edge computing (MEC) paradigm for offloading demanding computational tasks from the UAV via wireless communications. Particularly, the offloaded information may become compromising by the eavesdropper (Eve) when UAVs offload the computational tasks to MEC servers. To address this issue, a UAV-MEC (UMEC) system with energy harvesting (EH) is studied, where the full-duplex protocol is considered to realize simultaneously receiving confidential data from the UAV and broadcasting the control instructions. It is worth noting that in our proposed scheme, these control instructions also serve as the artificial interference to confuse the Eve. To improve the energy efficiency for offloading, the computational communication resource allocation is optimized to minimize the energy consumption for UAV with the consumed and harvested energy. Specially, the worst case secrecy offloading rate and computation-latency constraint are considered, to further enhance the reliability and security of the proposed system. Since the objective optimization problem is nonconvex, we convert it into a convex one by analytical means. The semiclosed form expressions of the offloading time, offloading data size, and transmit power are, respectively, derived. Moreover, the conditions of nonoffloading, partial, and full offloading are also discussed from a physical perspective. With the specific conditions of activating the above-mentioned three offloading options, numerical results verify the performance of our proposed offloading strategy in various scenarios and show the superiority of our offloading strategy with the existing works in terms of the offloading capacity and energy efficiency.

In this article, the network performance of equilibrium allocation of quantum key resources was investigated in quantum key distribution (QKD)-enabled optical data center networks. To effectively use quantum key resources, we propose three novel efficient load balancing routing, wavelength, and time-slot assignment (LB-RWTA) approaches, including LB-RWTA with flexible security level (LB-RWTA-FSL), LB-RWTA with specific security level (LB-RWTA-SSL), and LB-RWTA without security level (LB-RWTA-NSL). Particularly, the proposed LB-RWTA-FSL approach is uniquely featured by adaptive security level classification (ASLC) and load balancing (LB), aiming to demarcate the security level (SL) and reduce the overall network congestion. We introduce an existing routing, wavelength, and time-slot assignment (E-RWTA) approach without SL, called E-RWTA, for comparison. Simulation results show the effectiveness of our proposed approaches in terms of much higher quantum key resource efficiency and thus much higher network security performance than the state-of-the-art quantum key resource allocation approaches compared with the E-RWTA approach in QKD-enabled optical data center networks.

With the rise of the Industrial Internet of Things (IIoT), more and more industrial devices can be connected via the network. Data collection, processing, analysis, task execution, and other devices that can product network traffic volume are gradually being deployed to IIoT. However, under the limited spectrum resources and low-cost and low-energy production requirements of enterprises, how to ensure the interconnection and intercommunication of industrial networks while realizing the effective use of network communication resources is currently a hot topic. Among them, network traffic prediction is considered to be a very important task. The time variability and interpretability, especially the time-varying features of traffic sequences, greatly challenge this task. To address those, this article proposes a method calledFlow2graphto predict network traffic in IIoT. Specifically, some key segments, i.e., shapelets are extracted from the network traffic sequence according to time-varying traffic; then uses the relationship between the traffic sequence and shapelets to convert the flow into a shapelets conversion graph; Subsequently, the graph isomorphism network are used to learn the specificity of the flow sequence from different devices, thereby to predict its traffic value for a period of time in the future; finally, we conduct extensive experiments on real data to verify the effectiveness of the proposed method.

Artificial Intelligence is in transition as the fast convergence of digital technologies and data science holds the promise to liberate consumer data and provide a faster and more cost-effective way of improving human initiatives. Particularly, artificial intelligence (AI) is heavily influencing autonomous vehicles nowadays. The data driven-based AI autonomous vehicles have the potential to reshape the expectations of human’s actions, the way that companies’ stakeholders collaborate, and revamp business models in the various industries.

Several recent studies shed light on the vulnerability of networks against regional failures, which are failures of multiple nodes and links in a physical region due to a natural disaster. The paper defines a novel design framework, called Geometric Network Augmentation (GNA), which determines a set of node pairs and the new cable routes to be deployed between each of them to make the network always remain connected when a regional failure of a given size occurs. With the proposed GNA design framework, we provide mathematical analysis and efficient heuristic algorithms that are built on the latest computational geometry tools and combinatorial optimization techniques. Through extensive simulation, we demonstrate that augmentation with just a small number of new cable routes will achieve the desired resilience against all the considered regional failures.

More than half of the world’s current population resides in urban areas to compare to just 30% in the 1950s. The process of urbanization leads to exurban sprawl, the formation of slums, scattered workplaces, and aging infrastructure. These may cause huge inefficiencies in energy use, traffic, governance, waste management, and pollution, among others. To overcome these social, economic, and environmental challenges, public and private sectors invest heavily in smart city technologies. However, the risks of using smart technologies due to security breaches and cyberattacks in critical sectors should be well addressed.

This paper considers a cooperative device-to-device (D2D) system with non-orthogonal multiple access (NOMA). We assume that the base station (BS) can simultaneously communicate with all users to satisfy the full information transmission requirement. In order to characterize the impact of the weak channel and different decoding schemes, two novel decoding strategies are introduced: single signal decoding scheme and maximum ratio combining (MRC) decoding scheme, respectively. With the single signal decoding scheme, the users decode the received signals immediately after the receptions from the BS. On the other hand, the MRC decoding scheme jointly decodes the received signals via MRC until the corresponding phase comes and the users jointly decode the received signals by employing MRC. Considering Rayleigh fading channels, the ergodic sum-rate (SR), outage probability and outage capacity of the proposed D2D-NOMA system are analyzed. Moreover, approximate expressions for the ergodic SR are also provided with a negligible performance loss. Numerical results demonstrate that the ergodic SR and outage probability of the proposed D2D-NOMA scheme overwhelm that of the conventional NOMA schemes. Furthermore, it is also revealed that the system performance including the ergodic SR and outage probability are limited by the weak channel for both the single signal decoding scheme and conventional NOMA schemes, but not for the MRC decoding scheme.

Disaster management, search and rescue missions, and health monitoring are examples of critical applications that require object localization with high precision and sometimes in a timely manner. In the absence of the global positioning system (GPS), the radio received signal strength index (RSSI) can be used for localization purposes due to its simplicity and cost-effectiveness. However, due to the low accuracy of RSSI, unmanned aerial vehicles (UAVs) or drones may be used as an efficient solution for improved localization accuracy due to their agility and higher probability of line-of-sight (LoS). Hence, in this context, we propose a novel framework based on reinforcement learning (RL) to enable a UAV (agent) to autonomously find its trajectory that results in improving the localization accuracy of multiple objects in shortest time and path length, fewer signal-strength measurements (waypoints), and/or lower UAV energy consumption. In particular, we first control the agent through initial scan trajectory on the whole region to 1) know the number of nodes and estimate their initial locations, and 2) train the agent online during operation. Then, the agent forms its trajectory by using RL to choose the next waypoints in order to minimize the average location errors of all objects. Our framework includes detailed UAV to ground channel characteristics with an empirical path loss and log-normal shadowing model, and also with an elaborate energy consumption model. We investigate and compare the localization precision of our approach with existing methods from the literature by varying the UAV's trajectory length, energy, number of waypoints, and time. Furthermore, we study the impact of the UAV's velocity, altitude, hovering time, communication range, number of maximum RSSI measurements, and number of objects. The results show the superiority of our method over the state-of-art and demonstrates its fast reduction of the localization error.

Fifth generation wireless networks are expected to provide advanced capabilities and create new markets. Among the emerging markets, Internet of Things (IoT) use cases are standing out with the proliferation of a wide range of sensors that can be configured to continuously monitor and transmit data for intelligent processing and decision making. Devices in such scenarios are normally extremely energy-constrained and often exist in large numbers and can be located in hard-to-reach areas; the fact that necessitates the design and implementation of effective energy-aware data collection mechanisms. To this end, we propose the utilization of unmanned aerial vehicles (UAVs) to collect data in dense wireless sensor networks using projection-based compressive data gathering (CDG) as a novel solution methodology. CDG is utilized to aggregate data en-route from a large set of sensor nodes to selected projection nodes acting as cluster heads (CHs) in order to reduce the number of needed transmissions leading to notable energy savings and extended network lifetime. The UAV transfers the gathered data from the CHs to a remote sink node, e.g., a 5G cellular base station, which avoids the need for long range transmissions or multihop communications among the sensors. Our problem definition aims at clustering the sensors, constructing an optimized forwarding tree per cluster, and gathering the data from selected CH nodes based on projection-based CDG with minimized UAV trajectory distance. We formulate a joint optimization problem and divide it into four complementary subproblems to generate close-to-optimal results with lower complexity. Moreover, we propose a set of effective algorithms to generate solutions for relatively large-scale network scenarios. We demonstrate the superiority of the proposed approach and the designed algorithms via detailed performance results with analysis, comparisons, and insights.

The paper introduces a novel hybrid network coding scheme in a three-node two-way relaying network in a wireless fading environment. The proposed hybrid scheme is featured by an opportunistic mechanism which employs one of the two network coding schemes, namely physical-layer network coding (PNC) and digital network coding (DNC), according to the instant rate requirement and dynamic channel condition. We first develop a close-form expression for the power consumption of the proposed scheme, which is further used to formulate a series of optimization problems under both symmetric and asymmetric traffic scenarios. Solving the optimization problems yields important system parameters that determine the optimal power allocations, time split between uplink and downlink transmissions as well as between PNC and DNC, respectively. We will discuss the possible overhead in the real implementation of the proposed scheme. Extensive numerical experiments are conducted to compare the performance of the proposed hybrid scheme with the conventional PNC and DNC scheme, respectively.

This paper investigates the joint user scheduling (US) and user association (UA) problem for OFDMA-based networks under the centralized radio access network (C-RAN) architecture. We first formulate the joint optimization problem for US and UA, which is intractable in its exact form, and therefore, we propose a corresponding upper bound problem, with much lower computational complexity, with the help of a novel continuous rate function. We show that the upper bound problem can be further converted into an equivalent convex optimization problem via geometric programming (GP) that can be solved with inter-baseband unit coordination, which is viable in the C-RAN architecture. Furthermore, we show that the solutions of the convex upper bound problem can be mapped into the solution space of the original joint US and UA problem with a small gap. As a practically implementable solution to the original problem, a heuristic-based scheduler has been developed to obtain quasi-optimal UA and US solutions for the uplink (UL) as well as the downlink (DL) transmissions. Through extensive numerical simulations, we verify that the performance of the proposed heuristic-based scheduler is quasi-optimal on both UL and DL.

Fifth generation wireless networks are expected to provide advanced capabilities and create new markets spanning a wide range of use cases. Among these, massive IoT is standing out with the proliferation of sensors and wearable devices that continuously monitor and transmit data for further processing. This paper proposes a novel data collection technique using Unmanned Aerial Vehicles (UAVs) in dense wireless sensor networks (WSNs) using projection-based Compressive Data Gathering (CDG) as a solution methodology. CDG is utilized to aggregate data en route from sets of sensor nodes to a set of projection nodes (heads) in order to notably reduce the number of transmissions leading to energy savings and extended WSN lifetime. The UAVs forward the gathered data from heads to a remote sink to enhance efficiency by avoiding long range transmissions from heads to the sink or multi-hop communications among sensors to the sink. We formulate a joint optimization problem that captures clustering, heads selection, routing trees construction, and UAV trajectory planning. In order to overcome the complexity of the joint optimization problem, we decompose the problem into separate parts and propose a heuristic to solve each subproblem for large-scale network scenarios.

In order to overcome the non-line-of-sight nature of the indoor environment so as to achieve a cost-effective solution of 5G indoor service provisioning, distribution of antenna units in indoor chambers is the most straightforward solution. This paper investigates a novel distributed antenna access architecture that allows the antenna units to be distributed over a wide geographical area via multi-pair LAN cables. The proposed architecture supports simultaneous transmission of multiple intermediate frequency signals between the remote radio unit and each distributed antenna unit. To explore the capacity of the LAN cables, we introduce a real-time multi-pair air-to-cable (MP-A2C) scheduler that allows for a graceful mapping between the radio signal spectrum and sub-channels of the cable twisted pairs, as well as power shaping of each sub-channel signal. We will first provide the problem formulation of the optimal MP-A2C process, which is nonetheless non-convex and computationally intractable. To achieve real-time solution of the problem, we reformulate the problem into two sub-problems that can be solved in a divide-and-conquer manner. Extensive numerical results show that the formulated MP-A2C problem can easily lead to quasi-optimal schedules.

Deploying femtocells has been taken as an effective solution for removing coverage holes and improving wireless service performance in 3G‐beyond wireless networks such as WiMAX and Long Term Evolution (LTE). This article investigates a novel framework of dynamic spectrum management for femtocell networks, called cognitive‐empowered femtocells (CEF), aiming at mitigating both cross‐tier and intratier interferences with minimum modifications required on the corresponding macrocell network. With the proposed framework, each CEF base station (BS) and the femtocell users can utilize spatiotemporally available radio resources for the access traffic. We conclude that the proposed CEF framework can effectively complement the existing femtocell design and serve as a value‐added feature to the state‐of‐the‐art femtocell technologies, while achieving high scalability and interoperability by minimizing the required modifications on the macrocell protocol design.

Cloud services are widely used to virtualize the management and actuation of the real-world the Internet of Things (IoT). Due to the increasing privacy concerns regarding querying untrusted cloud servers, query anonymity has become a critical issue to all the stakeholders which are related to assessment of the dependability and security of the IoT system. The paper presents our study on the problem of query receiver-anonymity in the cloud-based IoT system, where the trade-off between the offered query-anonymity and the incurred communication is considered. The paper will investigate whether the accepted worst-case communication cost is sufficient to achieve a specific query anonymity or not. By way of extensive theoretical analysis, it shows that the bounds of worst-case communication cost is quadratically increased as the offered level of anonymity is increased, and they are quadratic in the network diameter for the opposite range. Extensive simulation is conducted to verify the analytical assertions.

Instant and precise localization of a mobile user is fundamental for supporting various sophisticated indoor location-aware services. This paper focuses on achieving unambiguous user positioning using practical Bluetooth low energy (BLE) beacons with multiple discrete power levels. By receiving the beacon coverage status from a user's device, the cloud server can unambiguously pinpoint the user's location and react correspondingly. We first define the problem of beacon deployment for positioning (BDP) and provide several theoretic bounds on the number of required beacons to gain sufficient understanding on its performance behavior. The BDP problem is further formulated into an integer linear program (ILP) and solved in extensive case studies. We claim that this is the first systematic and in-depth research on beacon deployment for unambiguous user positioning. Our analysis and experiments show that the proposed solution takes O(√N) to O(N/2) beacons for N test positions, which is 2-8 times less beacons compared to that by the naive approach, while the analytical bounds are tight with the ILP results with 20% of gap.

The paper studies the scenario of wireless multicast with a single transmitter and a relay that jointly deliver successively refined (or multi-resolution) sources to multiple receivers. By taking the end-to-end mean square error distortion (EED) as the performance metric, the problems of power allocation at the transmitter and relay are formulated. Due to nonlinearity of the formulations, a generalized programming algorithm is developed to obtain near optimal solutions. Case studies are conducted to verify the proposed formulations and solution approaches. The results show the advantages of using a relay assisted multiresolution approach.

The paper investigates the scenario of wireless multicast with a single transmitter and multiple relays that jointly deliver successively refined (or multi-resolution) sources to multiple receivers. An asynchronous cooperative joint source-channel coding (JSCC) protocol is proposed, which can mitigate the complexity and difficulty in signal synchronization under the wireless multicast with cooperative relays. By considering the end-to-end mean square error distortion (EED), the problems of JSCC multicast are formulated to minimize the total power consumption by jointly selecting proper relays and the power allocations at the base station as well as the selected relays. To solve the formulated problem that is nonetheless nonlinear in nature, a two-step iterative algorithm is investigated for power allocations at all transmitters. Case studies are conducted to demonstrate the advantages of using the proposed JSCC in a relay-assisted multi-resolution wireless multicast network.

This paper studies the end to end distortion of transmission of a layered encoded source over a cooperative relay broadcast channel. A jointly optimised source-channel code is proposed to multicast a two-layered encoded source to two destinations. A degraded discrete memoryless broadcast channel is assumed, where the first destination with better channel conditions decodes both layers consisting of the common base layer and the refining layer for source reconstruction at a higher quality. Meanwhile, the second destination only decodes the base layer for a lower quality reconstruction of the source. The first destination cooperates in transmitting the common base layer to the second destination using a decode-forward (DF) relaying protocol over an orthogonal receive component (ORC) relay channel. An inner bound on the capacity region of the ORC-DF cooperative broadcast channel with a degraded message set is derived and the end to end distortion of reconstructing the source at both of the destinations is characterized. The achievable rate region and distortion performance of such network are demonstrated to outperform another variant of a DF-based cooperative broadcast channel, as well as with the non-cooperative broadcast channel.

This paper explores a cyber-physical system (CPS) that enables a billboard viewer to instantaneously obtain the snapshot of the displayed media content upon a smartphone gesture. We first define an add-on device mounted to each billboard/signage, called media processing and content access box (MP-CAB), which collaborates with the content management server and the viewers' smartphones for achieving the desired applications. The detailed design of the MP-CAB will be presented, followed by introducing a simple yet efficient multicast scheduling approach in presence of lossy WiFi link and multiple viewers of heterogeneous receiving modes. We model the response delay of the proposed CPS which jointly considers a set of key parameters, such as file size, percentage of receiver modes, and length of snapshot cycles. Extensive case studies are conducted to provide in-depth analysis and gain insights into the proposed CPS and employed scheduling approach regarding the relationship among several operation parameters. Specifically, we look into the network operation and multicast scheduling settings for achieving minimal expected response delay and maximal image size, aiming to gain sufficient understanding of the behavior of the proposed CPS in the real-time content snapshot acquisition process.

Network-wide local unambiguous failure localization (NL-UFL) has been demonstrated as an interesting scenario of monitoring trails (m-trails). It attempts to enable every node to autonomously localize any failure event in the network in a distributed and all-optical manner by inspecting a set of m-trails traversing through the node. This paper investigates the m-trail allocation problem under the NL-UFL scenario by taking each link and node failure event into consideration. Bound analysis is performed using combinatorial group testing (CGT) theory and this is followed by the introduction of a novel heuristic on general topologies. Extensive simulation is conducted to examine the proposed heuristic in terms of the required cover length and the number of m-trails to achieve NL-UFL.

