This paper investigates the uplink secrecy performance of a reconfigurable intelligent surface (RIS)-aided multiple-input multiple-output non-orthogonal multiple access (MIMO-NOMA) network. In the proposed system model, users communicate with the base station (BS) via a strategically partitioned RIS. However, a silent passive eavesdropper overhears the data through a direct link. As part of the proposed security design, we propose a user-centric artificial noise (AN) transmission strategy that degrades the decoding ability of the eavesdropper without sacrificing the power budget. The AN is nullified in the composite channel utilizing singular value decomposition. After analyzing the channel statistics, which consider all channels experiencing Nakagami-$m$fading, we derive theoretical closed-form expressions for the ergodic secrecy rate (ESR) for each user in the NOMA pair using Gauss-Chebyshev quadrature and Taylor-Maclaurin expansions. Monte Carlo simulations validate the correctness of our analysis. The numerical results confirm that our proposed scheme consistently achieves a positive ESR. We also explore the impact of channel fading and RIS-partitioning ratio on the uplink ESR and comment on optimal power allocation. Notably, the results also confirm that the proposed system outperforms the benchmark MIMOorthogonal multiple access-based scheme.

Federated learning (FL) has emerged as a promising learning paradigm in which only local model parameters (gradients) are shared. Private user data never leaves the local devices thus preserving data privacy. However, recent research has shown that even when local data is never shared by a user, exchanging model parameters without protection can also leak private information. Moreover, in wireless systems, the frequent transmission of model parameters can cause tremendous bandwidth consumption and network congestion when the model is large. To address this problem, we propose a new FL framework with efficient over-the-air parameter aggregation and strong privacy protection of both user data and models. We achieve this by introducing pairwise cancellable random artificial noises (PCR-ANs) on end devices. As compared to existing over-the-air computation (AirComp) based FL schemes, our design provides stronger privacy protection. We analytically show the secrecy capacity and the convergence rate of the proposed wireless FL aggregation algorithm.

Bootstrapping security among wireless devices without prior-shared secrets is frequently demanded in emerging wireless and mobile applications. One promising approach for this problem is to utilize in-band physical-layer radio-frequency (RF) signals for authenticated key establishment because of the efficiency and high usability. However, existing in-band authenticated key agreement (AKA) protocols are mostly vulnerable to Man-in-the-Middle (MitM) attacks, which can be launched by modifying the transmitted wireless signals over the air. By annihilating legitimate signals and injecting malicious signals, signal modification attackers are able to completely control the communication channels and spoof victim wireless devices. State-of-the-art (SOTA) techniques addressing such attacks require additional auxiliary hardware or are limited to single attackers. This paper proposes a novel in-band security bootstrapping technique that can thwart colluding signal modification attackers. Different from SOTA solutions, our design is compatible with commodity devices without requiring additional hardware. We achieve this based on the internal randomness of each device that is unpredictable to attackers. Any modification to RF signals will be detected with high probabilities. Extensive security analysis and experimentation on the USRP platform demonstrate the effectiveness of our design under various attack strategies.

Effective sharing of spectrum resources is essential in forthcoming sixth-generation (6G) wireless networks to deploy massive Internet-of-Things (IoT) terminals. Unmanned aerial vehicles (UAVs) can significantly support IoT devices, especially in remote or disaster areas. Recently, power-domain non-orthogonal multiple access (PD-NOMA) utilized with underlay spectrum sharing has been proposed as a promising solution to enhance spectral efficiency. However, in a UAV-enabled multi-user spectrum sharing network, the risk of wiretapping in uplink signaling should be studied to ensure secured communications. This article investigates the uplink secrecy performance of a UAV-supported PD-NOMA-based underlay spectrum sharing (PDN-USS) network. The system is principally comprised of a secondary network with a pair of IoT terminals and a UAV receiver, where imperfect successive interference cancellation is carried out to decode data. Considering a transmission power constraint imposed at the secondary transmitters, we derive the closed-form expressions of the secrecy outage probability (SOP) for both IoT terminals. All the analytical expressions are obtained considering all the links undergo Nakagami-m fading. The simulation results validate the accuracy of the analysis and confirm that the PDN-USS system outperforms the benchmark OMA-based USS scheme in terms of the SOP. The results also provide valuable insights into the impact of the interference temperature and residual interference on the uplink SOP.

Spectrum activity surveillance (SAS) is essential to dynamic spectrum access (DSA)-enabled systems with a two-fold impact: it is a primitive mechanism to collect usage data for spectrum efficiency improvement; it is also a prime widget to collect misuse forensics of unauthorized or malicious users. While realizing SAS for DSA-enabled systems appears to be intuitive and trivial, it is, however, a challenging yet open problem. On one hand, a large-scale SAS function is costly to implement in practice; on the other hand, it is not clear how to characterize the efficacy and performance of monitor deployment strategies. To address such challenges, we introduce a three-factor space, composed ofspectrum,time, andgeographic region, over which the SAS problem is formulated by a two-step solution: 3D-tessellation for sweep (monitoring)coverageand graph walk for detectingspectrum culprits, that is, devices responsible for unauthorized spectrum occupancy. In particular, our system model transforms SAS from a globally collective activity to localized actions, and strategy objectives from qualitative attributes to quantitative measures. With this model, we design low-cost deterministic strategies for dedicated monitors, which outperform strategies found by genetic algorithms, and performance-guaranteed random strategies for crowd-source monitors, which can detect adversarial spectrum culprits in bounded time.