This paper investigates the scenario of wireless multicast with a single transmitter and multiple relays that jointly deliver successively refined (or multiresolution) sources to multiple receivers. An asynchronous cooperative joint source-channel coding (JSCC) protocol is proposed, aimed at mitigating the complexity and difficulty in signal synchronization in multicast. Taking end-to-end mean square error distortion (EED) as the quality of service (QoS) measure, the problems of JSCC transmission are formulated to minimize the total power consumption where both relay selection and power allocation at the base station (BS) and all the relays are jointly determined. To solve the formulated problem that is nonetheless nonlinear in nature, a two-step iterative algorithm is investigated for power allocations at all transmitters, where a sequential quadratic programming method is developed to find a strict local minimum. To reduce the computation complexity, a heuristic algorithm for relay selection is presented. Case studies are conducted to verify the proposed formulations and solution methods. We will demonstrate the advantages of using the proposed relay-assisted multiresolution approach.

Abstract The paper investigates resource allocation via power control for inter‐cell interference (ICI) mitigation in an orthogonal frequency division multiple access‐based cellular network. The proposed scheme is featured by a novel subcarrier assignment mechanism at a central controller for ICI, which is further incorporated with an intelligent power control scheme. We formulate the system optimization task into a constrained optimization problem for maximizing accepted users' requirements. To improve the computation efficiency, a fast yet effective heuristic approach is introduced for divide and conquer. Simulation results demonstrate that the proposed resource allocation scheme can significantly improve the network capacity compared with a common approach by frequency reuse. Copyright © 2014 John Wiley & Sons, Ltd.

This article explores a recently introduced novel technique called the nested monitoring trail (m‐trail) method in all‐optical mesh networks for failure localization of any shared risk link group (SRLG) with up to undirected links. The nested m‐trail method decomposes each network topology that is at least ‐connected into virtual cycles and trails, in which sets of m‐trails that traverse through a common monitoring node (MN) can be obtained. The nested m‐trails are used in the monitoring burst (m‐burst) framework, in which the MN can localize any SRLG failure by inspecting the optical bursts traversing through it. An integer linear program (ILP) and a heuristic are proposed for the network decomposition, which are further verified by numerical experiments. We show that the proposed method significantly reduces the required fault localization latency compared with the existing methods. Finally, we demonstrate that nested m‐trails can also be used in adaptive probing to find SRLG faults in all‐optical networks. The nested m‐trail based probing method needs a significantly reduced number of sequential probes. Thus, the method overcomes one of the important hurdles to deploy adaptive probing in all‐optical networks: the large number of sequential probes needed to localize SRLG faults. © 2015 Wiley Periodicals, Inc. NETWORKS, Vol. 66(4), 347–363 2015

Shared protection, such as failure-dependent protection (FDP), is well recognized for its outstanding capacity efficiency in all-optical mesh networks, at the expense of lengthy restoration time due to multihop signaling mechanisms for failure localization, notification, and device configuration. This paper investigates a novel monitoring trail (m-trail) scenario, called Global Neighborhood Failure Localization (G-NFL), that aims to enable any shared protection scheme, including FDP, for achieving all-optical and ultra-fast failure restoration. We first define the neighborhood of a node, which is a set of links whose failure states should be known to the node in restoration of the corresponding working lightpaths (W-LPs). By assuming every node can obtain the on-off status of traversing m-trails and W-LPs via lambda monitoring, the proposed G-NFL problem routes a set of m-trails such that each node can localize any failure in its neighborhood. Bound analysis is performed on the minimum bandwidth required for m-trails under the proposed G-NFL problem. Then, a simple yet efficient heuristic approach is presented. Extensive simulation is conducted to verify the proposed G-NFL scenario under a number of different definitions of nodal neighborhood that concern the extent of dependency between the monitoring plane and data plane. The effect of reusing the spare capacity by FDP for supporting m-trails is examined. We conclude that the proposed G-NFL scenario enables a general shared protection scheme, toward signaling-free and ultra-fast failure restoration like p-Cycle, while achieving optimal capacity efficiency as FDP.

In this paper, we consider low-complexity detection of coded spatial data streams with uniform power and non-uniform rate distribution in a single-user MIMO system. The receiver decodes these different streams as if facing a multiple access channel (MAC). Conventional receiver solutions for such schemes are based on successive interference cancellation (SIC) by employing a linear minimum mean square error (MMSE) successive stripping detector, where the optimality is nonetheless constrained to Gaussian codebooks. As a remedy, this paper introduces a novel near-optimal low-complexity max-log-MAP demodulator for a 2×nrsystem (nris the number of receive antennas) which reduces the complexity of detection from O(|χ|2) to O(|χ|1), where |χ| indicates the size of the signal set. In the sequel, we extend the proposed low-complexity demodulation scheme to higher-dimensional MIMO systems via a hybrid detector, where significant complexity saving is realized at the expense of slight performance degradation.

Network-wide local unambiguous failure localization (NL-UFL) [1] has been demonstrated as an interesting scenario of monitoring trails (m-trails). It attempts to enable every node to autonomously localize any failure event in the network in a distributed and all-optical manner by inspecting a set of m-trails traversing through the node. This paper investigates the m-trail allocation problem under the NL-UFL scenario by taking each link and node failure event into consideration. Bound analysis is performed using combinatorial group testing (CGT) theory and this is followed by the introduction of a novel heuristic on general topologies. Extensive simulation is conducted to examine the proposed heuristic in terms of the required cover length and the number of m-trails to achieve NL-UFL.

The paper investigates the broadcast of n-layered source codes over a single-relay network using a half-duplex nonorthogonal amplify-forward (HD-NAF) relaying protocol. Taking the distortion exponent, (i.e., the SNR exponent of the average end-to-end distortion) as the performance metric, we consider system operation in the high SNR regime. We first prove that the HD-NAF relay network with an n-layer code is subject to the successively refinable Diversity Multiplexing Tradeoff (DMT) curve, which is exercised to derive a closed-form expression for an achievable upper bound of the system distortion exponent. Rate allocation optimization is conducted to analyze and gain insight into system behavior. Numerical evaluations are performed based on derived analytical formulations, and the performance advantage of single-relay HD-NAF networks is justified in terms of the distortion exponent versus its conventional counterparts. Furthermore, it is observed that increases in the number of encoded layers increases system performance.

The articles in this special issue focus on energy efficiency techniques deployed in optical fiber networking.

Cloud services based on data center networks (DCNs) require a transmission infrastructure with high-capacity, low-latency, low-cost and high-availability, which can be offered by survivable optical networks. DCN placement is a fundamental issue in supporting cloud services in optical networks. It concerns not only the cost of providing cloud services, but also the service availability against failures via proper service replicas. In this paper, we jointly optimize DCN placement with service routing and protection to minimize the network cost, while ensuring fast protection of all services against any single link failure or service failure at a particular DCN. An ILP (Integer Linear Program) is first formulated to achieve optimal joint design. It integrates p-cycle (preconfigured protection cycle) for fast protection against a single link failure, and DCN replicas and fast service rerouting against a service failure. To make the design more scalable, a two-step heuristic is then proposed for large-size network scenarios. The first step separately solves the DCN placement and service routing problem in the failure-free scenario, and the second step takes fast service protection into account. The proposed design is validated by extensive numerical experiments.

Next-generation passive optical network (PON) has been considered in the past few years as a cost-effective broadband access technology. With the ever-increasing power saving concern, energy efficiency has been an important issue in its operations. In this paper, we propose a novel sleep-time sizing and scheduling framework for the implementation of green bandwidth allocation (GBA) in TDMA-PONs. The proposed framework leverages the batch-mode transmission feature of GBA to minimize the overhead due to frequent ONU on-off transitions. The optimal sleeping time sequence of each ONU is determined in every cycle without violating the maximum delay requirement. With multiple ONUs possibly accessing the shared media simultaneously, a collision may occur. To address this problem, we propose a new sleep-time sizing mechanism, namely Sort-And-Shift (SAS), in which the ONUs are sorted according to their expected transmission start times, and their sleep times are shifted to resolve any possible collision while ensuring maximum energy saving. Results show the effectiveness of the proposed framework and highlight the merits of our solutions .

Failure dependent protection (FDP) is known to achieve optimal capacity efficiency among all types of protection, at the expense of longer recovery time and more complicated signaling overhead. This particularly hinders the usage of FDP in all-optical mesh networks. As a remedy, this paper investigates a new restoration framework that enables all-optical fault management and device configuration via state-of-the-art failure localization techniques, such as the FDP restoration process. It can be implemented without relying on any control plane signaling. With the proposed restoration framework, a novel spare capacity allocation problem is defined and is further analyzed on circulant topologies for any single link failure, aiming to gain a solid understanding of the problem. By allowing reuse of monitoring resources for restoration capacity, we are particularly interested in the monitoring resource hidden property, where less or even no monitoring resources are consumed as more working traffic is in place. To deal with general topologies, we introduce a novel heuristic approach to the proposed spare capacity allocation problem, which comprises a generic FDP survivable routing scheme followed by a novel monitoring resource allocation method. Extensive simulation is conducted to examine the proposed scheme and verify the proposed restoration framework.

In 3GPP LTE-A, Coordinated Multi-Point (CoMP) is adopted to enhance the transmission rates of edge users. To maximize the total downlink throughput of all edge users, it is crucial to properly determine the set of simultaneously served users in each physical resource block (PRB) and the cooperative base stations (BSs) for each scheduled user, as well as the transmit power of the BSs. Based on the reference signal receiving power (RSRP) of each edge user, we first propose two simple and integrated transmission scheduling algorithms, one distributed and the other centralized, to choose cell-edge users and cooperative BSs in each PRB. With the scheduling results, the classic Water-Filling (WF) algorithm is carried out over all PRBs at each BS to get an initial single cell power allocation. To take the interference among different cooperative BS sets into account, we further formulate a non-cooperative power allocation game to adjust the initial power allocation for interference coordination, where the initial power allocation provides the strategy space of the game for each BS. This increases the total downlink throughput of edge users over all BSs. We prove that the game has a unique Nash Equilibrium (NE), and design an algorithm to find the NE. Performance gain is then demonstrated through extensive simulation studies.

In the pursuit of ever increasing demand of higher data rates, modern wireless communication systems are resorting to tighter frequency reuse patterns thereby leading to interference-limited systems. Recently proposed interference-aware receiver [1] is a low complexity and efficient receiver design for interference mitigation in cellular systems. However this advanced receiver necessitates the channel knowledge of both the desired and interfering signals which may not be available in a practical system. In this paper, we investigate the performance of interference-aware receiver under imperfect channel state information (CSI). We consider uncorrelated Rayleigh flat fading channels and model the estimation error as independent complex Gaussian random variables. We derive upper bound on the pair wise error probability (PEP) and show that the interference-aware receiver is characterized by full diversity in the presence of channel estimation errors. We compare the performance of interference-aware receiver with that of MMSE receiver and show that the degradation in the performance of MMSE receiver is much more pronounced than that of interference-aware receiver under imperfect CSI.

This paper investigates monitoring burst (m-burst), an interesting framework of all-optical failure localization technique reported in [2], in all-optical networks with multi-link SRLGs up to d links. We introduce a novel m-trail allocation method for achieving local unambiguous failure localization (L-UFL), where a single monitoring node (MN) can localize any SRLG failure by inspecting the optical bursts traversing through it. In specific, the proposed m-trail method ensures that (d + 1) link-disjoint m-trails originating from the MN will traverse each link, such that any healthy link is traversed by at least one uninterrupted m-trail during an SRLG failure. As a proof of concept, we formulate two integer linear programs (ILPs) and implement the method for SRLGs with d up to 3. Numerical results show that the scheme takes very short fault localization latency, while achieving the best performance.

Deployment of femtocells faces a significant challenge emanating from the interference from the overlay of macros to the underlay of femtos. This paper focuses on the mitigation of this cross-tier interference in the downlink by limited coordination between femtocells and macrocell. Contesting the natural strategy of orthogonalized transmission thereby eliminating the interference, we propose a spectrum splitting strategy which is based on coordinating this cross-tier interference in a way that the resultant interference is effectively exploited thereby improving the system performance. The problem is posed as a single-agent control problem. Macro base station (BS) is an agent that dynamically swaps its macro users/constellations on its bandwidth to manage the interfering constellations that it produces to its femtocell users. The agent learns the optimal interfering constellation strategy using information from its femto BSs using reinforcement-learning with a Q-learning implementation. Simulation results illustrate the sum rate gain brought about by the proposed strategy of managing interfering constellations for their subsequent exploitation.

Conventional all-optical restoration strategies like p-cycle achieve very fast restoration with high spare capacity consumption. In contrast, failure dependent protection (FDP) can achieve near-optimal capacity efficiency at the cost of high signaling/control complexity (so as for long restoration time). In this paper, we investigate a previously reported all-optical restoration framework that aims to yield a restoration speed similar to p-cycle while achieving near optimal resource consumption as FDP. In particular, we propose a simple yet efficient heuristic for joint allocation of monitoring trails and protection lightpaths, which serves as the key to enable the all-optical restoration. The resultant all-optical restoration framework is further examined by extensive simulations regarding the network resource consumption, number of transmitters, monitoring requirement, and running time.

The paper investigates a novel monitoring trail (m-trail) scenario that can enable any shared protection scheme for achieving all-optical and ultra-fast failure restoration. Given a set of working (W-LPs) and protection (P-LPs) lightpaths, we firstly define the neighborhood of a node, which is a set of links whose failure states should be known to the node in restoration of the corresponding W-LPs. A set of m-trails is routed such that each node can localize any failure in its neighborhood according to the ON-OFF status of the traversing m-trails. Bound analysis is performed on the minimum bandwidth required for the m-trails. Extensive simulation is conducted to verify the proposed scheme.

In this paper, we consider broadcasting layered source codes over a single-relay network using a half duplex non-orthogonal amplify-forward (HD-NAF) relaying protocol. Distortion exponent (i.e., the SNR exponent of the average distortion) is taken to evaluate the system performance in the high SNR regime. We prove that the HD-NAF relay network with two-layered codes corresponds to a successive refinable diversity multiplexing tradeoff (DMT) curve.With the identified property, a closed-form expression for an achievable upper bound of the system distortion exponent is derived, which can be achieved via properly allocated power and rate of each layer. Numerical evaluation is conducted to show performance advantages of the considered two-layered HD-NAF protocol against its counterparts.

The paper considers the problem of single-link failure localization in all-optical mesh networks. Our study follows a generic monitoring approach using supervisory lightpaths (S-LPs), in which a set of bi-directional monitoring trails (bm-trails) are defined and closely monitored, such that the network controller can achieve unambiguous failure localization (UFL) for any single link by collecting the flooded alarms from the affected bm-trails. With a target of minimizing the number of bm-trails (or the length of alarm codes) required for single-link UFL, the paper provides optimal (or essentially optimal) solutions to the bm-trail allocation problem on a number of well known topologies. First we demonstrate that the theoretical lower bound of [log2(|E|+1)] bm-trails can be achieved in any 2 · [{ log2{(|E|+1)} }] connected graph, where |E| is the number of links. Next, we prove an essentially optimal solution for 1-by-N grid topologies (also known as chocolate bar graphs), where [{0.42+ log2{(|E|+2)}}] bm-trails can be achieved. Based on the solution for chocolate bars, we further investigate bm-trail solutions to general 2-dimensional (2D) grid topologies, and the developed solution requires no more than 3+[ log2(|E|+1)] bm-trails for UFL. Such an optimal (or essentially optimal) logarithmic behavior, although has been well observed in general topologies in our previous studies , is formalized for the first time in this paper via a suite of polynomial-time deterministic constructions that consume less than a few seconds of running time in topologies of thousands of nodes.

Multicopy routing strategies have been considered the most applicable approaches to achieve message delivery in Delay Tolerant Networks (DTNs). Epidemic routing and two-hop forwarding routing are two well-reported approaches for delay tolerant networks routing which allow multiple message replicas to be launched in order to increase message delivery ratio and/or reduce message delivery delay. This advantage, nonetheless, is at the expense of additional buffer space and bandwidth overhead. Thus, to achieve efficient utilization of network resources, it is important to come up with an effective message scheduling strategy to determine which messages should be forwarded and which should be dropped in case of buffer is full. This paper investigates a new message scheduling framework for epidemic and two-hop forwarding routing in DTNs, such that the forwarding/dropping decision can be made at a node during each contact for either optimal message delivery ratio or message delivery delay. Extensive simulation results show that the proposed message scheduling framework can achieve better performance than its counterparts.

This paper introduces a novel multicopy routing protocol, called Self-Adaptive Utility-based Routing Protocol (SAURP), for Delay Tolerant Networks (DTNs) that are possibly composed of a vast number of devices in miniature such as smart phones of heterogeneous capacities in terms of energy resources and buffer spaces. SAURP is characterized by the ability of identifying potential opportunities for forwarding messages to their destinations via a novel utility function-based mechanism, in which a suite of environment parameters, such as wireless channel condition, nodal buffer occupancy, and encounter statistics, are jointly considered. Thus, SAURP can reroute messages around nodes experiencing high-buffer occupancy, wireless interference, and/or congestion, while taking a considerably small number of transmissions. The developed utility function in SAURP is proved to be able to achieve optimal performance, which is further analyzed via a stochastic modeling approach. Extensive simulations are conducted to verify the developed analytical model and compare the proposed SAURP with a number of recently reported encounter-based routing approaches in terms of delivery ratio, delivery delay, and the number of transmissions required for each message delivery. The simulation results show that SAURP outperforms all the counterpart multicopy encounter-based routing protocols considered in the study.

Multi-user transmission, enabled through spatial multiplexing, is a promising technique in wireless systems by sending information to more than one user on a common resource block. Although efficient, precise channel information is needed in order to minimize the possible interferences. Motivated by its importance, the study investigates interference management in multi-user downlink systems under heterogeneous feedback of channel state information to the transmitter (CSIT). In the considered scenario, the base station (BS) can obtain different levels of channel realization information from the users under multi-user transmission. In particular we focus on a generic scenario with two user equipments (UEs), one (UE-1) being able to provide a perfect CSIT to the BS and the other (UE-2) unable to, where an effective transmission strategy at the BS is proposed with the premise of mitigating interference at UE-1. Unfortunately the absence of CSIT for UE-2 pushes it in interference-limited regime. To this end, two approaches are considered in the study: one by developing additional spatial diversity, and the other via advanced receiver design at UE-2. We investigate both of the options and show that the rate of UE-2 gets significantly improved in both cases. However hardware and RF design constraints may make the advanced receiver design solution preferable over the spatial diversity solution. We then put this heterogeneous CSIT feedback system in the context of long term evolution (LTE) of third generation partnership project (3GPP) where interference cannot be nulled out even for UE-1 due to the feedback of low level quantized CSIT and the restriction of the use of a very limited set of beamformers. The paper demonstrates that the advanced interference-aware receiver design can bring significant gains in the considered scenario, thereby underlining the necessity of intelligent receiver-processing in modern wireless systems.

This paper investigates joint source-channel coding (JSCC) in a decode-and-forward three-node relay network, in which scalable source coding (SSC) is coupled with superposition coding (SPC) to form a layered coding architecture of SSC-SPC. In contrast to any previously reported research using asymptotic capacity-based distortion (CBD) measure, we derive the mean-squared error end-to-end distortion (EED) of such JSCC system based on a real-valued Gaussian source, aiming to achieve better precision and practicality for applications in which channels are subject to large error probabilities. The EED evaluation is formulated and applied to demonstrate achievable gains of the SSC-SPC architecture versus a number of conventional approaches. Power allocation optimization is performed based on the developed non-asymptotic EED model and compared to that by using an asymptotic CBD measure in which symbol losses caused by channel error cannot be considered. We demonstrate the performance gaps between results solved from EED versus CBD in our numerical example, and conclude that the optimization using CBD behaves awkwardly in computing proper power allocation configurations in the considered SSC-SPC architecture.

In this paper, we look at the simplest instance of heterogeneous broadcast channel (BC) where a multi-antenna transmitter base station (BS) is trying to communicate data to two user equipments (UEs), having the perfect CSIT about UE-1 and no CSIT about UE-2. We focus on UE-2 which is severely limited by the interference of UE-1. We consider the question whether additional spatial diversity or advanced receiver design at UE-2 is feasible for mitigating this interference. We investigate both the options and show that the rate of UE-2 gets significantly improved in both cases however hardware and RF design constraints may make the advanced receiver design solution preferable over spatial diversity solution.

This paper investigates the provisioning of multi-media services from a novel perspective of reducing end-to-end distortion (EED) in a decode-and-forward relay network. Exploiting a logical mapping between scalable source information and superposition coding (SPC), a benchmark for EED evaluation is formulated and applied to demonstrate achievable gains of the SVC-SPC architecture in a fundamental three-node relay network. Performance impact under various fading channel conditions is investigated via numerical experiments when successive interference cancellation (SIC) is employed for SPC signal decoding.

We consider power allocation in energy efficient OFDM (Orthogonal Frequency Division Multiplexing) or MIMO (Multiple-Input Multiple-Output) transmissions. An energy-per-goodbit (EPG) metric is used to gauge the average energy consumed for transmitting each bit. Existing works minimize EPG by searching for a set of dual variables which are used to compute the optimal power allocation in a Water-Filling (WF) expression. The searching process is complex and requires a long running time. In this paper, we propose a new algorithm to compute the optimal power allocation without searching any dual variables. Our algorithm is based on an iterative calculation of the total transmission power and it converges when the minimum EPG is reached. It takes WF as the basic building block. Unlike the conventional WF approach which needs to search for a Lagrange multiplier (i.e., the water level), we additionally propose a novel WF algorithm without searching the Lagarange multiplier. Numerical results show that our power allocation algorithm for EPG minimization, together with the embedded fast WF algorithm, can run multiple times faster than the existing ones.

Survivable routing serves as a key role in connection-oriented communication networks for achieving desired service availability for each connection. This is particularly critical for the success of all-optical mesh networks where each lightpath carries a huge amount of data. Currently, 1+1 dedicated path protection appears to be the most widely deployed network resilience mechanism because it offers instantaneous recovery from network failures. However, 1+1 protection consumes almost twice as much capacity as required, which imposes a stringent constraint on network resource utilization. In addition, finding an SRLG-disjoint path is essential for 1+1 protection, which is nonetheless subject to non-trivial computation complexity and may fail in some SRLG scenarios. To address these problems, we introduce a novel framework of 1+1 protection, called Generalized Dedicated Protection (GDP), for achieving instantaneous recovery from any SRLG failure event. It is demonstrated, that finding a non-bifurcated optimal solution for GDP is NP-complete. Thus, the paper presents a novel scheme applying Generalized Dedicated Protection and Network Coding (GDP-NC) to ensure both optimal resource utilization among dedicated protection approaches and instantaneous recovery for single unicast flows, which can be split into multiple parts in all-optical networks. We demonstrate that the proposed GDP-NC survivable routing problem is polynomial-time solvable, owing to the ability to bifurcate flows. This flexibility comes at the expense of additional hardware for linear combination operations for the optical flows.

In LTE-A (3GPP LTE-Advance) systems, CoMP (Cooperative Multi-Point) is adopted to enhance the performance of edge users. To maximize the edge user throughput, it is very crucial to properly determine the set of simultaneously served users in the same PRB (physical resource block) and cooperating BSs (base stations) for each selected user, as well as the transmit power of the BSs. In this paper, we first propose a simple scheduling algorithm to choose cell-edge mobile stations (MSs) and cooperating BSs for each PRB according to the RSRP (reference signal receiving power) of each MS, based on which the classic Water-Filling (WF) is applied at each BS to allocate transmit power over all PRBs. However, the objective of single cell power allocation is to maximize the throughput of each individual cell without considering interference among different cooperating BS sets. Therefore, we further formulate a power reallocation mechanism using non-cooperative game theory to refine the single cell WF result for interference coordination, which maximizes the total edge user throughput over all BSs and PRBs by properly taking CCI (co-channel interference) into account. Based on proving the existence of a unique Nash Equilibrium for the formulated game, we design an algorithm to find the Nash Equilibrium and demonstrate the performance gain through extensive simulation studies.

Cascaded Passive Optical Network (PON) has been reported as an effective approach for achieving flexible deployment of optical network units (ONUs) in metropolitan areas and possibly a great cost reduction from the operator perspectives. It serves as a promising technique to support low-cost deployment of long-reach Passive Optical Networks (LRPONs), which is one of the keys to enable a fiber to the premises (FTTP) service provisioning scenario. Motivated by its future-proving importance, this paper investigates a dimensioning task which revisits the cascaded splitter topology for the LRPON new scenario. We formulate and solve the splitter topology and placement optimization problem with the objective of deployment cost minimization using Integer linear programming (ILP). Two different schemes with or without cascade splitting topology are developed and implemented via case studies. The case study results show that the cascaded splitter topology is way more cost-effective, economical, and suitable in the deployment of LRPON for FTTP in practice.

Under a given modulation scheme and a target BER (bit error rate) requirement, it is difficult to increase the number of bits transmitted in each symbol (i.e., the rate), since this generally requires a significant increase of transmit power. In this paper, we study how to increase the rate in multiuser multiple-input multiple-output (MU-MIMO) broadcast channels using only bit and power loading, without requiring additional transmit power. To solve this challenging problem, our approach is to carry out a joint design of bit loading and power allocation over all streams, and meanwhile take user and stream selection into account. Specifically, we maximize the total number of bits per symbol (rather than the Shannon capacity) over all selected streams, under a target BER constraint for each stream and a constant total transmit power constraint. To enable flexible user and stream selection as well as achieving a high total rate, we consider OSDM (orthogonal space division multiplexing) rather than BD (block diagonalization) based MU-MIMO broadcast channels. Numerical results show that our proposed joint bit and power loading with OSDM user and stream selection is effective in increasing the total transmission rate without consuming additional resources.

Monitoring trail (m-trail) has been proposed as an effective approach for link failure localization in all-optical wavelength division multiplexing (WDM) mesh networks. Previous studies in failure localization rely on alarm dissemination via control plane signaling such that the network controller can collect the flooded alarms to form an alarm code for failure identification. Such cross-layer signaling effort obviously leads to additional control complexity. This paper investigates a novel m-trail failure localization scenario, called network-wide local unambiguous failure localization (NWL-UFL), where each node can perform UFL based on locally available on–off state of traversing m-trails, such that alarm dissemination in the control plane can be completely avoided. The paper first defines and formulates the m-trail allocation problem under NWL-UFL and conducts a series of bound analysis on the cover length required for localizing any single-link failure. This is the first study on monitoring trail allocation problem that aims to gain understanding on the consumed cover length via analytical approaches due to the special feature of the NWL-UFL scenario. A novel heuristic algorithm based on random spanning tree assignment (RSTA) and greedy link swapping (GLS) is developed for solving the formulated problem. Extensive simulation on thousands of randomly generated network topologies is conducted to verify the proposed scheme by comparing it to a naive counterpart and with the derived lower bounds. We also demonstrate the impact of topology diversity on the performance of the proposed scheme as well as its scalability regarding network sizes.

This paper provides an extensive analysis on interferences due to different interfering sources within cognitive-empowered femtocell (CEF) networks. Based on the interference analysis and formulations, a stochastic dual control (SDC) approach is introduced for dynamic sensing coordination, aiming to achieving efficient interference mitigation without involving global and centralized control efforts. Simulation results show that the proposed SDC approach can effectively reduce interferences under highly dynamic environments within CEF networks when compared with other spectrum sensing strategies.

ABSTRACT This paper addresses the issues of Base station—User Association and Resources Allocation (BUA‐RA) in OFDM‐TDMA based broadband wireless access (BWA) networks under passive optical networks (PON)‐WiMAX integration. With the powerful coordination capability at the optical line terminal (OLT), a key technology of inter‐cell cooperative transmission (CT) is incorporated in the integrated network architecture, which is called cooperative PON‐WiMAX network (CPWN). To achieve an efficient integration and inter‐cell cooperative transmission in the CPWNs, the BUA‐RA scheme is critical to the Quality of Service (QoS) provisioning for each user. In order to minimize the network resource usage, we provide three new BUA‐RA schemes which first time employ the cooperative transmission in a multi‐cell BWA network. The three schemes are designed for three kinds of subscribers with different moving types, and can be adaptively applied based on the network load. Simulations are conducted to verify the proposed BUA‐RA schemes by comparing with those without cooperative transmission technology. Our results demonstrate the efficiency of our proposed schemes, which are based on mathematical formulations and linearization. Copyright © 2010 John Wiley & Sons, Ltd.

We consider energy detection based spectrum sensing for opportunistic SU (Secondary User) transmissions in cognitive radio networks. Due to the time-varying nature of wireless fading channels and PU (Primary User) activities, the instantaneous SINR (Signal to Interference plus Noise Ratio) at the SU receiver changes from slot to slot in a time-slotted system. Unlike the conventional energy detector which uses a fixed value of energy threshold to detect the PU's occurrence, we let the SU transmitter dynamically adjust the threshold according to the instantaneous SINR. Under the constraint of limiting the average interference to the PU within a target level, the objective is to maximize the SU's average transmission rate and throughput. Our task is to determine a proper policy function for threshold control, which formulates the value of the threshold as a function of the SINR to achieve the above objective. In particular, we consider a linear policy function, which allows a higher threshold and thus more aggressive SU transmissions under a larger SINR. Simulation results show that the SU's average transmission rate can be significantly improved using the optimized policy function.

Monitoring trail (m-trail) provides an efficient way to achieve fast and unambiguous failure localization (UFL) in all-optical networks. To remove electronic alarm dissemination, the extended m-trail concept allows trail status checking at each on-trail node. Each monitoring node can localize any failure using its locally available on-off status of the traversing m-trails. In this paper, we introduce a novel algorithm to unambiguously localize any SRLG failure locally at any MN. The proposed algorithm is characterized by a signalling-free alarm collection mechanism which can completely be realized in the optical domain. We will show that in the course of minimizing the number of m-trails, the consumed monitoring resources in terms of cover length can also be effectively reduced. Simulation is conducted to verify the proposed algorithm with respect to the number of m-trails, resource consumption, and running time.

Femtocell networks are widely being deployed to extend cellular network coverage in indoor environments such as office building spaces and homes. In order to mitigate possible co-channel interferences, designs based on the concept of cognitive radio (CR) that enables an overlay between macrocell (primary) and femtocells (secondary) has been considered a promising approach. The paper first introduces a general dynamic sensing mechanism, which is characterized by performing per-time-slot fast sensing upon a channel at the femto devices, in contrast to the conventional CR design that each channel is sensed for identifying available TV bands. Then, based on the proposed sensing mechanism, the paper analyzes the possible throughput achieved by a femto user via a Markov chain model. Numerical experiment is conducted to verify the proposed model and examine different sensing scenarios using the practical GSM standard parameters, and prove the effectiveness of the proposed approach.

We consider power allocation in OFDM based underlay cognitive radio networks with partially known inter-system CSI (Channel State Information). Under a given total transmit power limit at the SU (Secondary User) transmitter, the goal is to assign a certain amount of power for signal transmission in each OFDM sub-channel, such that the SU's overall throughput can be maximized, and the average interference to the PU can be kept within a target outage probability level. The existing algorithm adopts an iterative binary searching process to find the solution, where the classic Water-Filling (WF) is invoked in each loop, which needs a relatively long running time. In this paper, an efficient algorithm is proposed to solve the problem in a much simpler and faster way. Specifically, we first propose an efficient approach to implement WF based on some in-depth theoretical analysis. Then, a novel power allocation algorithm is proposed by removing the binary searching process. Our algorithm runs WF only once and then directly calculates the final solution. Numerical results show that it can run tens to hundreds times faster than the existing algorithms, depending on the total number of OFDM sub-channels.

This paper demonstrates effective strategies for reducing the end-to-end distortion in a decode-and-forward relay network, where a coded wireless multicast/broadcast system utilizes a successively refinable source along with superposition coding (SPC) at the channel to provision large-scale multimedia services. Exploiting the nature of the successive refinement of source information, where enhancement layer data refines the coarse-resolution base layer into full resolution, the proposed framework relays successive refinable information with reduced distortions through a few proposed strategies. Promising results are justified with a practical measure of perceived receiver quality known as end-to-end distortion (EED). Formulations are derived to investigate the impact to distortion when subject to varying fading channel conditions when receivers utilize successive-interference cancellation (SIC) in decoding the SPC broadcast channel. It is concluded that the relaying of solely the enhancement layer information is a more effective way to reduce distortion among other strategies, which has neither been apparent nor discovered from any previous literature.

We propose TMAC, a timestamp-ordered MAC protocol for Wireless Mesh Networks (WMNs). TMAC extends CSMA/CA by scheduling data packets based on their age. Prior to transmitting a data packet, a transmitter broadcasts a request control message appended with a timestamp to a selected list of neighbors. It can proceed with the transmission only if it receives a sufficient number of grant control messages from these neighbors. A grant message indicates that the associated data packet has the lowest timestamp of all the packets pending transmission at the local transmit queue. We demonstrate that a loose ordering of timestamps among neighboring nodes is sufficient for enforcing local fairness, subsequently leading to flow rate fairness in a multi-hop WMN. We show that TMAC can be implemented using the control frames in IEEE 802.11 stack, and thus can be easily integrated in existing 802.11-based WMNs. Our simulation results show that TMAC achieves excellent resource allocation fairness while maintaining over 90% of maximum link capacity in parking lot and large grid topologies.

In ad hoc cognitive radio (CR) networks, medium access control (MAC) design has been raised as a major challenge due to its highly dynamic nature and strong user diversity, particularly in situations where a dedicated control channel is not reserved among the distributed CR nodes. In this paper, we propose a novel Stochastic Medium Access (SMA) scheme that takes interference constraints into account to improve spectrum sharing efficiency. Specifically, the proposed SMA scheme is developed to serve in a CR network without dedicated control channels, such that the probability of successful channel accesses can be maximized. The formulated optimization problem is then solved by using a dynamic Markov-Chain Monte-Carlo scheme. Moreover, the paper introduces a suite of mechanisms for implementation of the proposed SMA scheme, including segmentation of long packets and contention resolution, which is working on top of power controlled Request-to-Send (RTS) and Clear-to-Send (CTS) exchanges in a multichannel environment. An analytical model is developed on the proposed SMA scheme using an absorbing Markov chain model to evaluate throughput of the secondary user network. Extensive simulation is conducted to study the impact of some important factors on the proposed SMA scheme, such as channel conditions and secondary traffic loads.

The presence of a predefined control channel in ad hoc wireless networks is a common assumption widely accepted by the research community. However, it may not always be the case in some future networking scenarios with high-network dynamics and strong user diversity, such as cognitive radio (CR) ad hoc networks. This paper investigates channel negotiation in CR ad hoc networks without a predefined control channel by introducing a novel gossip-enabled stochastic channel negotiation (GES-CN) framework. The channel negotiation process is first formulated as an optimization problem, aiming to improve the probability of successful channel negotiation in the CR network while achieving sufficient suppression on the interferences to the primary networks. With the GES-CN framework, we develop an analytical model on the probability of successful channel negotiation as well as the resultant overhead in terms of the number of channel negotiation attempts made before achieving a successful channel negotiation process via an absorbing Markov chain. Numerical results demonstrate the merits of the proposed GES-CN framework and validate the developed analytical model. We conclude that the proposed GES-CN framework is an excellent candidate for the future distributed CR ad hoc networks with high dynamics and heterogeneity.

Being reported as the most general monitoring structure for out-of-band failure localization approach, the monitoring trail (m-trail) framework has been witnessed with great efficiency and promises to serve in the future Internet backbone with all-optical mesh wavelength division multiplex (WDM) networks. Motivated by its potential and significance, this paper investigates failure localization in all-optical mesh networks using m-trails. By considering shared risk link groups (SRLGs) with up to all adjacent links of any node in the network, a novel algorithm of m-trail allocation for achieving unambiguous failure localization (UFL) of any single SRLG failure is developed. The proposed algorithm aims to minimize the number of required m-trails and can achieve superb performance with respect to the computation efficiency. We claim that among all the previously reported counterparts, this paper has considered one of the most applicable scenarios to the design of network backbone, and the proposed method can be easily extended to the case of node failure localization. Extensive simulation is conducted to verify the proposed algorithm in comparison to its existing counterparts.