The channel-hopping (CH) based rendezvous is an important technique in next-generation wireless cognitive radio networks (CRNs) where spectrum efficiency is desired. It allows unlicensed secondary users (SUs) to dynamically schedule rendezvous channels using their assigned CH sequence. Rendezvous is an essential operation for radios in CRNs to meet and establish a communication link, or find a common channel. Thus, radios can exchange information and communicate on a channel.In this paper, we propose a rendezvous protocol called K-Group Random Channel Hopping (K-RCH) which is based on the symmetric-role model. K-RCH assigns nodes into groups. Each group contains at least two nodes, which means our model is general and can fit both pairwise or multi-user rendezvous. K-RCH increases the chance of rendezvous by synchronizing channel hopping patterns of nodes in the same group and allowing for multi-round rendezvous. K-RCH considers a heterogeneous channel availability model and is suitable for complicated communication environments. Our simulation results show that K-RCH achieves a much shorter rendezvous time than most existing rendezvous protocols. The expected time to rendezvous (ETTR) is reduced by more than 85% as compared to the Jump-Stay strategy and the TENOR protocol. The ETTR decreases with an increasing number of SUs.

With wireless virtualization, Wireless Infrastructure Providers (WIPs) are able to sublease out RF spectrum to multiple Wireless Virtual Network Operators (WVNO) who in turn offer services to their customers while sharing the same physical infrastructure. WVNOs are capable of leasing through a reservation process which may be accompanied by some strict guarantees, usually discouraging overbooking through certain penalties. On a global scale, it is important for WIPs to also be able to proactively reserve spectrum resources for consumer usage based on informed estimates. As part of the educated estimation, predictions are made from data of previous spectrum allocations and harmonized with aggregation of crowd-sourced data for events in a bid to reduce the probability of overbooking. The data aggregation effort relies on the the reliability of workers to generate highly accurate results using a community-based aggregation model. Also in this paper, a novel spectrum reservation prediction algorithm, namely Volume-conditioned Spectrum Selective Moving Average (VSSMA) is proposed using the trend similarity of spectrum allocation. The simulation results show that the relative mean error of the VSSMA algorithm is much lower than the Exponential Weighted Moving Average (EWMA) algorithm which is widely used now. We validate the desirable properties of the proposed approach through theoretical analysis, as well as simulations.

Effective clustering is vital to mitigate routing scalability and reliability issues in heterogeneous vehicular networks. In this paper, we propose an adaptive clustering scheme to maximize the cluster stability in vehicular networks. The scheme uses the predicted driving behavior of vehicles over a time horizon to maximize the clusters' lifetime. To this end, we first define the stability degree of vehicles by exploiting the unique aspects of vehicular environments. We then formulate the clustering problem as an optimization problem, which is used within a rolling horizon framework in the cluster formation process. Our scheme is based on a heterogeneous vehicular network architecture, which allows the coexistence of dedicated short-range communication and cellular network for vehicular communications. The simulation results demonstrate that our scheme significantly outperforms alternative clustering algorithms in terms of the overall clusters' lifetime under different traffic conditions. Our scheme can also be utilized to provide a well-grounded comprehension of the optimally of the existing and future distributed clustering algorithms.

The millimeter wave (mmWave) frequency band is a promising candidate for next generation cellular and wireless networks. To compensate the significantly higher path loss due to the higher frequency, the mmWave band usually uses the beamforming technology. However, this makes the network topology control a great challenge. In this paper, we propose a novel framework for network topology control in mmWave networks, termed Beamforming Oriented tOpology coNtrol (BOON). The objective is to reduce total transmit power of base stations and interference between beams. BOON smartly groups nearby user equipment into clusters, constructs sets from user equipment clusters, and associates user equipment to base stations and beams. We compare BOON with three existing topology control schemes in terms of transmit power, network sum rate, signal to interference and noise ratio, and computation complexity. The results indicate that overall BOON significantly outperforms them. In particular, on average BOON uses only 10, 32, and 25 percent transmit power of other three schemes, respectively, to achieve the same network sum rate.

An on-demand spectrum access cognitive radio network offers spectrum services to users, so that users can dynamically set up application-oriented virtual topologies to support user applications. In this paper, we develop a mathematical model for the on-demand spectrum access architecture for cognitive radio networks based on the citizens broadband radio service (CBRS). The model can be used to estimate the blocking probability of spectrum demands from priority access license users, the network capacity, and the number of free spectrum bands available for lower priority general authorized access users. The performance evaluation indicates that the results from the mathematical model match simulation results well, which validates the accuracy of our model.

Advanced metering infrastructure (AMI) networks allow utility companies to collect fine-grained power consumption data of electricity consumers for load monitoring and energy management. This brings serious privacy concerns since the fine-grained power consumption data can expose consumers' activities. Privacy-preserving data aggregation techniques have been used to preserve consumers' privacy while allowing the utility to obtain only the consumers total consumption. However, most of the existing schemes do not consider the multidimensional nature of power consumption in which electricity consumption can be categorized based on the consumption type. They also do not consider multisubset data collection in which the utility should be able to obtain the number of consumers whose consumption lies within a specific consumption range, and the overall consumption of each set of consumers. In this article, we propose an efficient and privacy-preserving multidimensional and multisubset data collection scheme, named “MDMS. ” In MDMS, the utility can obtain the total power consumption as well as the number of consumers of each subset in each dimension. In addition, for better scalability, MDMS allows the utility to delegate bill computation to the AMI networks' gateways using the encrypted readings and following the dynamic prices in which electricity prices are different based on both the time and the consumption type. Moreover, MDMS uses lightweight operations in encryption, aggregation, and decryption resulting in low computation and communication overheads as given in our experimental results. Our security analysis demonstrates that MDMS is secure and can resist collusion attacks that aim to reveal the consumers' readings.