Achieving fast and precise failure localization has long been a highly desired feature in all-optical mesh networks. Monitoring trail (m-trail) has been proposed as the most general monitoring structure for achieving unambiguous failure localization (UFL) of any single link failure while effectively reducing the amount of alarm signals flooding the networks. However, it is critical to come up with a fast and intelligent m-trail design approach for minimizing the number of m-trails and the total bandwidth consumed, which ubiquitously determines the length of the alarm code and bandwidth overhead for the m-trail deployment, respectively. In this paper, the m-trail design problem is investigated. To gain a deeper understanding of the problem, we first conduct a bound analysis on the minimum length of alarm code of each link required for UFL on the most sparse (i.e., ring) and dense (i.e., fully meshed) topologies. Then, a novel algorithm based on random code assignment (RCA) and random code swapping (RCS) is developed for solving the m-trail design problem. The algorithm is verified by comparison to an integer linear program (ILP) approach, and the results demonstrate its superiority in minimizing the fault management cost and bandwidth consumption while achieving significant reduction in computation time. To investigate the impact of topology diversity, extensive simulation is conducted on thousands of random network topologies with systematically increased network density.

The integration of Ethernet Passive Optical Networks (EPONs) and IEEE 802.16 (WiMAX) has been lately presented as a promising fiber-wireless (FiWi) broadband access network. Conversely, lightweight layer-2 virtual private networks (VPNs) over FiWi, which can provide bandwidth guarantee to the respective users, were only recently addressed by Dhaini et. al. In this paper, WiMAX-VPON, the framework proposed by Dhaini et. al to support layer-2 VPNs over EPON-WiMAX, is improved to take into account the polling control overhead when distributing the VPN bandwidth. A new generic analytical model is also presented to evaluate the performance of each registered VPN service. Our proposed model, which can also be used to analyze any polling-based FiWi network, applies for wireless and optical domains and provides performance measurements such as packet queuing delay, end-to-end (from wireless user to optical server) packet delay and average queue size. Numerical results are compared with simulation experiments, and show consistency between both outcomes.

Emerging 4G standards, such as WiMAX, LTE, and TD-SCDMA, have adopted the proven technique of Adaptive Modulation and Coding (AMC) to dynamically react to channel fluctuations while maintaining bit- error rate targets of the transmission. To mitigate the vicious effects due to stale channel state indication (CSI) problem, this paper introduces a novel framework by incorporating AMC with layered transmission through Superposition Coding (SPC). A Markov chain model is adopted under this framework, to effectively assist the system in selecting the optimal modulation and coding scheme for each layer in every multi-resolution unicast transmission. Extensive simulation is conducted to verify the proposed framework and compare it with a number of counterparts. The results demonstrate that the proposed framework can achieve a much better spectrum efficiency due to improved robustness by addressing the stale CSI problem at each multi-resolution modulated transmission.

The wireless networks lack a physical boundary due to the broadcasting nature of wireless transmissions. The security has become a critical concern in the physical layer of wireless networks. In this work, we present a cross-layer security scheme for STBC system. By introducing a distort signal set the sender randomly flip-flops between the distort signal set and the orthogonal code set to confuse the attacker. The physical-layer security is enhanced as a result. In the proposed scheme the physical-layer may rely on upper-layer encryption techniques for security, which results in a cross-layer security scheme.

We study SRLG (Shared Risk Link Group) failure monitoring and localization in all-optical WDM (Wavelength Division Multiplexing) networks. All links in each SRLG are logically grouped as a whole, and they fail at the same time when the SRLG failure event occurs. To achieve fast SRLG failure localization, monitoring is carried out at the optical layer using the recently proposed monitoring trail (m-trail) structure. By formulating an ILP (Integer Linear Program), we optimally solve the m-trail allocation problem to achieve unambiguous SRLG failure localization with the minimum monitoring cost. We claim that our work provides the first study in optimally allocating free-routed m-trails for achieving fast and unambiguous SRLG failure localization, with flexible tradeoff between the monitor cost and the bandwidth cost (i.e., supervisory wavelength-links).

Due to the heterogeneity and versatility of emerging services and applications in wireless networks, it has been a great challenge on improving the network utility by taking advantage of the spatial and temporal diversity of radio resource consumption. This paper is committed to solving this problem by introducing a service-aware spectrum sharing algorithm (SSA) in a joint radio resource management (JRRM) architecture, where a spectrum pool is adopted for leisure spectrum resource management in heterogeneous wireless networks. Based on an objective utility function, the JRRM unit could optimize the spectrum scheduling decisions for the composing networks with awareness of the related supporting services. Moreover, to facilitate a precise decision process, we illustrate an transmission rate requirement prediction model (TRPM) that is adaptive to the system condition variants to forecast service requests. Experiment results show that the proposed SSA can solidly enhance the system performance in terms of radio resource usage ratio, system throughput, user service access ratio, and eventually achieve better network utility.

Achieving fast, precise, and scalable fault localization has long been a highly desired feature in all-optical mesh networks. Monitoring tree (m-tree) is an interesting method that has been introduced as the most general monitoring structure for achieving unambiguous failure localization (UFL). Ideally, with J m-trees one can monitor up to 2J-1 links when a single failure has to be located. Such a logarithmic behavior has also been observed in numerous case studies of real life network topologies. It is expected that the m-tree framework will lead to a highly scalable link failure monitoring mechanism for not only all-optical mesh networks, but any possible future information system with mesh topologies, such as all-optical mesh networks, touch panels, quantum computing, and VLSI. It is an important task to investigate the extent such an optimal logarithmic behavior may hold, in particular in practically relevant network topologies. As an endeavor toward this goal, the paper investigates the problem by identifying essentially tight logarithmic bounds for two dimensional lattice networks. Experiments are conducted to show the feasibility and performance of the proposed constructions.

In this paper, we propose a trust opinion aggregation scheme in vehicular ad-hoc networks, to support trust models used to evaluate the quality of information shared among peers in the environment. Our scheme extends an existing identity-based aggregate signature algorithm to correctly combine signatures for multiple messages into one aggregate signature and eliminate signature redundancy. As a result, our proposed scheme is secure and archives both space efficiency and time efficiency, as confirmed by our comparative analysis.

This paper introduces a novel routing protocol in Delay Tolerant Networks (DTNs), aiming to solve the online distributed routing problem. By manipulating a collaborative reinforcement learning technique, a group of nodes can cooperate with each other and make a forwarding decision for the stored messages based on a cost function at each contact with another node. The proposed protocol is characterized by not only considering the contact time statistics under a novel contact model, but also looks into the feedback on user behavior and network conditions, such as congestion and buffer occupancy sampled during each previous contact with any other node. Therefore, the proposed protocol can achieve high efficiency via an adaptive and intelligent routing mechanism according to network conditions. Extensive simulation is conducted to verify the proposed protocol, where a comparison is made with a number of existing encounter-based routing protocols in term of the number of transmissions of each message, message delivery delay, and delivery ratio. The results of the simulation demonstrate the effectiveness of the proposed technique.

The paper introduces a novel message authentication framework over broadcast channels, where a symmetric cryptography-based physical layer assisted message authentication (PLAA) scheme is introduced in wireless networks. The proposed framework integrate the conventional message authentication schemes and the physical layer authentication mechanisms by taking advantage of temporal and spatial uniqueness in physical layer channel responses, aiming to achieving fast authentication while minimising the packet transmission overhead. Our claims through extensive analysis and simulation will be verified via comparing with public key infrastructure-based PLAA scheme and traditional upper layer authentication schemes.

To satisfy the stringent requirement of capacity enhancement in wireless networks, cooperative relaying is envisioned as one of the most effective solutions. In this paper, we study the capacity enhancement problem by way of Relay Stations (RSs) placement to achieve an efficient and scalable design in broadband wireless access networks. To fully exploit the performance benefits of cooperative relaying, we develop an optimization framework to maximize the capacity as well as to meet the minimal traffic demand by each Subscriber Station (SS). In specific, the problem of joint RS placement and bandwidth allocation is formulated into a mixed-integer nonlinear program. We reformulate it into an integer linear program which is solvable by CPLEX. To avoid exponential computation time, a heuristic algorithm is proposed to efficiently solve the formulated problem. Numerical analysis is conducted through case studies to demonstrate the performance gain of cooperative relaying and the comparison between the proposed heuristic algorithm against the optimal solutions.

In this paper, a novel scheme for cognitive radio (CR) spectrum sensing in medium access control (MAC) layer, called as extended knowledge-based reasoning (EKBR), is proposed. The target of EKBR is to improve the fine sensing efficiency by jointly considering a number of network states and environmental statistics, including fast sensing results, short-term statistical information, channel quality, data transmission rate, and channel contention characteristics. This is for a better estimation on the optimal range of spectrum for fine sensing so as to adaptively reduce the overall channel sensing time. Performance analysis is conducted on the proposed EKBR scheme using a multidimensional absorbing Markov chain to evaluate various performance metrics of interest, such as average sensing delay (or referred to as sensing overhead in the study), average data transmission rate, and percentage of missed spectrum opportunities. Numerical results show that the proposed EKBR scheme achieves better performance than that by the state-or-the-art techniques while yielding less computation complexity and sensing overhead.

Abstract In IEEE 802.16 networks, a subscriber station (SS) could be a single mobile user, a residence house, or an office building providing Internet service for multiple customers. Considering the heterogeneity among SSs which have diverse traffic demands, in this paper, we introduce the weighted proportional fair (WPF) scheduling scheme for the Best Effort (BE) service in IEEE 802.16 networks to achieve the flexible and efficient resource allocation. We develop an analytical model to investigate the performance of WPF in terms of spectral efficiency, throughput, resource utilization, and fairness, where the Rayleigh fading channel and the adaptive modulation and coding (AMC) technique are considered. Extensive simulations are conducted to illustrate the efficiency of the WPF scheduling scheme and verify the accuracy of the analytical model. Copyright © 2009 John Wiley & Sons, Ltd.

In this paper, a novel cooperative stochastic channel prioritization algorithm is presented for the purpose of improving spectrum sensing efficiency in cooperative cognitive radio systems. The proposed algorithm achieves the goal by prioritizing the channels for fine sensing based on both local statistics obtained by the cognitive radio as well as long-term spatiotemporal statistics obtained from other cognitive radios. Channel priority is determined in a stochastic manner by performing statistical fusion on the local statistics and statistics from neighboring cognitive radios to obtain a biasing density from which stochastic sampling can be used to identify the likelihood of channel availability. Therefore, the individual cognitive radios collaborate to improve the likelihood of each cognitive radio in obtaining available channels. Simulation results show that the proposed cooperative stochastic channel prioritization algorithm can be used to reduce both sensing overhead and percentage of missed opportunities when implemented in a complimentary manner with existing cooperative cognitive radio systems.

This paper introduces a multi-copy routing protocol, called Self Adaptive Routing Protocol (SARP), for intermittently connected mobile networks. SARP aims to exploring the possibility of taking nodes as carriers of messages to be delivered among network partitions. The choice of the best carrier for a message is made according to the prediction based on the history of nodal encounters. The paper will argue that the movement of the nodes and their possible future collocation with the recipient of the messages can be used to make intelligent message forwarding decisions. The proposed protocol has been implemented and compared to a number of existing encounter-based routing approaches, where a near-realistic mobility model is used for testing. The performance of the proposed technique is evaluated in terms of delivery delay and the number of transmissions performed. The results of the simulation show that the proposed technique outperforms all existing multi-copy encounter-based routing protocols. Index terms: DTN, multi-copy routing.

In this paper, we introduce a novel framework for physical layer assisted message authentication (PAA) under public key infrastructure (PKI) in vehicular communication networks. The proposed framework takes advantage of temporal and spatial uniqueness in physical layer channel responses for each transmission pair, in which a trust between two vehicles can be maintained by comparing the current estimated channel response and the previous estimated channel response. We will show that the proposed message authentication framework can achieve extremely high efficiency and minimal authentication delay without compromising the security requirements, which is further verified through both analysis and simulation.

In Mobile Ad Hoc Networks (MANET), anomaly detection and response system (ADRS) plays a paramount role in diagnosing anomalous events, which are resulted by both accidental system errors and intentional attacks. While a variety of ADRS is ready for deployment, there lacks a sound and formal way to examine their operational characteristics for selecting the most appropriate ones with particular concerns. To that end, this paper develops a decision-theoretical framework to identify the fundamental tradeoffs between the key evaluation metrics of ADRS in MANET, along with a formal method to optimize the overall performance of ADRS in terms of those metrics of concern. In particular, each ADRS sensor is treated as an autonomous agent, making its decision as the local operational environment and a global signal that estimates the performance of ADRS as a whole, in terms of detection performance (detection accuracy and false positive rate) and operational cost (detection cost and response cost). The theoretical framework then serves as a basis for developing policy gradient algorithms for practically and automatically inferring the optimal behavior of ADRS sensors. A set of simulations is conducted for validating the feasibility and evaluating the performance of our proposed framework.

Achieving fast and precise failure localization has long been a highly desired feature in all-optical mesh networks. M-trail (monitoring trail) has been proposed as the most general monitoring structure for achieving unambiguous failure localization (UFL) of any single link failure while effectively reducing the amount of alarm signals flooded in the networks. However, it is critical to come up with a fast and intelligent m-trail design approach for minimizing the number of m-trails and the totally consumed bandwidth, which ubiquitously determines the length of alarm code and bandwidth overhead for the M-trail deployment, respectively. In this paper, the m-trail design problem is investigated. To gain deeper understanding of the problem, we firstly conduct a bound analysis on the minimum length of alarm code required for UFL. Then, a novel algorithm based on random code assignment (RCA) and random code swapping (RCS) is developed for solving the m-trail design problem. The algorithm prototype can be found in. The algorithm is verified by comparing with an integer linear program (ILP), and the results demonstrate its superiority in minimizing the fault management cost and bandwidth consumption while achieving significant reduction in computation time. To investigate the impact of topology diversity, extensive simulation is conducted on thousands of random network topologies with systematically increased network connectivity. Lastly, we provide abundant discussions and interesting conclusive remarks that position our discoveries.

We introduce Cooperative Fast Protection (CFP) as a novel protection scheme in WDM networks. CFP achieves capacity-efficient fast protection with the features of node-autonomy and failure-independency. It differs from p-cycle by reusing the released working capacity of the disrupted lightpaths (i.e. stubs) in a cooperative manner. This is achieved by allowing all the failure-aware nodes to switch the traffic, such that the disrupted lightpaths can be protected even if the end nodes of the failed link are not on the protecting cycles. CFP also differs from FIPP p-cycle by not requiring the source node of the disrupted lightpath on the protecting cycle. By jointly optimizing both working and spare capacity placement, we formulate an ILP for CFP design. Numerical results show that CFP significantly outperforms p-cycle by achieving faster protection with much higher capacity efficiency.

To satisfy the stringent requirement of capacity enhancement in wireless networks, cooperative relaying is envisioned as one of the most effective solutions. In this paper, we focus on the problem of capacity enhancement by way of relay stations (RSs) placement, which is a critical task of network planning and deployment to achieve an efficient and scalable network design. To fully exploit the performance benefits of cooperative relaying, we develop an optimization framework to maximize the capacity as well as meet the minimal traffic demand for each subscriber station (SS). The problem of joint RS placement and bandwidth allocation is formulated into a mixed integer nonlinear program and solved through a heuristic approach based on genetic algorithm (GA). Moreover, an upper bound on the capacity is derived to assist the estimation of system performance given a network configuration. Numerical results are presented to demonstrate the effectiveness of the solution approach and the performance benefits due to RS placement and optimal bandwidth allocation through cooperative relaying.

In this paper, a novel statistics-driven spectrum sensing algorithm is developed for improving spectrum sensing efficiency in the media access control (MAC) layer of cognitive radio (CR) systems. The proposed algorithm aims to achieve higher spectrum sensing efficiency and spectrum access opportunity by prioritizing channels for fine sensing based on the statistical likelihood of channel availability. The sensing priority is obtained by jointly exploiting the long-term spatiotemporal statistics recorded from the historical result of fine sensing, the short-term statistical information of channel condition obtained from a small-scale observation window, and the instantaneous statistical information obtained from fast sensing. Simulation results show that the proposed prioritization algorithm can achieve improved data transmission rates and reduced missed spectrum access opportunities when compared to the conventional non- prioritization spectrum sensing approach for situations where cooperative spectrum sensing is not suitable.

This paper introduces a cross-layer design framework for robust and efficient video multicasting over IEEE 802.16 (also known as WiMAX) networks in metropolitan areas. In the framework, multiple description coding (MDC) on scalable video bitstreams at the source for achieving multiresolution robustness is jointly designed with superposition coding (SCM) on multicast signals at the channel to overcome multiuser channel diversity in wireless multicast. The coded multicast signals under the proposed framework can cope with multiuser channel diversity and mitigate the impact due to short-term channel fluctuations, which are the two most challenging issues in achieving robust and efficient video multicasting in metropolitan areas. We formulate the proposed framework and analyze its video quality performance in terms of the total receivable/ recoverable bitstreams by a receiver. A heuristic methodology is developed for system parameter selection and performance optimization that can be applied to practical scenarios of video multicasting for IPTV services in WiMAX. Simulation is conducted based on actual standard video sequences to verify the proposed methodology on parameter selection and performance optimization. Performance gains of the proposed cross-layer design framework in the presence of fading channel diversity are demonstrated.

It has been well recognized as an efficient approach for broadcasting popular videos by partitioning a video data stream into multiple segments and launching each segment through an individual channel simultaneously and periodically. Based on the design premises, some recent studies, including skyscraper broadcasting (SkB), client-centric approach (CCA), greedy disk-conserving broadcasting (GDB), and reverse fast broadcasting (RFB) schemes, etc., have been reported. To study the client segment downloading process, this paper first introduces an applicable sequence-based broadcasting model that can be used to minimize the required buffer size. By extending RFB, this paper further proposes a reverse sequence-based broadcasting model, which can generally improve the existing schemes such as SkB, CCA, GDB, and FB in terms of the relaxed client buffer size. To have a deeper understanding on the proposed reverse model, the upper bound of the client buffer requirement is obtained through a comprehensive analysis, which is proved to be much smaller than the conventional sequence model by 25% to 50%. Based on the proposed reverse model, a reverse sequence-based broadcasting scheme is developed for achieving smaller delay than CCA and GDB.

Multicast communications is an efficient mechanism for one-to-many transmissions over a broadcast wireless channel, and is considered as a key technology for supporting emerging broadband multimedia services in the next generation wireless networks, such as Internet Protocol Television (IPTV), mobile TV, etc. Therefore, it is critical to design efficient multicast scheduling schemes to support these multimedia services. In this paper, we propose a cooperative multicast scheduling scheme for achieving efficient and reliable multicast transmission in IEEE 802.16 based wireless metropolitan area networks (WMAN). By exploiting the multi-channel diversity across different multicast groups and user cooperation among group members, the proposed scheme can achieve higher throughput than existing multicast schemes, for subscriber stations in both good and bad channel conditions. In addition, it has good fairness performance by considering the normalized relative channel condition of each multicast group. An analytical model is developed to evaluate the performance of the proposed scheme, in terms of service probability, power consumption, and throughput of each group member and multicast groups. The efficiency of the proposed scheme and the accuracy of the analytical model are corroborated by extensive simulations.

This paper proposes an efficient yet simple design framework for achieving flexible resource allocation and packet scheduling for non-real-time polling service (nrtPS) traffic in IEEE 802.16 networks. By jointly considering the selective automatic repeat request mechanism at the media access control layer as well as the adaptive modulation and coding technique at the physical layer, the proposed framework enables a graceful tradeoff between resource utilization and packet delivery delay while maintaining the minimum throughput requirements of nrtPS applications. An analytical model is developed for parameter manipulation in the proposed framework, where some important performance metrics, such as inter-service time, delivery delay, goodput, and resource utilization, are investigated for performance evaluation. Simulation results are given to demonstrate the efficiency of the proposed framework and verify the accuracy of the analytical model.

This paper studies the problem of network dimensioning and location planning (DLP) in multi-hop wireless networks by incorporating recent advances in wireless multilevel cooperative relaying (CR), which has been recognized as an effective design paradigm for achieving throughput/capacity enhancement in modern metropolitan area networks. The paper is committed to develop an optimization framework and a suite of decent solution approaches which can manipulatively capture the nature of the DLP problem and precisely characterize the behavior of multi-level cooperative relaying. For this purpose, the tasks of dimensioning, relay placement, relay allocation, and signal relay sequence design are jointly considered and accommodated into a unified framework. To make the solution of the optimization problem computationally tractable, a heuristic two-phase algorithm is developed. Simulation and case studies are conducted to verify the proposed optimization framework, and the results demonstrate the significant cost reduction and achievable rate improvement due to multi-level CR.

While Markov reward models (MRMs) have been widely used for system dependability evaluation, their application for evaluating security still poses as a challenge. It is observed that attacker behavior plays a key role in causing models of security evaluation to be complicated. Another observation is that representing attacker behavior in terms of attack effects instead of attack itself enables the system security to be indirectly evaluated by identifying families of attacks rather than individual instantiations. Furthermore, an attacker behavior tends to be affected by defense mechanisms (we say defender) due to their close interactions. These observations motivate us to boost MRMs to the security context by extracting the behaviors of attacker and defender. To do that, we present a general yet simple state- based approach to characterizing and inferring the behaviors of attackers and defenders in typical network attacks. It specifically contributes in two folds: 1) two objective-oriented models are developed to measure the attacker's and defender's behaviors, respectively; 2) the objectives, actions, and the resultant effects by the attacker and defender, along with the underlying system states, are then integrated and formulated as partially observable Markov decision processes. The developed models and analysis allow the behaviors of attacker and defender to be characterized in a fine-grained way, and specific attack-defense strategies to be inferred approximately via existing model-based algorithms. The system security hereby can be indirectly validated on the basis of the aggregated effects resulted from the interactive behaviors of attacker and defender. A real trace study is conducted to show feasibility and effectiveness of our proposed approach.

This paper tackles a fundamental problem of network planning and dimensioning under EPON-WiMAX integration for next-generation wireless metropolitan-area broadband access. Due to the powerful coordination capability of the optical line terminal (OLT), inter-cell collaboration through physical layer cooperative transmission (CT) among the optical network unit-base stations (ONU-BSs) can be initiated. In order to achieve the most efficient deployment of network infrastructure and meet the long-term performance requirements, the proposed planning and dimensioning model jointly considers the problems of ONU-BS placement, BS-User (BU) association, and resource breakdown assignment (RBA), which are further formulated into a combinatorial optimization problem. To linearize the problem formulation, an approach based on decomposition and Special Ordered Set of Type 1 (SOS1) remodeling method is developed such that the reformulated problem can simply be solved by CPLEX. Case studies are conducted to demonstrate the performance gain in terms of total infrastructure cost and spectra efficiency against the case without considering collaboration among the ONU-BSs and optimal RBA.

We consider optical layer monitoring schemes for fast link failure localization in WDM mesh networks. A new concept monitoring trail (m-trail) is proposed. It differs from the existing monitoring cycle (m-cycle) concept by removing the cycle constraint. As a result, m-trail provides a more flexible all-optical monitoring structure which includes simple, non-simple m-cycles and open trails as special cases. Aiming at minimizing the total monitoring cost, an integer linear program (ILP) is formulated for m-trail design. Numerical results show that the m-trail based scheme significantly outperforms its m-cycle based counterpart.

To realize efficient in-transit messages (bundles) authentication in delay tolerant networks (DTNs), this paper introduces a novel batch bundle authentication (BBA) scheme to validate the bundles in a batch instead of authenticating them one by one. We take the advantage of identity based cryptography to dramatically reduce the transmission cost, and adopt batch signature technique to realize the efficient bundle signature verification. Compared with existing message authentication approaches, our scheme has the superiority on improved efficiency even under the invalid signature attack. Simulation results demonstrate that the proposed scheme can be an enhancement for current bundle security protocol specification.

Exploiting the broadcast nature of wireless communications, multicast transmission is an efficient way to improve the network throughput by transmitting the same contents to multiple receivers simultaneously. It has been considered as a key technology for supporting emerging services in next-generation IEEE 802.16 based wireless metropolitan area networks (WMANs), such as Internet Protocol TV (IPTV) and mobile TV. Therefore, it is critical to devise efficient multicast scheduling schemes to support these multimedia services. In this paper, we propose a novel multicast scheduling scheme, using downlink cooperative transmission for achieving high throughput not only for all multicast groups but also for each group member. Extensive simulations are conducted to demonstrate the effectiveness and efficiency of the proposed scheme.

In IEEE 802.16 networks, a subscriber station (SS) could be a single mobile user, a residence house, or an office building providing Internet service for multiple customers. Considering the heterogeneity among SSs which have different traffic load/demands, in the paper, we introduce the weighted proportional fair (WPF) scheduling scheme for best effort (BE) service in IEEE 802.16 networks to achieve the flexible and efficient resource allocation. Furthermore, an analytical model is developed to investigate the performance of WPF in terms of spectral efficiency, throughput, resource utilization, and fairness. Extensive simulations are conducted to illustrate the efficiency of the proposed scheme and verify the accuracy of the analytical model.

Cooperative relaying is one of the most effective techniques in coverage extension and capacity enhancement by virtue of spatial diversity. To fully explore the benefits of adopting relay stations (RSs), a vital issue is the placement of RSs by jointly considering an advanced coding scheme. In this paper, we aim to provide a general framework for solving the minimum cost RS placement problem in 802.16J Mobile Multi-hop Relay (MMR) networks. We first introduce a novel dual-relay architecture, where all the users, i.e., the mobile stations (MSs) and the fixed subscriber stations (SSs), are connected to the BS via two active RSs through decoded-and-forwarding scheme. We will then demonstrate that the most significant advantages of the dual-relay architecture lie in the ability of achieving high throughput for the systems. In addition, the users can be subject to better fault tolerance, robustness, and power saving. We formulate the dual- relay RS placement problem, and solve it through a two-phase algorithm to deal with the NP-hardness. Numerical analysis is conducted to evaluate the performance gain due to cooperative RS placement in the proposed framework, and demonstrate that the proposed approach can lead to a well acceptable solution compared with that by exhaustively searching.

To enable the practical electronic cash systems, significant attention has been paid to the partially blind signature because of its unlinkability and unforgeability. To the best of our knowledge, most of partially blind signature schemes are constructed under either the traditional public key certificate based system or the ID-based system, which may incur significant efforts in certification management and/or revocation. In this paper, we introduce a novel approach for partially blind signature with self-certified public keys. This is the first research effort for significantly reducing the certificate management and revocation in partially blind signature, and is characterized by the adoption of bilinear pairings and the analytic techniques of provable security.

Wireless sensor networking is an emerging technology, which potentially supports many emerging applications for both civilian and military purposes, ranging from environmental monitoring to battlefield surveillance. However, since sensor nodes are inexpensive devices, which could be easily compromised and controlled by an adversary, the compromised nodes could report false sensed results and degrade the reliability of the whole network. Therefore, how to identify these compromised nodes in a wireless sensor network is a very important security issue. To solve this problem, we propose an efficient algorithm, called AICN, to logically identify the compromised nodes in an efficient and effective way. Based on the network reliability estimation (NRE), we also present its enhanced version to further improve the efficiency.

Reliability is crucial for high speed backbone networks. Protection mechanisms are therefore critical in the design of infrastructure networks. This paper investigates a new multi- path provisioning model with availability-guarantee on networks where events of up to two simultaneous link failures can occur. A service level agreement (SLA) which mandates service availability must be met even during network failure situations. We present a mathematical formulation to perform optimal capacity allocation in both GMPLS Self-protecting Multi-path (SPM) environment and SONET/SDH networks. Linear Programming (LP) and Integer Linear Programming (ILP) models are formulated in this study to provide multi-path protection mechanisms on MPLS and SONET/SDH networks. Network Service Providers (NSP) could use this mathematical model to design a network with certain availability requirement according to a priori defined SLAs to accommodate network traffic under dual link failure scenarios.

The concept ofp-cycle (Preconfigured Protection Cycle) allows fast and efficient span protection in WDM mesh networks. Compared to a simpler-cycle, a non-simplep-cycle can traverse a node or span multiple times. As a result, non-simplep- cycles can better explore mesh connectivity of a network. On the other hand, the recently proposed PXT (Pre-Cross-Connected Trail) concept removes the cycle constraint by allowing arbitrary protection trails. In this paper, we carry out a comparative study among these fast protection schemes, and formulate ILPs (Integer Linear Programs) for non-simplep-cycle and PXT design. As far as we know, our ILP for non-simplep-cycle design is the first one without candidate cycle enumeration, and our ILP for PXT design is the first one proposed in this area. Based on our ILPs, we find simple, non-simplep-cycle and PXT solutions for a simple network. We show that the required spare capacity for 100% protection in each scheme is reduced in the same order above.

Addressing security and privacy issues is a prerequisite for a market-ready vehicular communication network. Although recent related studies have already addressed most of these issues, few of them have taken scalability issues into consideration. When the traffic density becomes larger, a vehicle cannot verify all signatures of the messages sent by its neighbors in a timely manner, which results in message loss. Communication overhead as another issue has also not been well addressed in previously reported studies. To deal with these issues, this paper introduces a novel RSU-aided messages authentication scheme, called RAISE. With RAISE, roadside units (RSUs) are responsible for verifying the authenticity of the messages sent from vehicles and for notifying the results back to vehicles. In addition, our scheme adopts the k-anonymity approach to protect user identity privacy, where an adversary cannot associate a message with a particular vehicle. Extensive simulations are conducted to verify the proposed scheme, which demonstrates that RAISE yields much better performance than any of the previously reported counterparts in terms of message loss ratio and delay.

To achieve efficient authentication on emergency events in vehicular ad hoc networks, we introduce a novel aggregated emergency message authentication (AEMA) scheme to validate an emergency event. We make use of syntactic aggregation and cryptographic aggregation techniques to dramatically reduce the transmission cost, and adopt batch verification technique for efficient emergency messages verification. Compared with existing emergency message authentication approaches, our scheme shows the superiority on generality, enhanced security and efficiency.

We introduce an efficient conditional privacy preservation (ECPP) protocol in vehicular ad hoc networks (VANETs) to address the issue on anonymous authentication for safety messages with authority traceability. The proposed protocol is characterized by the generation of on-the-fly short-time anonymous keys between on-board units (OBUs) and roadside units (RSUs), which can provide fast anonymous authentication and privacy tracking while minimizing the required storage for short-time anonymous keys. We demonstrate the merits gained by the proposed protocol through extensive analysis.

With the adoption of state-of-the-art telecommunication technologies for sensing and collecting traffic related information, Vehicular Sensor Networks (VSNs) have emerged as a new application scenario that is envisioned to revolutionize the human driving experiences and traffic flow control systems. To avoid any possible malicious attack and resource abuse, employing a digital signature scheme is widely recognized as the most effective approach for VSNs to achieve authentication, integrity, and validity. However, when the number of signatures received by a Roadside Unit (RSU) becomes large, a scalability problem emerges immediately, where the RSU could be difficult to sequentially verify each received signature within 300 ms interval according to the current Dedicated Short Range Communications (DSRC) broadcast protocol. We introduce an efficient batch signature verification scheme for communications between vehicles and RSUs (or termed vehicle- to-Infrastructure (V2I) communications), in which an RSU can verify multiple received signatures at the same time such that the total verification time can be dramatically reduced. We demonstrate that the proposed scheme can achieve conditional privacy preservation that is essential in VSNs, where each message launched by a vehicle is mapped to a distinct pseudo identity, while a trust authority can always retrieve the real identity of a vehicle from any pseudo identity. With the proposed scheme, since identity-based cryptography is employed in generating private keys for pseudo identities, certificates are not needed and thus transmission overhead can be significantly reduced.

To achieve secure group communications, it is critical to develop a secure group key management strategy to guarantee security of the group keys. In this paper, based on the forward security and secret sharing techniques, we propose a new dynamic group key management scheme to minimize the rekeying cost. The forward security technique reduces the rekeying operations in joining event, while the secret sharing technique ensures the scalability in leaving event. In addition, the proposed scheme can provide anonymous authentication as well as forward and backward confidentiality. Theoretical analysis also confirms the efficiency of the proposed scheme.

To enhance the overall performance of a mobile ad hoc network (MANET), people have tried to solve the issue of node selfishness, which has sparked a surge of research interests in credit-based incentive protocols. The core idea of credit-based incentive is to provide incentives for selfish nodes to faithfully forward packets in a MANET. Recently, several credit-based incentive protocols have been proposed. However, the fairness issue in those reported credit-based incentive protocols has never been well addressed yet. Without the fairness guarantees, the whole network still cannot reach its optimum cooperative status. Therefore, in this paper, aiming at fairness, we first define the fairness principle for credit-based incentive protocol, and then present a novel fair incentive protocol (FIP) for MANETs.

A cross-layer design (CLD) framework for robust and efficient video multicasting over IEEE 802.16 (or WiMAX) is introduced. In the framework, multiple description coding on scalable video bitstreams at the source for achieving multi-resolution robustness is jointly designed with superposition coding (i.e., multi-resolution modulation) on multicast signals at the channel to overcome the channel diversity problem in wireless multicast. The resulting cross-layer coded multicast signals enable us to recover some lost bitstreams in high quality layers, which is not possible if multi-resolution modulation is used alone for multicasting as in previous works. Simulation results show that indeed our joint design outperforms the scheme using only superposition coded multicast by achieving better video quality for users under multi-user channel diversity.

As an emerging application scenario of wireless technologies, vehicular communications have been initiated not only for enhancing the transportation safety and driving experiences, but also for a new commercial market of on-board Internet services. Due to extraordinarily high mobility of vehicles in a vehicular network, frequent handover requests will be a norm, which initiates the demand for an effective and fast authentication scheme that can maintain the service continuity in presence of the frequent handover events. However, previously reported authentication schemes, although with minimized handover latency and packet loss rate, may disclose the location information of the mobile user to the third party, which will seriously violate the location privacy of the user. In this paper, we propose a location privacy preserving authentication scheme based on blind signature in the elliptic curve domain. The scheme cannot only provide fast authentication, but also guarantee the security and location anonymity to the public. To analyze the proposed scheme, a theoretical traceability analysis is conducted, which shows that the probability of tracing an vehicle's route is negligibly small. We will also examine the authentication speed of the scheme, and show that the scheme can satisfy seamless handover for fast moving vehicles.

As one of the backup measures of intrusion prevention techniques, intrusion detection system (IDS) plays a paramount role in the second defense line of computer networks. Due to the special infrastructure and communication mode, intrusion detection in wireless mesh networks (WMNs) is especially challenging and requires particular design considerations. In this paper, we propose a novel anomaly detection scheme, called RADAR, to detect anomalous mesh nodes in WMNs. Firstly, we introduce a general concept of reputation to characterize and quantify the mesh node's behavior/status in terms of fine-grained performance metrics. This enables us to construct a robust baseline for leveraging and measuring the derivation between normal and anomalous behavior of each mesh node. Secondly, based on reputation management, we develop a cooperative anomaly detection scheme by fully exploring the spatio-temporal properties of mesh nodes' behavior. Our current scheme is specified and implemented with a reactive routing protocol, aiming at detecting malicious mesh nodes which intentionally violate normal routing mechanisms. The simulation results show that our scheme performs well in terms of detection accuracy, false positive rate, computational overhead, and scalability.

Abstract It has been witnessed that the car manufacturers and telecommunication industries gear up to equip each car with the latest wireless communication technologies, most notably the short‐range communication systems and/or networks (vehicle‐vehicle or vehicle‐roadside) based on IEEE 802.11p. The short‐range vehicular communication technologies are expected to evolve into VANETs (Vehicular Ad‐hoc NETworks), which will be supporting various safety and commercial applications that significantly improve the driving experiences and safety. The merits of launching VANETs are obvious; however, it comes with a set of challenges, especially in the aspects of security and privacy preservation, in which any malicious behavior of users, such as a modification and replay attack with respect to the disseminated messages, could be fatal to the other users. In addition, the issues on VANET security become more challenging due to the unique features of such network scenarios, including high‐speed mobility and large amount of network entities (i.e., the vehicles). Furthermore, conditional privacy preservation must be achieved in a sense that the user related privacy information, including the driver's name, the license plate, speed, position, and traveling routes along with their relationships, has to be protected; while the authorities should be able to reveal the identities of message senders in the event of a traffic dispute, such as a crime/car accident scene investigation. This special issue aims to address the aforementioned issues by collecting six technical papers through a peer‐review process, hoping to contribute to the state‐of‐the‐art progress of secure and privacy preserving vehicular communications. Copyright © 2008 John Wiley & Sons, Ltd.