Performance of wireless networks for Internet of Things (IoT) is suffering from exponential growth of lightweight hand-held and smart IoT devices as well as the data flow in the network. Static assignment of wireless resources is creating bottleneck to the further development of emerging applications, including IoT and cyber-physical systems. Wireless network virtualization through slicing of primary wireless resources is regarded as an emerging approach for enhancing overall network performance to solve the bottleneck problem for those emerging applications. In this paper, we study wireless virtualization where a three-layer game is formulated for wireless infrastructure providers (WIPs), mobile virtual network operators (MVNOs), and IoT devices (or end users). In the proposed three-layer game, players play sequentially to find out their optimal strategies. With the help of a controller, WIPs divide and reconfigure their RF bands to sublease frequency slices to MVNOs based on their service-level-agreement. MVNOs let end users use their subleased frequency slices. For the game, we present a unique optimal solution that facilitates a tradeoff between quality of service of end users, payoffs of MVNOs and payoff of WIPs. We also present a necessary condition and closed form for the existence of an equilibrium in the game. Furthermore, performance of the proposed approach is evaluated using numerical results which show that the payoffs of WIPs and MVNOs are maximized while offering competitive price for the subleased RF spectrum for their users.

Internet of Things (IoT) is a networking paradigm that interconnects physical systems to the cyber world, to provide automation and intelligence via interdependent links between the two domains. Such interdependence renders IoT systems vulnerable to random failures, e.g., broken communication links or crashed cyber instances, because a single incident in one domain can develop into a cascade-of-failures across domains, which dissolves the network structure, and has devastating consequences. To answer how robust an IoT system is, this paper studies its resilience by examining the impact of edge- and jointly-induced cascades, that is, a sequence of failures caused by randomly broken physical links (and simultaneous failing cyber nodes). Resilience of an IoT system is quantified by two new metrics, the critical edge disconnecting probability φcr, i.e., the maximum intensity of random failures the system can withstand, and the cascade length τcf, i.e., the lifetime of a cascade. For IoT systems with Poisson degree distributions, we derive exact solutions for the critical disconnecting probability φcr, above which an edge-induced cascade will completely fragment the network. We also find that the critical condition φcrmarks a dichotomy of the expected cascade length E(τcf): for the super-critical (φ > φcr) scenario, we obtain E(τcf) ~ exp(1 - φ) through analysis, while for the subcritical scenario, we observe E(τcf) ~ exp(1/1 - φ) through simulations. With these results, the final outcome of a cascade can be anticipated upon the initial failures, while the reaction window of time-sensitive countermeasures can be obtained before a cascade fully unfolds.

Spectrum sharing is a key technology to relieve the ever-increasing spectrum demand and realize the full potential of radio spectrum. In this paper, we study spectrum sharing between higher priority users and lower priority users under geo-location based spectrum sharing systems. We consider a dynamic spectrum allocation scheme that allocates spectrum to a higher priority user based on its spectrum need that can be determined by its traffic load. The lower priority users utilize the unallocated spectrum. In addition to studying the performance of higher priority users with this dynamic spectrum allocation scheme, we also investigate the impact of this scheme on spectrum availability and stability of lower priority users. We develop a mathematical model to analyze the performance. The simulation results indicate that spectrum sharing is efficient, and the spectrum is abundant and relatively stable to lower priority users, even when the system is moderately loaded with higher priority users.

For enhancing the utilization of radio frequency (RF) bands, dynamic spectrum access has been considered to be an emerging paradigm where unlicensed secondary users access the licensed RF spectrum opportunistically without causing harmful interference to licensed primary users. In order to access idle channels, secondary users are required either to sense channels or search the geolocation based spectrum database before starting their actual communications. Note that the database searching approach has been proven to be more effective than the channel sensing approach since the sensing based approach results in higher sensing uncertainties. When a large number of secondary users query the spectrum database for finding idle channels at the same time, the spectrum server could be overwhelmed that could result in (unintentional) Denial-of-Service attack. In this paper, we investigate group-query-as- aservice for searching idle channels in database driven dynamic spectrum access where selected secondary users (aka grid leaders who are selected based on the interactive trust levels, location and resources in their grids) query on behalf of the other secondary users (aka grid followers). In this approach, secondary users are associated with the contours created based on same idle channels with the help of spectrum sensors and mobile edge computing (MEC) servers at each base station. The performance of the proposed group-query-as-a-service is evaluated using numerical results obtained from Monte Carlo simulation. We found that the proposed approach results in less delay with increase edge hit rate and higher throughput than the individual query based approach.