Abstract Vehicular ad hoc networks (VANETs) are gaining growing interest from both industry and academia. The primitive objective of VANETs is to enhance the road safety for public transportation systems through dedicated short range communications (DSRC) protocol. In addition to the powerful radios and abundant spectrums, DSRC also paves the way for VANETs to support numerous emerging Internet‐related applications. In this paper, we introduce a promising commercial application which allows each vehicle to purchase file/data through a roadside unit (RSU). Due to the high mobility of vehicles, the contact period between an RSU and a vehicle could be insufficient to download the complete file. Thus, in the proposed file purchasing systems, once a vehicle in the process of downloading a file leaves the transmission range of the RSU, its neighboring vehicles with a piece of the file can cooperatively help to complete the file transfer via vehicle‐to‐vehicle (V2V) communications. Such a commercial file purchasing system can obviously initiate a new application scenario; however, it cannot be put into practice unless the security issues, such as the user privacy, incentives for inter‐vehicle cooperation, and the copyright protection for∼the file content, are well addressed. In order to deal with these security issues, we develop a secure framework for the file purchasing system in VANETs. Performance evaluation will be conducted to verify the proposed scheme. Copyright © 2008 John Wiley & Sons, Ltd.

In this paper, a novel approximate link-state dissemination framework, called TROP, is proposed for shared backup path protection (SBPP) in multiprotocol label switching (MPLS) networks. While performing dynamic explicit survivable routing in a distributed environment, link-state dissemination may cause a nontrivial signaling overhead in the process of exploring spare resource sharing among individual backup label switched paths (LSPs). Several previously reported studies have tackled this problem by initiating a compromise between the amount of dissemination and the achievable extent of resource sharing. The paper first summarizes the previously reported schemes into a compact and general link-state dissemination framework by way of singular value decomposition (SVD). To improve the accuracy of the matrix reconstruction and to eliminate the overestimation of the sharable spare capacity along each link, a novel SVD approach based on the min-plus algebra (also called tropical semirings) is introduced. Simulation results show that the proposed schemes can achieve a lower blocking probability than that by all the other counterpart schemes while taking the same complexity of link-state dissemination. This great advantage is gained at the expense of a longer computation time for solving a linear program (LP) in each dissemination cycle at the core nodes. We also consider the stale link-state phenomena that may cause imprecision in the routing information at the ingress nodes due to the delay in the periodic/event-driven link-state update message advertisement.

Spare capacity allocation serves as one of the most critical tasks in dynamic GMPLS networks to meet the stringent network availability constraint stipulated in the SLA of each connection. In this paper, an availability-aware spare capacity reconfiguration scheme based on shared backup path protection (SBPP) is proposed, aiming to guarantee the E2E availability of each LSP. We first provide an E2E availability model for a SBPP connection that is composed of a working and a SRG-disjoint shared backup LSP pair in the presence of all possible single, and dual simultaneous failures. Partial restoration is identified to further improve the capacity efficiency, and achieve finer service differentiation. For this purpose, restoration attempt is defined as a parameter for each connection that can be manipulated at the source node when the spare capacity of each link is scheduled. Based on the developed model, a linear program (LP) is formulated to perform inter-arrival spare capacity reconfiguration along each pre-determined shared backup LSP to meet the availability constraint of each connection. Simulation is conducted to verify the derived formulation, and to demonstrate the benefits gained in terms of the spare capacity saving ratio, where the conventional SBPP scheme that achieves 100% restorability for any single failure is taken as a benchmark. We will show that the simulation results validate the proposed E2E availability model, where a significant reduction on the required redundancy can be achieved in the effort of meeting a specific availability constraint for each SBPP connection.

Shared segment protection (SSP), compared with shared path protection (SPP), and shared link protection (SLP), provides an optimal protection configuration due to the ability of maximizing spare capacity sharing, and reducing the restoration time in cases of a single link failure. This paper provides a thorough study on SSP under the GMPLS-based recovery framework, where an effective survivable routing algorithm for SSP is proposed. The tradeoff between the price (i.e., cost representing the amount of resources, and the blocking probability), and the restoration time is extensively studied by simulations on three networks with highly dynamic traffic. We demonstrate that the proposed survivable routing algorithm can be a powerful solution for meeting stringent delay upper bounds for achieving high restorability of transport services. This can significantly improve the network reliability, and enable more advanced, mission critical services in the networks. The comparison among the three protection types further verifies that the proposed scheme can yield significant advantages over shared path protection, and shared link protection.

User authentication is essential in service-oriented communication networks to identify and reject any unauthorized network access. The state-of-the-art practice in securing wireless networks is based on the authentication, authorization and accounting (AAA) framework where one or multiple identical and duplicated AAA servers are adopted to authenticate mobile users (MUs), handle authorization requests, and collect accounting data. However, the conventional AAA framework cannot tolerate a server compromise event due to misuse, misconfiguration, and malicious access, etc., which may cause serious damages and resource abuses to the network operation. In this paper, we propose a novel design paradigm toward a compromise-resilient authentication architecture in service-oriented wireless mesh networks (WMNs) based on the (t, n) threshold signature technique, termed Threshold User Authentication (TUA) scheme. With the TUA scheme, only t or more out of n AAA servers in the WMN can cooperatively grant the network access to a MU, while any t-1 or less cannot. Detailed protocol-aspect design and implementations are presented. Extensive analysis on efficiency and reliability of authentication functionality is conducted to gain a deeper understanding on the parameter settings and optimization, which demonstrates the effectiveness of the TUA scheme. We conclude that the proposed authentication scheme can contribute to the WMN network design in metropolitan areas where numerous mesh points (MPs) coexist and are managed under a single control plane with multiple distributed AAA servers.

In this paper, we propose a Timed Efficient and Secure Vehicular Communication (TSVC) scheme with privacy preservation, which aims at minimizing the packet overhead in terms of signature overhead and signature verification latency without compromising the security and privacy requirements. Compared with currently existing public key based packet authentication schemes for security and privacy, the communication and computation overhead of TSVC can be significantly reduced due to the short message authentication code (MAC) tag attached in each packet for the packet authentication, by which only a fast hash operation is required to verify each packet. Simulation results demonstrate that TSVC maintains acceptable packet latency with much less packet overhead, while significantly reducing the packet loss ratio compared with that of the existing public key infrastructure (PKI) based schemes, especially when the road traffic is heavy.

The future metropolitan-area wireless mesh networks (WMNs) are expected to contain compromise-prone Mesh Access Points (MAPs) with a high frequency of inter-domain roaming/handoff events. This paper introduces a novel secure localized authentication and billing (SLAB) scheme, which aims to address both security guarantee and performance in terms of system compromise resilience capability, inter-domain handoff authentication latency, and workload of the roaming broker (RB). With extensive analysis and simulation, we demonstrate that the proposed scheme can be a practical solution for achieving secure roaming and billing in metropolitan-area WMNs.

In this paper, we propose an application-driven MAC-layer buffer management framework based on a novel active dropping (AD) mechanism for real-time video streaming in IEEE 802.16 Point-to-Multi-Point (PMP) networks. The basic idea of the proposed approach is that the MAC-layer protocol data units (MPDUs) of a video stream could be actively dropped at the Base Station (BS) if the corresponding frame is not with a sufficient confidence to be successfully delivered to the recipient within its application-layer delay bound. In contrast to the conventional cross-layer techniques that manipulate transmission and/or retransmission priorities for sending MPDUs of a single stream, the proposed AD mechanism can be more effectively bound the delay of each video frame and release precious transmission resources for the subsequent frames or the frames of the other competing streams. This is considered as an intelligent approach for minimizing delay propagation due to bad channels or any other possible reason. A comprehensive analytical model is formulated on deriving how confident a frame can be effectively delivered within its application-layer delay bound by jointly considering the effect of playback buffering. Extensive simulation is performed to demonstrate the effectiveness of the proposed scheme. We expect that the proposed application-driven MAC-layer buffer management can incorporate with the emerging cross-layer design paradigm for real-time video streaming in TDMA-based wireless broadband access networks such as IEEE 802.16.

As a promising broadband wireless access standard, IEEE 802.16 specified some advance physical layer techniques and media access control layer protocols, which pose many fundamental differences in terms of automatic repeat request (ARQ) mechanism, scheduling scheme, and resource allocation, compared with those done in many previous works. In this paper, we analyze the performance of ARQ in IEEE 802.16 networks by jointly considering the opportunistic scheduling scheme, where the delivery delay and goodput are investigated as two performance metrics. Simulation results are given to verify the proposed analysis model.

In this paper, we propose a new TESLA (timed efficient stream loss-tolerant authentication) based secure vehicular communication (TSVC) protocol with privacy preserving, aiming to achieve less communication overhead without compromising the security and privacy requirements. With TSVC, the communication overhead can be significantly reduced due to the message authentication code (MAC) tag attached in each packet and only a fast hash operation is required to verify each packet. Simulation results show that TSVC maintains acceptable message latency with much smaller packet size while significantly reducing the message loss ratio compared with that by the existing PKI-based protocols especially when the traffic is denser.

This paper introduces a novel congestion control scheme for TCP over OBS networks, called Statistical Additive Increase Multiplicative Decrease (SAIMD), which aims to improve the throughput performance for high-bandwidth TCP flows in OBS networks. We show through analytic model and extensive simulations that the proposed scheme can effectively solve the false congestion detection problem and significantly outperform the conventional TCP counterparts without losing fairness.

The future metropolitan-area wireless mesh networks (WMNs) are expected to have compromise-prone mesh access points (MAPs) with high frequency of inter-domain roaming/handoff events. To achieve security without losing efficiency, this paper introduces a novel secure localized authentication and billing (SLAB) scheme. Our scheme aims to address both security guarantee and performance in terms of system compromise resilience capability, inter-domain handoff authentication latency, and workload of the roaming broker (RB). We demonstrate that the proposed scheme can be a practical solution for achieving secure roaming and billing in metropolitan-area WMNs.

Shared-backup path protection (SBPP) has been widely studied in the GMPLS networks due to its efficient spare capacity sharing and flexibility in service provisioning. This paper presents a model for evaluating the end-to-end (E2E) availability of an SBPP connection by assuming that no more than two simultaneous failures could possibly occur in the network. To minimize the redundancy while meeting the E2E availability requirement, a framework of partial restoration from any unexpected failure is created. Based on the proposed availability model, a novel Linear Program (LP) formulation is introduced, which aims to perform the spare capacity allocation for SBPP connections. A new availability-aware spare capacity reprovisioning (SCR) architecture is then introduced for dynamic provisioning of SBPP connections. Extensive simulations are conducted to validate the proposed availability model and demonstrate the effectiveness of the SCR architecture.

In this paper, we present a novel anonymous secure routing protocol for mobile ad hoc networks (MANETs). The proposed protocol not only provides anonymity from all the intermediate nodes, but also integrates the authenticated key exchange mechanisms into the routing algorithm design. Furthermore, a new attack on anonymous services, called snare attack, is introduced, where a compromised node lures a very important node (VIN) into communicating with him and traces back to the VIN by following the route path. An adversary can then snare the VIN and launch decapitation strike on the VIN. Finally, we present a novel DECOY mechanism as a countermeasure to enhance anonymity of VINs and defeat snare attack.

In the paper, we propose an efficient two-factor localized authentication scheme suitable for WLAN roaming. The proposed authentication scheme can greatly improve the security compared with the previously reported counterparts, where two independent factors, such as "what you know" and "what you have", are utilized in the authentication process for a mobile user (MO). Some important issues specific to the wireless environment are considered in the design of the scheme, such as limited computation power, memory space, and battery capacity of mobile stations (MSs), and ping-pong movement problem when roaming across WLANs. The detailed implementation of the proposed scheme is presented, where some of the key performance measures and security are analyzed. Numerical results demonstrate that the proposed scheme can significantly outperform the legacy authentication schemes in terms of signaling overhead, power consumption, and authentication latency without losing the capability of preserving the system security.

Vehicular communication networking is a promising approach of facilitating road safety, traffic management, and infotainment dissemination for drivers and passengers. However, it is subject to various malicious abuses and security attacks which hinder it from practical implementation. In this paper, we propose a novel security protocol based on group signature and identity-based signature scheme to meet the unique requirements of vehicular communication networks. The proposed protocol not only guarantees security and anonymity, but also provides easy traceability property when the identity of the sender of a message has to be revealed by the authority. To further enable Internet access, the network architecture incorporating with the proposed security protocol is introduced. Simulation is conducted to analyze the system performance which proves the feasibility of the proposed scheme.

Transport control protocol (TCP) has served as a reliable, self-regulated, and congestion tolerant transport protocol for many Internet applications. Relatively, limited knowledge has been gained in terms of the impacts encountered in TCP when optical burst switching (OBS) is adopted in the network backbone. A novel scheme, called TCP with Explicit Notification Generalized Additive Increase Multiplicative Decrease (TCP-ENG), is introduced, which is considered as the first study that integrates the explicit notification platform with the GAIMD approach. The proposed scheme aims to solve the false congestion detection problem in the IP over OBS networks. An analytical model is developed for the proposed scheme and is verified through extensive simulation.

To make the WiMAX Point-to-Multi-Point (PMP) systems more competitive and applicable to the future metropolitan area networking scenarios, deploying relay stations (RSs) as defined in IEEE 802.16j has been considered a promising solution that can replace the 802.16e mesh mode for coverage extension and throughput enhancement. In this paper, we are committed to tackle the task of RS placement and relay time allocation in IEEE 802.16j Mobile Multi-hop Relay (MMR) networks, in order to meet the uneven distributed traffic demand of each subscriber station (SS) as well as the thirst for system capacity. By incorporating advanced cooperative relaying technology such as Decode-Forward (D-F) or Compress-Forward (C-F), the task of RS placement and relay time allocation is formulated into an optimization problem, aiming at finding the optimal location of a single RS and the resource allocation for all the SSs. Numerical analysis is conducted through a number of case studies to demonstrate the performance gain by using the proposed approach for relay placement and relay time allocation.

The paper proposes a distributed connection admission control and resource allocation scheme for IEEE 802.16 networks. Rather than investigating the short-term variation of wireless channel conditions for different sub-carriers, the study focuses on relative long-term capacity planning at the base station on a time-of-a-day basis for each subscriber station and mobile user. With the proposed scheme, each subscriber station performs distributed admission control to decide whether or not to accept connection requests originated by its end users based on the granted capacity aiming at optimizing the overall revenue. A cross-layer design and optimization cooperated with a suite of distributed signaling are addressed and implemented such that the network capacity can be assigned efficiently. Simulation results are given to demonstrate the efficiency of the proposed scheme.

In this paper, a novel compromise-resilient localized authentication scheme is proposed for metropolitan-area wireless mesh networks (WMNs), which aims to mitigate the impact caused by a compromise event on one or multiple mesh access points (MAPs) before they are identified and removed from the network. As a proactive mechanism based on a "best practice" strategy - Defence in Depth, the proposed scheme can protect critical WMN functionalities, such as user authentication and handoff support, even in presence of compromised MAPs.

Nowadays, wireless personal devices, such as cell phones and Personal Data Assistants (PDAs), have gradually taken an important part of our daily lives. With two-factor authentication, the wireless personal devices can be further promoted to more security demanding and mission-critical applications, such as e-commerce, home surveillance, and medical monitoring, etc. Facility access is one of applications that have demonstrated a tremendous market potential for replacing the conventional physical key approach. In this paper, we present a novel keyless facility access control system by using wireless personal devices, where the devices serve as a second authentication factor to assure security. The proposed system is not only cost-efficient, but also capable of mitigating security threats existing in the traditional key control system. Furthermore, the proposed authentication protocol is featured in two different authentication processes for the first time and subsequent accesses by using a one-time authentication mechanism based on one-way hash chain while considering the resource constraints of the wireless personal devices and E-lock. Finally, a role-based access control (RBAC) system is adopted to reduce the complexity of key maintenance.

An increasing interest in IEEE 802.16 networks has been witnessed due to the demonstrated unique features in offering quality of service (QoS) satisfaction and service differentiation. Efficient scheduling plays a key role in fulfilling these operational requirements and unique characteristics. Traditional scheduling schemes such as opportunistic scheduling and proportional fairness scheduling focuses on throughput maximization and fairness instead of service differentiation and QoS guarantee. In this paper, a novel scheduling scheme is proposed to provide the QoS satisfaction and service differentiation in terms of delay. The proposed scheme manipulates a new design parameter - the time window of throughput evaluation, to differentiate the delay performance of each queue. By embedding wireless channel condition of each queue into the preference metric, opportunistic scheduling can be properly realized by trading the delay performance. An analytical model is developed on inter-service time, queue length, and waiting time, and is verified through extensive simulation.

User authentication is essential in service-oriented communication networks to identify and reject any unauthorized network access. The state-of-the-art practice in securing wireless networks is based on the technique of authentication, authorization and accounting (AAA) framework where an AAA server is adopted to authenticate mobile users (MUs), handle authorization requests, and collect accounting data. However, the traditional AAA framework is by way of a single authentication server, and cannot tolerate AAA server failure due to various malicious attacks such as denial-of-service (DoS) attack, or any other failure event such that the authentication server is compromised due to misuse, misconfiguration and malicious access, etc. Thus, a more resilient approach is to adopt multiple authentication servers, where any authentication request is handled by more than one authentication servers in order to resist any compromise event of an authentication server. To meet this design objective, we introduce a novel compromise-resilient authentication system based on (t, n) threshold signature technique. With the proposed system, only t or more out of n authentication servers can cooperatively allow a MU to have network access, and any t-1 or less cannot. Case study of reliability analysis is conducted to demonstrate the effectiveness of the system. The proposed authentication system is expected to particularly contribute to wireless mesh networking (WMN) in metropolitan areas where thousands of nodes may coexist and are managed under a single control plane such that duplicated AAA servers are necessary.

We propose a novel inter-WISP roaming architecture based on trusted third party (TTP) and partially blind signature technique in wireless metropolitan area networks (WMAN). The proposed architecture aims to not only greatly improve user privacy and identity anonymity even in the presence of cooperation between the wireless Internet service provider (WISPs) and the TTP, but also dramatically reduce the required size of central database devised to minimize any possible service abuse. In addition, an efficient billing scheme among mobile users (MUs), WISPs and TTP, is introduced to address billing issues associated with roaming. Moreover, a localized inter-WISP authentication scheme is also proposed to support seamless handoff. Detailed analysis on a number of important performance metrics, such as computation time, handoff latency and power consumption, is conducted to verify the performance of the proposed schemes.

Active restoration (AR) is a novel lightpath restoration scheme proposed recently to guarantee a certain degree of survivability in wavelength-division multiplexing (WDM) optical networks with a reasonable trade-off between capacity requirement and restoration time. In this paper, we conduct a comprehensive performance analysis for AR-based optical networks. In particular, we propose a novel analytical framework for modeling the restoration probability of a connection (the probability that the connection can be successfully restored in case of a failure) when the possible correlation among its multiple backup routes is incorporated. Although theoretically, we need to consider all the possible correlations between as many as Q) pairs of backup routes to analyze the restoration probability in a network with N nodes, and this high computation complexity may obscure the practicality of an approach, considering all the possible correlations among backup routes, our analysis in this paper indicates that by considering at most the possible correlations among any three successive backup routes of a connection, we can achieve a very good approximation to the simulated restoration probability of the connection, as verified by extensive simulation results upon two typical network topologies under various workloads. We find that the proposed framework can deeply investigate into the inherent relationship among restoration probability, wavelength channel utilization ratio, number of wavelengths per fiber, routes hop length, and wavelength conversion capability. As a result, the framework significantly contributes to the related areas by providing network designers with a quantitative tool to evaluate the restoration probability and, thus, the survivability of AR-based optical networks.

This paper introduces a new dynamic availability-aware survivable routing scheme under the framework of generalized multi-protocol label switching (GMPLS)-based recovery, which aims to achieve the best generality for the network operation in meeting the end-to-end (E2E) availability requirement of each connection. The paper first defines the partial restorability, justifies the feasibility of equipping a connection with partial restorability under the GMPLS control plane, and highlights the approach of evaluating the E2E availability for a pair of working and partially restorative SRG (shared risk group)-disjoint shared backup label switched paths (LSPs). A compact matrix expression is developed for modeling the minimum spare capacity along each link and the cost function for solving both of the paths. Based on the developed cost function, a novel integer linear program (ILP) is formulated to dynamically determine the working and backup LSPs of the corresponding connection request with the least amount of total capacity while the E2E availability requirement of the connection is met. We demonstrate that the model is general to the traffic uniformity, connection indivisibility, and working bandwidth restorability compared with the previous studies. Simulation is conducted to verify the proposed ILP model by making a comparison with a number of legacy schemes that achieve 100% restorability in facing a specific number of simultaneous failures, such as shared path protection (SPP), 1+1 protection, and dual-failure protection. In the case study, we have seen merits in the proposed algorithm by significantly reducing the required redundancy in the effort of achieving the given availability constraint for each connection request.

The integration of the third generation (3G) wireless wide-area networks (WWAN) and the IEEE 802.11 wireless local-area networks (WLAN) has drawn much attention from both industry and academia. To achieve an effective and efficient integration between the two networks with very different characteristics, nonetheless, is still an open issue. One of the challenges is to provide an integrated strategy for achieving a seamless vertical handoff of mobile users roaming between the two network domains where the delay, delay jitter, and packet loss probability can be well controlled. This paper is committed to study a two-step vertical handoff mechanism based on linear regression which is further modeled through an analytical approach. The proposed vertical handoff scheme is characterized by its adaptability to different quality of service (QoS) requirements by manipulating a threshold on the expected handoff instant. A new approach of mobility analysis is introduced to facilitate modeling of vertical handoff delay by taking advantage of Markov chain techniques. We have seen merits gained in our scheme in achieving a good trade-off between the average handoff delay and the multi-tunnel time by manipulating a threshold value, where both analytical and simulation results prove the effectiveness.

It has been shown that burst retranmsission scheme and burst deflection scheme can effectively reduce the burst loss probability, thereby improving the performance of loss-based TCP implementations. However, both schemes introduce additional delays for bursts that are retransmitted or deflected. The additional delays could result in delay-based TCP falsely detecting network congestion, which may negatively impact the performance of delay-based TCP implementations, such as TCP Vegas. In this paper we investigate the delay-based TCP Vegas behavior over OBS networks. Furthermore, we analyze the throughput of TCP Vegas over a barebone OBS network and an OBS network with burst retransmission.

The past studies for survivable routing suffers from the scalability problem when the number of nodes or connection requests grows in the network. In this proposal, a novel path based shared protection framework namely Inter-Group Shared protection (I-GSP) is developed such that the traffic matrix can be divided into multiple protection groups (PGs) based on specific grouping policy. This novel scheme not only overcomes the scalability problem but also provides an upper bound on the affected working paths in case of link failure in the network. Experiment results show that I-GSP based integer linear programming model solves the networks in a reasonable amount of time for which a regular integer linear programming formulation becomes computationally intractable. For most of the cases the performance gap between the optimal solution and the proposed I-GSP ranges between (2-16)%. The proposed optimization model yields a scalable and near-optimal solution for the capacity planning in the survivable optical networks.

There is an increasingly growing interest in the IEEE 802.16 owing to its unique and useful characteristics in offering broadband wireless access. One of the key strengths is its support for different quality of service (QoS) classes which positions it to support high-quality voice, video, and data services. Connection admission control (CAC) plays an important role in fulfilling service differentiation and QoS satisfaction defined in IEEE 802.16 Std.. A traditional CAC scheme, known as complete sharing, is expected unable to explore the maximum advantage in using the IEEE 802.16 networks since it does not take the priority of different service classes into account. In this paper, a reservation based CAC scheme is introduced. By considering the service differentiation defined in the IEEE 802.16 networks, the proposed scheme can provide significantly lower connection block probabilities for higher priority services, which leads to better revenue. We analyze the proposed scheme in terms of some importance performance metrics, such as connection block probability for different service classes, bandwidth utilization, and the revenue generated at the BS. The analysis and simulation results are given to illustrate the efficiency of the proposed scheme and the accuracy of the analysis.

Due to the nature of wireless ad hoc networks such as dynamic infrastructure and non-centralized management, the routing process has a huge exposure to malicious hacking and intrusions. This fact results in a likelihood of node compromise, leading to a disruption of the legitimate network functions/services. Most reported studies in coping with the problem have focused on the effort of protection on route discovery and data transmission against various attacks. In this paper, we solve the problem from a different perspective by targeting the node compromise revocation, i.e., isolating and breaking off the misbehaving nodes. To mitigate the security breaches from internal compromised nodes and eventually eliminate compromised nodes from the wireless ad hoc networks, we propose an energy efficient malicious node removal mechanism. Further, a new attack on routing service called entrap attack is introduced, where an innocent node is incriminated as a malicious node.

Additive Increase Multiplicative Decrease (AIMD) window adjustment mechanism has been embedded in TCP in order to regulate the transmission rate in modern communication networks. In recent years, the AIMD (1,0.5) traffic regulation mechanism along with possibly additional enhancements, such as false timeout detection and explicit notification, has been considered in the carriers with Optical Burst Switching (OBS) as the underlying transmission technology. This paper introduces a novel rate control mechanism based on Generalized AIMD (α,β), called Burst AIMD (BAIMD), for tuning the rate control parameters (α, β) at each sender. BAIMD is designed to improve throughput while maintaining friendliness with co-existing AIMD (1,0.5) flows, and is characterized in the following two folds: (1) no burst window is required in the TCP sender's level; (2) no explicit notifications are required. The above characteristics make the proposed scheme distinguished from all the past reported counterparts by minimizing the signalling efforts and control complexity. The simulation result shows that BAIMD can solidly outperform the past reported AIMD-based (1,0.5) rate control schemes under a wide range of traffic loads. We also suggest that BAIMD rate control mechanism may serve as a better choice than AIMD (1,0.5) in the bufferless OBS networks due to its dynamic and flexible (α,β) parameter pair.

Due to the bufferless nature of optical burst switched network, contentions occur even at low traffic loads, leading to burst losses. Contention resolution schemes, such as burst retransmission and deflection, can reduce burst losses, especially at low traffic loads. However, both schemes result in additional packet delay for the packets in bursts that are retransmitted or deflected. The additional packet delay affects the performance of delay-based TCP implementations that rely on packet delay to estimate available bandwidth in networks and to detect network congestion state. In this paper, we discuss the issues of TCP Vegas over OBS networks and propose a threshold-based TCP Vegas version that is suitable for the characteristics of OBS networks. The threshold-based TCP Vegas are able to distinguish whether the increases in packet delay are due to network congestion, or due to burst contentions at low traffic loads. Our simulation results show that the threshold-based TCP Vegas has higher throughput for a TCP connection compared to TCP Vegas and the loss-based TCP implementations, such as TCP Sack.

In this paper, the performance of unsolicited grant service (UGS) connections defined in IEEE 802.16 Std. is investigated. A simple admission control strategy based on the periodic exhaustive service principle is first introduced to provide Quality of Service (QoS) satisfaction for such connections. The task of system parameter selection and performance evaluation for the UGS flows is tackled. In particular, the maximum retransmission limit that works along with the embedded Automatic Repeat reQuest (ARQ) mechanism is emphasized. A novel transferred model is formulated such that the lossy characteristic of the wireless channels in real networks can be completely engineered by way of the traffic arrival pattern and the size of the messages in the proposed model. Significant merits and efficiency have been identified in the proposed model through extensive simulation, where a complete match between the analytical and simulation results is observed.

This paper tackles the resource allocation problem in wavelength division multiplexing (WDM) networks supporting virtual private networks (O-VPN), in which working, and spare capacity are allocated in the networks for satisfying a series of traffic matrices corresponding to a group of O-VPN. Based on the (M:N)nprotection architecture where multiple protection groups (PG) are supported in a single network domain, we propose two novel integer linear programming (ILP) models, namely ILP-I, and ILP-II, aiming to initiate a graceful compromise between the capacity efficiency, and computation complexity without losing the ability of addressing the quality of service (QoS) requirements in each O-VPN. ILP-I considers all the connection requests of each O-VPN in a single formulation, which may suffer from long computation time when the number of connection requests in an O-VPN is large. To trade capacity efficiency with computation complexity, ILP-II is developed such that each O-VPN can be further divided into multiple small PG based on specific grouping policies that satisfy multiple QoS requirements. With ILP-II, it is expected that all the working, and spare capacity of the O-VPN can be allocated with a polynomial time complexity provided that the size of each PG is well constrained. Experimental results show that, in terms of capacity efficiency, a significant improvement can be achieved by ILP-I compared to that by ILP-II at the expense of much more computation time. Although ILP-II is outperformed by ILP-I, it can handle the situation with an arbitrary size of O-VPN. We conclude that the proposed ILP-II model yields a scalable solution for the capacity planning in the survivable optical networks supporting O-VPN based on the (M:N)n protection architecture

It is observed that the singular value decomposition (SVD) transformation based on min-plus algebra (or called tropical semi-rings) leads to a very good characteristic in zero underestimating the reconstructed matrix. This paper introduces a novel distributed control framework for shared protection in optical networks with reduced routing information based on the tropical semi-rings technique, called sharing with reduced information with tropical semi-rings (SRI-TROP). The design of the proposed framework aims to initiate a compromise between the amount of link-state dissemination and the performance impairment due to the incompleteness of routing information, such that the precision in the link-state matrix reconstruction can efficiently map to the reduction in blocking probability. Based on the framework, a series of novel schemes are proposed, which are verified and compared with the reported counterparts in a simulation. The simulation results show that the performance in terms of the precision in the reconstructed link-state and the resultant blocking probability can be significantly improved.

Because of their pervasiveness and autonomy in operation, mesh-based wireless sensor networks (WSNs) are an ideal candidate in offering sustained monitoring functions at reasonable cost over a wide area. However, devising an energy-efficient, cost-effective and reliable communication strategy for WSNs requires tight collaboration of all of the sublayers, which introduces new technical challenges in the areas of data, network and power management. This paper proposes a cross-layer sleep-scheduling-based organizational approach, called SS-Trees, that aims to harmonize the various engineering issues and provides a method of increasing monitoring coverage and operational lifetime of mesh-based WSNs engaged in wide-area surveillance applications. An integer linear programming (TLP) formulation based on Dijkstra's algorithm and an iterative algorithmic approach are also suggested to determine the feasible SS-Tree structures for achieving such design goals.

An analytical model for studying the performance of the delayed acknowledgement (Dly-ACK) mechanism in IEEE 802.15.3 over a fading channel is developed. A three-state Markov channel model is used to approximate both correlated and uncorrelated error processes. Explicit mathematical expressions for the goodput and efficiency of Dly-ACK are derived. It is found that the Dly-ACK mechanism yields higher goodput in a burst error environment than in a random error environment. The goodput tends to increase as the size of the burst increases; however, the amount of increase depends on the underlying delay. Simulations results are given to validate the analytical results.

Shared segment protection (SSP), compared to shared path protection (SPP) or shared link protection (SLP), provides an optimal protection configuration, since SSP can increase the number of connections sharing the same protection segments and can reduce the restoration time in case of single link failure. This paper provides a thorough study on SSP under the GMPLS-based recovery framework, where an effective survivable routing algorithm for SSP is proposed, called shared segment protection (SSP) algorithm. The main advantage of the SSP algorithm is to reduce the high computation complexity in solving the ILP formulation first introduced in P-H. Ho et al., (2004). With an efficient iterative approach the design space is significantly reduced by excluding all the links that result intolerably long routes. The tradeoff between the price (i.e., cost representing the amount of resources, and the blocking probability) and the restoration time is extensively studied by simulations on three networks with highly dynamic traffic. It is demonstrated that the SSP algorithm can be a powerful solution in the GMPLS-based recovery with a stringent delay upper bound for achieving high availability and restorability of the transport services. The comparison among the three protection types further verifies that SSP can yield significant advantages over SPP and SLP.

This paper proposes a novel framework of bandwidth provisioning based on optical burst switching (OBS), called optical flooding cluster switching (OFCS), which is developed to achieve a better resource allocation and efficiency by fully exploiting the potential characteristics of data-dominated traffic with a high self-similarity and burstiness in the modern communication networks. The concept of flooding clusters is first defined, which serves as basis of the study. The design objectives and the working principles of the OFCS scheme are introduced, where the corresponding advantages against the pure OBS, pure OCS (optical circuit switching), and the hybrid OBS/OCS architectures, are discussed. A comprehensive analytical model on the burst drop rate is formulated for the proposed scheme. To verify the analytical model and compare with the other counterparts, extensive simulation efforts have been addressed. The results reveal that OFCS can overcome the non-predictiveness of traffic self-similarity, where the flooding clusters are set up for a partial prediction of the burst arrival. We conclude that the flooding effect of data-dominated traffic can be successfully smoothed out by the proposed OFCS scheme

Horizontally expanded and vertically stacked optical banyan (HVOB) is a general architecture for constructing banyan-based optical switches. Blocking analysis is an effective approach to studying network performance and finding a graceful compromise among hardware cost, network depth and blocking probability; however, little has been done on analyzing the blocking behavior of general HVOB networks. In this paper, we study the overall blocking behavior of a HVOB network, where an upper bound on the blocking probability of the network is developed. The upper bound depicts accurately the overall performance behavior of a HVOB network as verified by extensive simulation results and it agrees with the strictly nonblocking condition of the network. The derived upper bound is significant because it reveals the inherent relationship among blocking probability, network depth, and network hardware cost, by which a desirable tradeoff can be made among them. In particular, our bound provides network developers an effective tool to estimate the maximum blocking probability of a HVOB network in which different routing algorithms can be applied with a guaranteed performance in terms of blocking probability, hardware cost and network depth. An important conclusion drawn from our work is that the hardware cost of HVOB networks can be reduced dramatically without introducing either significantly high blocking probability or a large network depth.

The scheme of vertical stacking has caught much interest in the design of ultra high-speed communication switches for the past a few years. In particular, the scheme can greatly facilitate the effort of constructing all-optical photonic switches in the event that a banyan network structure is adopted. A vertically stacked photonic banyan (VSPB) network can preserve the good properties of the banyan network structures, such as the small depth and absolute loss uniformity; on the other hand, it introduces a significant increase in the hardware cost. Extensive research efforts have been addressed in determining the minimum number of stacked copies (planes) required for a nonblocking VSPB network. However, very few of them focused on the performance of the VSPB networks in terms of blocking probability. Therefore, in this paper, we study the blocking behavior of the VSPB networks and propose a corresponding analytical model under the random routing strategy. The proposed analytical model is designed to fully explore the property of symmetry in banyan network structures, and can calculate the blocking probability of a VSPB network stage by stage in a recursive manner such that the combinatorial explosion problem is avoided. To verify the proposed model, we conduct extensive simulations, in which the results indicate that our model can accurately describe the blocking behavior of VSPB networks under the random routing strategy and it agrees with the conditions of strictly nonblocking VSPB networks. We find that the proposed analytical model can deeply investigate into the inherent relationship between blocking probability and network hardware cost in terms of the number of planes; as a result, a quantitative guidance for initiating a graceful compromise between blocking probability and hardware cost can be developed based on the analytical model. Our analysis results also show that the hardware cost of a VSPB network can be dramatically reduced by simply allowing a negligible nonzero blocking probability in most of the practical cases. This fact will solidly contribute to the network switch architecture design and enable more practical applications of VSPB networks.

In this paper, we study the system reliability optimization of distributed access networks subject to a constraint on the total cost. We first formulate the cost-constrained system reliability optimization problem as a searching process in a combinatorial tree, which enumerates all the possible solutions to the problem. Because the calculation of each possible solution for the reliability problem is extremely time-consuming, a novel algorithm, the Shrinking & Searching Algorithm (SSA), is proposed to speed up the searching process. SSA jointly considers the upper bound of the system reliability for each branch in the combinatorial tree, and the cost constraint on the possible solutions. It avoids most of the redundant calculations in the searching process by gradually shrinking the difference between lower & upper bounds of the length of a path in the corresponding combinatorial tree, which represents a feasible solution. Case study & simulation results are presented to demonstrate the performance of the SSA.