Internet of things (IoT) is expected to provide a fully informative and controllable environment that features networking, automation, and intelligence by interconnecting physical systems to cyber world. Such a correlation opens the interdependence between the two, upon which a single incident in one domain, e.g., a broken communication link, or an out-of-battery device, can cause a cascade-of-failures across physical and cyber domains. To understand the resilience of IoT systems against such detrimental cascades, this paper studies the aftermath of edge and jointly-induced cascades, that is, a sequence of failures induced by randomly broken physical links (and simultaneous failing cyber nodes) by answering how many nodes will survive the cascade with a newly defined node yield metric. Specifically, we construct a framework to establish self-consistent equations of node yield through an auxiliary graph, without requiring the exact network topology. Then two algorithms are proposed to numerically calculate node yield for interdependent networks with arbitrary degree distributions. For random graph with Poisson degree distributions, we prove the existence of a critical initial edge disconnecting probability φcr, under which an edge-induced cascade will result in dissolving the network topology, derive the closed form solution for φcr, and find that φcrincreases sub-linearly with the mean degree of the physical network.

We propose a new energy harvesting (EH) strategy that uses a dedicated energy source (ES) to optimally replenish energy for radio frequency EH powered wireless devices. Specifically, we develop a two-step dual tunnel energy requesting (DTER) strategy that minimizes the energy consumption on both the EH device and the ES. Besides the causality and capacity constraints that are investigated in the existing approaches, DTER also takes into account the overhead issue and the nonlinear charge characteristics of an energy storage component to make the proposed strategy practical. Both offline and online scenarios are considered in the second step of DTER. To solve the nonlinear optimization problem of the offline scenario, we convert the design of offline optimal energy requesting problem into a classic shortest path problem and thus a global optimal solution can be obtained through dynamic programming algorithms. The online suboptimal transmission strategy is developed as well. Simulation study verifies that the online strategy can achieve almost the same energy efficiency as the global optimal solution in the long term.

Wireless virtualization is regarded as an emerging paradigm for enhancing radio frequency (RF) spectrum utilization through slicing of primary wireless resources in heterogeneous networks (HetNets). In this paper, we study the creation of virtual wireless networks through wireless virtualization for mobile virtual network operators (MVNOs) where portion of the primary bandwidth is sliced and leased to the MVNOs. For wireless virtualization, owners of wireless infrastructures in HetNets divide and reconfigure their RF bands to sublease to MVNOs based on their service-level-agreements while keeping enough wireless resources to their own users. Next, we leverage the wireless virtualization to investigate the network sum-capacity and revenue maximization problems for MVNOs where MVNOs offer competitive prices to attract more users for wireless communications. We evaluate the performance of the proposed approach using different metrics such as network sum-capacity, revenue of the MVNOs, competitive price for RF spectrum usage that is based on the spectral capacity of the MVNOs, and the outage probability. Numerical results obtained from simulations show that the sum-capacity of virtual network can be maximized while maximizing their revenue and offering lower/competitive spectrum-usage price for their users.

Energy harvesting is emerging as a promising alternative source to power the next generation of wireless networks. This paper introduces a new energy harvesting strategy that uses a dedicated energy source to optimally replenish energy for radio frequency (RF) based wireless communication systems. Specifically, we develop a two-step dual tunnel energy requesting (DTER) strategy that allows an energy harvesting device to effectively obtain energy from a dedicated energy source. While minimizing the system energy consumption, DTER takes into account the practical constraints on both the energy source and the energy harvesting device. Additionally, the overhead issue and the charge characteristics of an energy storage component are examined to make the proposed strategy practical. To solve the nonlinear optimization problem in DTER, we convert the design of optimal energy requesting problem into a classic shortest path problem and thus enable us to find a global optimal solution through dynamic programming algorithms. Theoretical analysis and simulation study verify that DTER outperforms two other schemes in the literature.

Vehicular ad-hoc networks (VANETs) have been envisioned to prominently enhance the road safety and traffic efficiency through real-time vehicle- to-vehicle and vehicle-to- infrastructure communications. Roadside Units (RSUs) play an important role in vehicular environments in terms of connectivity, routing, and transmission delay. However, deploying enough RSUs to provide a universal coverage within an area is not feasible. In addition, there still lacks understanding of the performance of message dissemination in urban environments where one deploys RSUs in a stand- alone fashion. In this paper, we study the performance of message dissemination in VANET environments and propose a Safety-Based Disconnected RSU Placement algorithm (S-BRP) that reduces the dissemination delay in some areas. We evaluate the S-BRP algorithm through extensive simulation studies. The proposed algorithm outperforms Mesh, the alternate deployment policy, in terms of the dissemination delay and traffic flow.

Large-scale multiple input multiple output (MIMO) wireless system is regarded as a solution to provide high speed connection for exponentially increasing wireless subscriptions for emerging cyber-physical systems (CPSs) and Internet of Things. In order to realize its full potential, there are several challenges to be addressed to achieve high secrecy rate or data rate. In this paper, we analyze outage probability for secrecy rate in MIMO wireless systems in the presence of eavesdroppers and jammers for CPS devices. Our proposed approach takes into account the impact of jammers while finding the best response to minimize the jamming/interfering effect (or to enhance the secrecy rate) and the impact of eavesdropper in secrecy rates of the users. We present formal analysis for secrecy outage probability and interception probability considering Rayleigh fading scenario. The performance is evaluated by using numerical results obtained from Monte Carlo simulations. Numerical results indicate that the system performance is improved significantly when the users adapt their transmit vectors based on their observed interference values. Furthermore, the secrecy outage probability increases with power of jammer and the secrecy capacity decreases when jammer power increases. We observed that the proposed approach outperforms the other existing approaches.