As text messaging services are becoming increasingly popular in today's global wireless market, fundamental design issues still linger with respect to text entry methods on mobile devices. Current schemes are often plagued with problems, such as poor typing efficiency, stringent physical size limitations, and unwarranted cognitive processing burden, on mobile users. The proposed text entry scheme for mobile communications, called SIMKEYS, balances input efficiency, ergonomics, usability and cost via a compact 12-button keypad. By pursuing a deterministic and linguistically optimized approach in character disambiguation, SIMKEYS achieves a significant improvement in typing performance over existing methods as verified by extensive simulation results while consuming negligible amounts of system resources and incurring minimal development costs. Because of its simplicity and efficiency, SIMKEYS lets the general public truly enjoy the unprecedented benefits and freedom of mobile messaging, and it will certainly pave the way towards the next stage of wireless Internet development.

This paper proposes a novel framework of shared protection, namely group shared protection (GSP), in mesh wavelength division multiplexing (WDM) networks with dynamically arriving connection requests. Based on the (M:N)/sup n/ control architecture, GSP has n mutually independent protection groups, each of which contains N SRLG-disjoint working paths protected by M protection paths. Due to the SRLG-disjointedness of the working paths in each protection group, GSP not only allows the spare capacity to be totally sharable among the corresponding working paths, but also reduces the number of working paths affected due to a single link failure. Based on the framework, an integer linear program (ILP) formulation that can optimally reconfigure the spare capacity for a specific protection group whenever a working-protection path-pair joins is proposed. Two heuristics namely link-shared protection (LSP) and ring-shared protection (RSP) are introduced for further compromising the performance and the computational complexity. The proposed schemes are compared with a reported one, namely successive survivable routing (SSR). The experimental results show that LSP, RSP and SSR yield similar performance in terms of resource sharing, whereas ILP outperforms all of them by (6-16%). Due to the limited number of working paths in each protection group, ILP can handle a dynamically arriving connection request in a reasonable amount of time. Also, we find that the number of affected working paths in GSP is about half of that in SSR. We conclude that GSP provides a scalable and efficient solution for dynamic spare capacity reconfiguration following the (M:N)/sup n/ control architecture.

The paper proposes a novel distributed control architecture for shared protection with reduced complete routing information, which aims to initiate a graceful compromise between the amount of link-state dissemination and the performance impairment due to the incompleteness of routing information. We first give explicit and comprehensive descriptions on a number of reported routing information dissemination scenarios for shared protection. A novel framework of link-state dissemination for facilitating shared protection, called reduced complete routing scenario, is introduced, in which the singular value decomposition (SVD) transformation is adopted to deal with the information reduction. We show, through simulation, that the proposed scheme can achieve a higher throughput and a better estimation in reconstruction of the spare provision matrix than the other schemes taking the same complexity of link-state dissemination.

This paper investigates the problem of optimal diverse routing for shared path-based protection in the complete routing information scenario on mesh optical networks, where a novel Integer Linear Programming (ILP) formulation is introduced such that the least-cost link-disjoint working and protection path-pair can be derived in a single step. The proposed ILP formulation is characterized by the facts that it is solvable with the commercially available Linear Programming (LP) solvers and that it can deal with the dependency between working and spare capacity in the network, which is a step ahead of the most state-of-the-art techniques in the design of diverse routing algorithms for shared protection. To verify the proposed ILP, an experiment is conducted to compare it with four reported schemes for end-to-end shared protection on two network topologies, namely APFPBC, MLR, ITSA, and ILP-2S, where blocking probability is taken as the performance metric with connection requests being dynamically launched into the networks. The simulation results show that the ILP formulation yields the best performance while the ILP-2S scheme investigating less network states yields the worst. We also use the results by the proposed ILP to evaluate the four heuristic-based schemes adopted in the simulation in terms of two performance indexes – the percentage of optimality (denoted as %opti) and the offset of optimality (denoted as Q).

In this paper, we investigate on penalty-based adaptable reservation admission (PARA) as an effective tool for quality of service (QoS) differentiation at the network layer and MAC layer. PARA enables resource reservation, allocation, and admission control to be adaptive to traffic conditions and the stress conditions at individual nodes. It also facilitates efficient differentiation between the service quality for applications with different QoS requirements, leading to an effective tool for DiffServ. Such capabilities are particularly useful for wireless networks and the Internet, resolving the QoS guarantee issues in the presence of mobility and bursty traffic. An important advantage and unique characteristic of PARA is that such differentiated service provisioning is under the control of network operators or individual nodes, in contrast to previous approaches in QoS adaptation. Our analytical results show that PARA can achieve considerably lower blocking rates for high-priority traffic as compared to previous resource management schemes without PARA.

In this paper, a survivable routing algorithm is proposed for shared segment protection (SSP), called optimal self-healing loop allocation (OSHLA), which dynamically allocates spare capacity for a given working lightpath in mesh wavelength-division-multiplexing (WDM) networks with partial wavelength conversion capability. Two novel graph transformation approaches, namely graph of cycles and wavelength graph of paths, are introduced to solve this problem, in which the task of survivable routing is formulated as a series of shortest path searching processes. In addition to an analysis on the computation complexity, a suite of experiments is conducted to verify OSHLA on four networks with different topologies and traffic loads. We find that the blocking probability and computation complexity are dominated by the upper bound on the length of the working and protection segments. Comparison is made between OSHLA and four other reported schemes in terms of blocking probability. The results show that OSHLA can achieve the lowest blocking probability under the network environment of interest. We conclude that OSHLA provides a generalized framework of survivable routing for an efficient implementation of SSP in mesh WDM partial wavelength convertible networks. With OSHLA, a compromise is initiated by manipulating the upper bound on the length of working and protection segments such that the best performance-computation complexity gain can be achieved.

This paper introduces a novel approach, called Short Leap Shared Protection with spare capacity Reallocation (SLSP-R), to deal with dynamic reconfiguration of spare capacity for MPLS-based recovery in the Internet backbone networks. SLSP-R is based on the SLSP framework and is designed to quantify the impact of computation complexity on network performance. The basic idea for SLSP-R is to subdivide a lengthy optimization process into several subtasks in order to trade the optimization quality with computation time. For this purpose, we compare three strategies for grouping working paths before an integer programming (InP) formulation is solved, namely, the Most Overlapped, Most Diverse, and Randomly Distributed. Analytical modeling of the problem is provided to show the feasibility of the subgrouping strategy. A numerical experiment as well as simulation-based study are conducted on four networks with different topology to evaluate the SLSP-R algorithm. The design methodology to determine the size of each subset of working paths is verified in the simulation.

This paper focuses on the problem of dynamic survivable routing for segment shared protection (SSP) in mesh communication networks provisioning bandwidth guaranteed tunnels. With SSP, a connection is settled by concatenating a series of protection domains, each of which contains a working and protection segment pair behaving as a self-healing unit for performing local restoration whenever the working segment is subject to any unexpected interruption. We first discuss the advantages of using SSP-the ability to shorten the restoration time as well as achieve a higher throughput by saving spare capacity required for 100% restorability; then the survivable routing problem is formulated into an Integer Linear Programming (ILP), where the switching/merging node pair of each protection domain along with the corresponding least-cost working and protection segment pair can be jointly determined for a dynamically arrived connection request. A novel approach of arc-reversal transformation is devised to deal with the situation that the working segments of two neighbor protection domains may overlap with each other by more than a single node. Due to a very high computation complexity induced in solving the ILP, a novel heuristic algorithm is proposed, named Cascaded Diverse Routing (CDR), to allocate protection domains for a connection request by performing diverse routing across a set of predefined candidate switching/merging node pairs. Experiments are conducted on five two-connected network topologies to verify the ILP and the CDR algorithm. We first determine the best diameter of protection domains for the CDR scheme in each network topology. Using the results of best diameters, CDR is compared with two reported schemes, namely PROMISE and OPDA. We demonstrate in the simulation results that the path-shared protection schemes are outperformed by the SSP schemes in terms of blocking probability under all possible arrangements in the experiment and that CDR yields better performance than PROMISE and OPDA due to the extra efforts in manipulating the location of working segments at the expense of longer computation time.

This paper proposes a suite of approaches to solve the survivable routing problem with shared protection. We first define in mathematics the maximum extent of resource sharing for a protection path given the corresponding working path according to the current network link-state. Then the problem of solving the least-cost working & protection path-pair (in terms of the sum of the cost) is formulated into an Integer Linear Programming process. Due to the dependency of the protection path on its working path, however, the formulation is not scalable with the network size, and takes an extra effort to solve. Therefore, we introduce two heuristic algorithms, called Iterative Two-Step-Approach (ITSA) & Maximum Likelihood Relaxation (MLR), which aim to explore the approximating optimal solutions with less computation time. We evaluate the performance of the proposed schemes, and make a comparison with some reported counterparts. The simulation results show that the ITSA scheme, with a properly defined tolerance to optimality, can achieve the best performance at the expense of more computation time. On the other hand, MLR delivers a compromise between computation efficiency & performance.

This paper provides a suite of approaches to solving the survivable routing problem with shared protection. The problem diverse solving the least-cost working and protection path-pair (in terms of the sum of the cost) is formulated into integer linear programming. We also introduce two heuristic algorithms, called iterative two-step-approach (ITSA) and maximum likelihood relaxation (MLR), which aim to finding the approximating optimal solution within a limited amount of computation time. We examine the performance of the proposed schemes and make a comparison with some reported counterparts. It is observed that the ITSA scheme with a properly defined tolerance to the optimality can achieve the best performance at the expense of much longer computation time. MLR can provide an ultra-fast path selection process, which behaves as a good tradeoff between computation efficiency and performance.

In this paper, we propose an approach of optimal protection domain allocation, called OPDA (optimal protection domain allocation), for dynamically allocating spare capacity for a given working lightpath in WDM networks with partial wavelength conversion capability. The optimization process is formulated as a shortest path searching problem in a transferred graph of cycles and wavelength graph of paths. We conduct a series of experiments to verify the proposed approach on four networks with different topologies and traffic load. We conduct experiments to compare the blocking probability of using OPSA with four reported schemes. The results show that OPDA achieves the best performance.

In this paper, we propose the multichannel variable-radius multiple access (M-VRMA) scheme for power-controlled multichannel medium access control (MAC) in mobile ad hoc networks. We propose the RTS/object-to-sending (OTS)/VP-CTS (ROV) protocol based on M-VRMA, multiple access with lag time, OTS, and VP-CTS for efficient variable-radius supports in heterogeneous ad-hoc networks, without relying on busy-tone or any mechanisms that require expensive specialized hardware or more than one transceivers per device. Our simulation results demonstrate that for the same radio bandwidth, ROV can achieve considerably higher throughput as compared to fixed-radius IEEE 802.11 or previous power-controlled RTS/CTS protocols without variable-radius supports.

In this paper, we solve the survivable routing problem in dynamic WDM mesh networks under the framework of short leap shared protection (SLSP). A novel algorithm called cascaded diverse routing (CDR) is proposed. We also demonstrate a novel approach to solving the diverse routing problem in networks with dynamic traffic for the purpose of shared protection, called iterative two-step-approach (ITSA). Simulation is conducted using four different networks (22-, 30-, 79-, 100-node) for a comparison between ordinary shared protection schemes and the SLSP scheme. Simulation results show that the best performance can be achieved with well-design diameter of protection domains for every connection request according to the size and topology of the network.

This paper proposes a scalable design for next-generation optical cross-connects (OXCs), where a novel strategy for dimensioning the network switching capability as a long term planning is presented. When traffic demand grows, the proposed scheme simply expands the switching capacity of OXCs in waveband- and fiber-switching tiers. To minimize the number of extra fibers for waveband- and fiber-switching tiers required to satisfy a given traffic matrix, we formulate the problem of routing and wavelength assignment with tunnel allocation (RWAT) into two integer linear programming (ILP) processes that are performed sequentially. Experiments are conducted on two sample networks to compare the throughput and the number of switch points when the networks adopt different switching architectures with different traffic loads. We conclude that the proposed optimization scheme can dimension the networks with expandability and scalability to the growing traffic demand.

This paper provides an approximate optimal routing algorithm, called relax-converter-first (RCF), for dynamic WDM networks with heterogeneous and partial wavelength conversion capability in each node. The algorithm can derive an optimal solution if the cost of consuming a wavelength converter is set much smaller than is the case for taking a wavelength channel. We propose a wavelength graph technique along with a modified Dijkstra's shortest path first algorithm. Simulation is conducted to verify the performance in terms of blocking probability focusing on the following two themes: first, a comparison in performance is conducted among the cases of using fixed alternate routing, shortest path first algorithm with wavelength graph (SPAWG), and RCF; second, the performance of using the RCF scheme is examined with different cost of taking a wavelength converter in network nodes with different wavelength conversion capability. We also provide the simulation statistics about the optimality in using the RCF scheme under different network environments.

This paper proposes a scalable design for next-generation optical cross-connects (OXCs). We present a novel strategy for dimensioning the switching capability as a long term planning. Switching fabrics in OXCs have to be expanded according to traffic growth, which may incur a scalability problem due to the exponentially increasing cost in manufacturing and maintenance. The proposed scheme expands the switching capacity of OXCs with waveband- and fiber-switching components (or, equivalently, expands the network capacity with waveband- and fiber-switching tiers). To minimize the number of extra fibers for waveband- and fiber-switching tiers required to satisfy a given traffic matrix, we formulate the problem of routing and wavelength assignment (RWA) with tunnel allocation (RWAT) into a constraint programming (CP) process. The CP is simplified as two integer linear programming (ILP) processes that are performed sequentially. Experiments are conducted on four examples to compare the throughput and the number of switching points when different switching architectures are adopted under different traffic increase. The benefits of our approach are demonstrated. Finally, we conclude that the proposed optimization scheme can dimension the networks with expandability and scalability to the growing traffic demand.

We solve the problem of protection domain allocation in dynamic WDM networks under the framework of short leap shared protection (SLSP). A novel survivable routing algorithm, namely dynamic SLSP (D-SLSP), is proposed, which contains two on-line algorithms: heavy fixed alternate routing (H-FAR) and cascaded diverse routing (CDR). A novel approach for deriving the link-state for solving the optimal protection path corresponding to a working path is given. A simulation is conducted using four different networks (22-, 30-, 79-, 100-node) for a comparative study between the ordinary shared protection schemes and the SLSP. Simulation results show that the best efficiency is achieved by using SLSP with a properly chosen diameter in each protection domain for every connection request, according to the size and topology of the network.

A novel planning algorithm, namely capacity-balanced alternate routing (C-BAR), is proposed for enhancing fixed alternate routing in dynamic wavelength-routed WDM networks. With C-BAR, alternate paths between each source-destination (S-D) pair are defined at the network planning stage according to the load distribution and the location of each S-D pair, so that the routing of lightpaths can take the most advantages of the load-balancing characteristic of the alternate paths. A methodology for designing the number of alternate paths between an S-D pair for achieving a specific performance requirement is demonstrated. Simulation is conducted to examine the proposed approaches, and show that the C-BAR algorithm can significantly improve the performance in blocking probability compared with the other reported RWA schemes.

GMPLS was devised to be able to support multi-granularity traffic and bundling of wavelength channels in the optical domain. It has been a challenge to achieve an efficient and flexible use of the multi-granularity OXCs (MG-OXCs) in the optical next generation Internet which is assumed to deploy a generalized MPLS (GMPLS) based control plane. In this paper, a heuristic algorithm, capacity-balanced static tunnel allocation (CB-STA), is proposed for solving the problem of routing and wavelength assignment with tunneling (RWAT), which is aimed at facilitating an efficient use of bandwidth in the WDM networks with MG-OXCs. CB-STA allocates fiber and waveband tunnels into networks at the network planning stage, which requires each tunnel to have a fixed length and capacity-balanced characteristics, in order to increase the link utilization in the fiber and waveband switching layers. A comparison is made, using simulation, between CB-STA and a dynamic tunnel allocation scheme. Detailed discussions are provided.

In this paper, we solve the survivable routing problem in dynamic WDM mesh networks under the framework of short leap shared protection (SLSP). A novel algorithm called cascaded diverse routing (CDR) is proposed. We also demonstrate a novel approach to solving the diverse routing problem in networks with dynamic traffic for the purpose of shared protection, called iterative two-step-approach (ITSA). Simulation is conducted using four different networks (22-, 30-, 79-, 100-node) for a comparison between ordinary shared protection schemes and the SLSP scheme. Simulation results show that the best performance can be achieved with well-designed diameter of protection domains for every connection request according to the size and topology of the network.

This paper solves the problem of path selection for connection-oriented MPLS-based mesh networks with a special focus on implementation issues in middle-sized networks, such as metropolitan-area networks (MANs). A novel network planning algorithm, called capacity-balanced alternate routing (C-BAR), is proposed. For C-BAR, alternate paths between each ingress-egress pair are defined at a network planning stage according to the network topology and potential traffic load and location of each ingress-egress pair so that load-balancing can be achieved in routing label switched paths (LSPs). Both analytical and simulation-based studies have been conducted to examine the proposed approach. The results show that the C-BAR algorithm can significantly improve the performance in blocking probability by spreading potential traffic to the whole network compared with other reported connection-oriented routing schemes.

GMPLS is one of the most promising frameworks proposed for the next generation optical Internet, which supports multi-granularity of switching types including fiber-, waveband- and lambda-switching in the optical domain. We present some algorithms for solving the routing and wavelength/tunnel assignment (RWTA) problem based on the multi-granularity 4-tier switching architecture. We also propose novel network planning algorithms, the weighted network link state, and an enhancement to the fixed-alternative routing scheme, the heavy fixed alternative routing (H-FAR), to facilitate RWTA. We show that with the weighted network link state and H-FAR, the RWTA problem in the optical Internet with multi-granularity OXCs (MG-OXCs) can be solved efficiently, and the performance in terms of call blocking rate in a network with MG-OXCs is comparable with that in a lambda-switched network, which means the link utilization of tunnels is close to that of wavelength-switched channels.

The task of finding a physically disjoint protection path from a working path to guarantee service continuity during the occurrence of failures has been one of the most important issues for improving survivability of the optical Internet. We focus on the study of finding asymmetrically weighted optimal node-disjoint path-pairs for shared protection so that network performance in terms of success rate of building up disjoint path-pairs and average restoration time are improved. We first propose and examine a novel heuristic algorithm to solve the diverse routing problem in a network with heterogeneous link states for working and protection path pairs, which is based on the sub-optimal path-solver (SOPS), a new method for finding loop-less K-shortest paths. A simulation-based study on the weighting parameter of working paths versus network performance is conducted.