Given a set of communication links in cognitive radio networks, assume that the underlying channel state information along each link is unknown; however, we can estimate it by exploiting the feedbacks and evolutions of channel states. Assume time is divided into time-slots. Under the protocol interference model, the opportunistic spectrum scheduling problem aims to select interference-free links to transmit at each time-slot to maximize the average throughput over the long time horizon. Existing works on the opportunistic spectrum scheduling problem cannot satisfyingly address the wireless interference constraints. We apply the framework of restless multi-armed bandit and develop approximation algorithms for the problem with stochastic identical links and nonidentical links respectively. Based on the updated estimations of channel states, the proposed algorithms keep refining future link scheduling decisions. We also obtain approximation bounds of these two proposed algorithms.

Cognitive radio network is regarded as an emerging technology to solve 'spectrum scarcity' through dynamic spectrum access to support exponentially increasing wireless subscriptions. However, spectrum sensing and dynamic spectrum sharing in cognitive radio network invite more security attacks making security as one of the main concerns. In this paper, we analyze the performance of the secondary users in terms of physical-layer security in the presence of both eavesdroppers and jammers in cognitive radio networks. In this case, secondary users not only have to compete against eavesdroppers and jammers (who are trying to reduce the secrecy rates of secondary users) but also have to compete with other secondary users to gain access to idle channels to gain high secrecy rates. The main contribution of this work is to investigate game theoretical model to maximize utility of secondary users in the presence of eavesdroppers and jammers. The proposed approach can be particularized to a scenario with eavesdroppers only or jammers only while evaluating the performance of secondary user physical layer security. Performance of the proposed approach is evaluated with the help of numerical results obtained from simulations and the proposed approach outperforms other existing methods. Furthermore, there is sever impact on utilities (secrecy rates) of secondary users when both eavesdroppers and jammers are active in the network.

We study real-time multicast scheduling in multi- hop wireless sensor networks. Given multiple heterogeneous periodic multicast tasks, for each task, the data produced by the distinguished source node for a certain control application with sufficiently long time horizon need to be delivered to all target nodes periodically, the objective is to design an interference-aware routing and scheduling protocol to meet the delay requirements. In this work, we propose an efficient distributed routing and scheduling protocol under the protocol interference model. We conduct schedulability analysis and the proposed protocol approximately optimize the schedulable load. Based on our protocol design, we propose schedulability test schemes for a set of real-time multicast tasks. The performance evaluation results corroborate our theoretical analysis.

On Demand Frame Contention (ODFC) is designated as a solution to exclusive self-coexistence in wireless regional area networks. According to ODFC, contention winners are selected in a random manner regardless of the users' delay constraints and frame demands. As a result, ODFC may freeze some users due to that their delay constraints are not satisfied. Moreover, it may lead to a unfair resource distribution in terms of frame demands. To fully consider various delay constraints and frame demands, in this paper we formulate the resource allocation optimization problem as an integer programming problem and present a new approach termed \emph{On Demand Delay-constrained Fair Distribution} (ODDFD). ODDFD utilizes an iterative approach to solve the resource allocation problem considering delay constraints and frame demands. The distinguished feature of ODDFD is that it is able to deal with both delay sensitive networks and delay insensitive networks. Specifically, for a delay sensitive network, ODDFD minimizes jitter variance and average unexpected delay. For a delay insensitive network, the resource is allocated based on their frame demands and achieve a fair distribution in terms of their demands. Extensive simulations are conducted and verify that the jitter variance and average unexpected delay are decreased in a delay sensitive network, and the fairness of frame demands is increased in a delay insensitive network.

Spectrum sensing plays a critical role in cognitive radio networks. Most of existing works on spectrum sensing adopted energy detection which takes samples on a band and then compares the summation with a threshold to determine the state of the band. However, if a licensed band is subdivided by the primary users, such as in the unlicensed WiFi band, the energy detection faces a challenge. The threshold used to decide if there is a PU signal on the band now depends on the number of sub-bands that are being used by primary users, since the received signal power on the band is now dependent on the number of used sub-bands. In this work, we propose a wavelet based spectrum sensing approach that does not depend on the number of used sub-bands and adaptively detects PU signals on a licensed band. We use the measured real world signals to test the approach. The simulation results indicate that the proposed approach can effectively detect the PU signal on a licensed band without needing the knowledge of band subdivision. In addition, the comparative study with the existing techniques is performed to evaluate two performance metrics, true detection and false alarm, for primary users signal detection.

In this paper, we propose an anti-jamming game for space communication systems where a cognitive jammer reactively senses channels using energy detection and jams the channel using "detect and jam" strategy while the legitimate transmitter-receiver pair uses a joint frequency hopping and power/rate adaptation approach to avoid the impact of the jamming. Jamming and anti-jamming process between legitimate satellite link and a jammer is formulated as a zero-sum game. The proposed game takes into account of the signal propagation delay, detection performance (signal detection and jamming start time) of a jammer, received jamming power from the jammer, and hopping and jamming costs. Performance of the proposed approach is evaluated with the help of simulations and the proposed approach outperforms other existing methods.

The current opportunistic spectrum access architecture suffers from several technical barriers. Capitalizing on recent spectrum policy evolution and technology advances, we propose an application-oriented spectrum sharing architecture, termed on-demand spectrum access, to eliminate the barriers bothering the opportunistic spectrum access architecture. We consider a spectrum service provider that has a mesh infrastructure network and offers on-demand spectrum services to users. The users can dynamically set up application-oriented virtual topologies to carry out specific applications such as video conferences. We develop an efficient online spectrum service provision algorithm, termed Provision based on Onion Subsetting. The time complexity and the correctness are analyzed. We evaluate the performance of the on-demand spectrum access architecture under the provision algorithm through simulations.

We study minimum latency multiflow scheduling in duty-cycling multi-hop wireless networks. Given a set of multi-hop flows in duty-cycling wireless networks, each flow has a source node and a destination node, the objective is to schedule all multi-hop flows within a minimum latency. Under the uncoordinated duty-cycling model, we design transmission scheduling that can achieve a small constant factor of the optimal latency. The approximation ratio is independent of the period length p where p is the period length of duty-cycling networks. We also propose a duty-cycle-aware multiflow scheduling method based on node coloring. Finally, we study the routing and scheduling for multi-hop multiflow in wireless networks where each node has a full duty-cycle.

Spectrum sensing is a critical component for cognitive radio networks. Most of the spectrum sensing algorithms and performance analysis, however, assume that the secondary users are stationary. In this paper, we investigate the performance analysis of spectrum sensing by mobile secondary users. Two performance metrics, false alarm probability and miss detection probability, are thoroughly investigated. In addition, a new performance metric, expected transmission time, is designed to factor the secondary users' mobility. The random waypoint based mobility model is adopted for secondary users. For spectrum sensing by mobile secondary users, a critical variable is the distance between the primary user and mobile secondary users. We mathematically model this distance, and derive its probability distribution. At last, the expressions are derived for all three performance metrics, the false alarm probability, the miss detection probability, and the expected transmission time. Extensive simulations are performed, and the results are consistent with the theoretical analysis. It is concluded that the mobility of secondary users has significant impact on miss detection probability, but not on false alarm probability.

In this paper, we address the challenge of providing secondary users access to licensed spectrum when there are active primary user transmissions. The motivation is to eliminate the disruption to secondary user communications by the resurgence of primary user transmissions. We propose a novel protocol, termed spectrum co-access protocol (SCAP), for secondary users to transparently and simultaneously access spectrum with primary users. This protocol enables mutually beneficial coexistence between the primary user network and the secondary user network. Through spectrum co-access, SCAP creates a virtual SU control channel in licensed spectrum that is transparent to the PU. The result is a unique medium access control protocol that allows for transparent simultaneous spectrum access between the SU and PU networks. The performance evaluation indicates that SCAP provides significant performance improvement for the SU network over the existing opportunistic spectrum access scheme.

We study stable wireless link scheduling under the physical interference model in wireless networks. Given a set of elastic wireless communication requests arriving in an online fashion, the objective is to perform link scheduling to maximize the network throughput capacity. This well-motivated problem under an arbitrary physical interference model is notoriously hard. In this work, we develop efficient interference-aware scheduling protocols under different transmission power control settings, i.e., uniform power control and monotone power control. The novel proposed scheduling protocols can attain a provable efficiency ratio. The extensive simulations validates the proposed protocols under various environmental settings.

The IEEE 802.22 cognitive Wireless Regional Area Networks (WRAN) uses cognitive radio technique to allow Secondary Users (SUs) to opportunistically share the TV bands with TV broadcast service on a non-interfering basis and hence improve the spectrum utilization. WRAN employs Orthogonal Frequency Division Multiplexing (OFDM) technology for transmission and thus is sensitive to inter-carrier interference. So one of the challenging issues in WRAN performance analysis is the interference analysis from SUs. Existing research on interference primarily focuses on the co-channel interference. The study of inter-carrier interference in WRAN has not received considerable attention. In this paper, we design a new interference model for IEEE 802.22 cognitive WRAN that incorporates both the co-channel interference and inter-carrier interference. We first examine the interference in the context of one SU, and then study the aggregate interference in the context of multiple SUs. Existing work on studying the aggregate interference is to derive its probability density function, which is known computationally intensive. In this paper, we investigate the aggregate interference from a new perspective. Instead of deriving the probability density function, we calculate the aggregate interference by estimating the maximum number of interfering SUs. Our results suggest that the maximum number typically ranges from 6 to 10 depending on the network configurations. This finding significantly simplifies the interference estimation process. To verify the new interference model, comprehensive simulations are performed. Results confirm that the inter-carrier interference cannot be ignored especially when a high frequency offset is present. The maximum number of SUs and its effectiveness are also validated.

For wireless networks, coverage with different restrictions that can capture the practical requirements have received great research interests. We will study several restricted coverage problems. The first problem is aboutK-coverage, i.e., how to deploy wireless nodes such that each target is covered by at leastKwireless nodes. We study the problem restricted to linear-K-coverage where there is a line, all targets lie in one side of this line and all wireless nodes lie in the other side. Assume each wireless node is associated with a weight, the objective is to select a minimum weighted subset of nodes such that each target isK-covered. We propose a 3-approximation for this problem by exploring geometric properties. The second problem is calledK-road-coverage. Given a road map in a two-dimensional area which contains a set of paths and a set of wireless nodes, the locations of nodes can either be arbitrary or fixed, the objective is to select a minimum number of wireless nodes such that each path can beK-covered. We will reduce the problem toK-coverage and apply the algorithmic results forK-coverage to solve it. Another line of this work is to investigate a well-motivated problem called strongly dominating set, which is intrinsically related to coverage. Given a wireless networking system represented by a digraph G = (V, E⃗). Each wireless node u has a covering disk centering at u with its radius equal to the transmission range of u. We then draw a directed edge uv⃗ in G if u's corresponding covering disk contains v. A subset U ⊆ V of wireless nodes is a strongly dominating set if every wireless node in V \ U has both an in-neighbor in U and an out-neighbor in U. The objective is to find a minimum size strongly dominating set. Our method can achieve an approximation factor of (2 + ε).

Promising to significantly improve spectrum utilization, cognitive radio networks (CRNs) have attracted a great attention in the literature. Nevertheless, a new security threat known as the primary user emulation (PUE) attack raises a great challenge to CRNs. The PUE attack is unique to CRNs and can cause severe denial of service (DoS) to CRNs. In this paper, we propose a novel PUE detection system, termed Signal activity Pattern Acquisition and Reconstruction System. Different from current solutions of PUE detection, the proposed system does not need any a priori knowledge of primary users (PUs), and has no limitation on the type of PUs that are applicable. It acquires the activity pattern of a signal through spectrum sensing, such as the ON and OFF periods of the signal. Then it reconstructs the observed signal activity pattern through a reconstruction model. By examining the reconstruction error, the proposed system can smartly distinguish a signal activity pattern of a PU from a signal activity pattern of an attacker. Numerical results show that the proposed system has excellent performance in detecting PUE attacks.

Cognitive radio networks are a promising solution to the spectrum scarcity issue. In cognitive radio networks, because of the low reliability of individual spectrum sensing by a single secondary user, cooperative spectrum sensing is critical to accurately detect the existence of a primary user signal. However, cooperative spectrum sensing is vulnerable to the spectrum sensing data falsification (SSDF) attack. Specifically, a malicious user can send a falsified sensing report to mislead other (benign) secondary users to make an incorrect decision on the PU activity. Therefore, detecting the SSDF attack or identifying the malicious sensing reports is extremely important for robust cooperative spectrum sensing. This paper proposes a distributed density based SSDF detection (DBSD) scheme to countermeasure the SSDF attack. DBSD can effectively exclude the malicious sensing reports from SSDF attackers, so that a benign secondary user can effectively detect the PU activity in distributed cooperative spectrum sensing. Furthermore, DBSD can also exclude abnormal sensing reports from ill-functioned secondary users. Simulation results show that DBSD achieves very good performance in cooperative spectrum sensing.

We study real time periodic query scheduling for data collection in multihop Wireless Sensor Networks (WSNs). Given a set of heterogenous data collection queries in WSNs, each query requires the data from the source sensor nodes to be collected to the control center within a certain end-to-end delay. We first propose almost-tight necessary conditions for a set of different queries to be schedulable by a WSN. We then develop a family of efficient and effective data collection algorithms that can meet the real-time requirement under resource constraints by addressing three tightly coupled tasks: (1) routing tree construction for data collection, (2) link activity scheduling, and (3) packet-level scheduling. Our theoretical analysis for the schedulability of these algorithms show that they can achieve a constant fraction of the maximum schedulable load. For the case of overloaded networks where not all queries can be possibly satisfied, we propose an efficient approximation algorithm to select queries to maximize the total weight of selected schedulable queries. The simulations corroborate our theoretical analysis.

Cognitive radio is viewed as a disruptive technology innovation to improve spectrum efficiency. The deployment of coexisting cognitive radio networks, however, raises a great challenge to the medium access control (MAC) protocol design. While there have been many MAC protocols developed for cognitive radio networks, most of them have not considered the coexistence of cognitive radio networks, and thus do not provide a mechanism to ensure fair and efficient coexistence of cognitive radio networks. In this paper, we introduce a novel MAC protocol, termed fairness-oriented media access control (FMAC), to address the dynamic availability of channels and achieve fair and efficient coexistence of cognitive radio networks. Different from the existing MACs, FMAC utilizes a three-state spectrum sensing model to distinguish whether a busy channel is being used by a primary user or a secondary user from an adjacent cognitive radio network. As a result, secondary users from coexisting cognitive radio networks are able to share the channel together, and hence to achieve fair and efficient coexistence. We develop an analytical model using two-level Markov chain to analyze the performance of FMAC including throughput and fairness. Numerical results verify that FMAC is able to significantly improve the fairness of coexisting cognitive radio networks while maintaining a high throughput.

We study delay-efficient data aggregation scheduling in wireless sensor networks subject to signal to interference-plus-noise ratio (SINR) constraints. We construct a routing tree and propose two scheduling algorithms that can generate collision-free link schedules for data aggregation. We prove that the delay of each algorithm is O(R + Δ) time slots, where R and Δ are respectively the graph radius and the maximum node degree in a reduced communication graph of the original network; the proposed algorithms are asymptotically optimum on delay in random wireless sensor networks. We evaluate the performances of the proposed algorithms and the simulation results corroborate our theoretical analysis.

In many practical applications of wireless sensor networks, it is crucial to accomplish the localization of sensors within a given time bound. We find that the traditional definition of relative localization is inappropriate for evaluating its actual overhead in localization time. To address this issue, we define a novel problem called essential localization and present the first rigorous study on the essential localizability of a wireless sensor network within a given time bound. Additionally, we propose an efficient distributed algorithm for time-bounded essential localization over a sensor network and evaluate the performance of the algorithm with analysis and extensive simulation studies.

The existing dynamic spectrum access network architecture fails to offer incentives to primary users (PUs). Therefore, PUs are unwilling to cooperate with secondary users (SUs) and intend to set up stringent requirements on SUs' spectrum access. This diminishes the benefit of dynamic spectrum access and hinders its commercialization success. In this paper, we propose a novel architecture for dynamic spectrum access networks, termed incentivized cooperative dynamic spectrum access network (IC-DSAN), to motivate PUs to cooperate with SUs, such that both PUs and SUs achieve significantly higher performance. In an IC-DSAN, SU nodes serve as relays between PU nodes and while relaying PU packets, utilize network coding to encode SU packets onto PU packets, i.e., SU packets get a `free ride' via network coding. To further improve the performance, we propose a new network coding scheme termed coding over coded packets. At last, an optimization model is developed to analyze the throughput gain of IC-DSAN. The performance evaluation indicates that the throughputs of both PUs and SUs significantly increase.

In cognitive radio networks, cooperative spectrum sensing is critical for secondary users to accurately detect primary users. However, it is vulnerable to attacks from malicious users, which intentionally report incorrect sensing results, to mislead other secondary users or the fusion center in decision making. Therefore, detection of malicious users is extremely important for spectrum sensing. This paper proposes a decentralized scheme to detect malicious users in cooperative spectrum sensing. The scheme utilizes spatial correlation of received signal strengths among secondary users in close proximity and is based on robust outlier-detection technique. We have also proposed a neighborhood majority voting approach for the secondary users to decide if a specific user is malicious. Simulation results show that the proposed scheme can achieve a very good performance in detecting malicious users.

Recently there have been various studies on dynamic spectrum access (DSA) approaches, e.g., opportunistic spectrum access and spectrum auction, to address spectrum scarcity and inefficient spectrum utilization caused by today's static spectrum allocation policy. In this paper, we propose a new approach, demand spectrum access as a service (DSAS), to achieve DSA. We consider a spectrum service provider that dynamically offers spectrum service to users such that the users can set up dynamic topologies for data communication, e.g., transport a bulk data flow between two nodes, or carry out a video conference among a set of nodes. Through DSAS, the precious spectrum is dynamically shared and efficiently utilized by users. In this paper, we consider two spectrum services, SameBand and DiffBand, and develop efficient online algorithms to allocate spectrum for the two services, so that users can set up dynamic topologies. The performance of the algorithms is evaluated through both analysis and simulation.

Spectrum sensing plays a critical role in cognitive radio networks (CRNs). The majority of spectrum sensing algorithms aim to detect the existence of a signal on a channel, i.e., they classify a channel into either busy or idle state, referred to as a two-state sensing model in this paper. While this model works properly when there is only one CRN accessing a channel, it significantly limits the potential and fairness of spectrum access when there are multiple co-existing CRNs. This is because if the secondary users (SUs) from one CRN are accessing a channel, SUs from other CRNs would detect the channel as busy and hence be starved. In this paper, we propose a three-state sensing model that distinguishes the channel into three states: idle, occupied by a primary user, or occupied by a secondary user. This model effectively addresses the fairness concern of the two-state sensing model, and resolves the starvation problem of multiple co-existing CRNs. To accurately detect each state of the three, we develop a two-stage detection procedure. In the first stage, energy detection is employed to identify whether a channel is idle or occupied. If the channel is occupied, the received signal is further analyzed at the second stage to determine whether the signal originates from a primary user or an SU. For the second stage, we design a statistical model and use it for distance estimation. For detection performance, false alarm and miss detection probabilities are theoretically analyzed. Furthermore, we thoroughly analyze the performance of throughput and fairness for the three-state sensing model compared with the two-state sensing model. In terms of fairness, we define a novel performance metric called all-level fairness for all(ALFA) to characterize fairness among CRNs. Extensive simulations are carried out under various scenarios to evaluate the three-state sensing model and verify the aforementioned theoretical analysis.

In this paper, we propose a systematic approach to designing and deploying a RFID Assisted Navigation System (RFID-ANS) for VANETs. RFID-ANS consists of passive tags deployed on roads to provide navigation information while the RFID readers attached to the center of the vehicle bumper query the tag when passing by to obtain the data for navigation guidance. We analyze the design criteria of RFID-ANS and present the design of the RFID reader in detail to support vehicles at high speeds. We also jointly consider the scheduling of the read attempts and the deployment of RFID tags based on the navigation requirements to support seamless navigations. The estimation of the vehicle position and its accuracy are also investigated.

Covert channel is used to secretly transfer information. In covert timing channels, all messages are decoded based on the arrival time of packets at the receiver side. In covert communications, synchronization between the sender and receiver plays a key role in decoding accuracy. Lost, duplicated, and out-of-order arrived packets may cause the loss of synchronization between the sender and receiver. In this study, a synchronization scheme, which is based on Phase Lock Loop (PLL), is proposed to build an effective covert timing channel. The scheme is software based and implemented in the transport layer. This is the first effort of using PLL for building a covert channel. Simulation results show that the scheme can achieve high decoding rate. Moreover, the covert timing channel built by the scheme is not affected by packet loss, duplication, and out-of-order arrival.

In this paper, we present a rendezvous scheme for dynamic spectrum access (DSA) networks that can achieve approximately optimal throughput while not relying on a common control channel. Compared with existing rendezvous schemes for DSA networks that use a common control channel, the proposed scheme avoids congestion and jamming of the control channel, and also reduces control complexity and overhead in DSA. We prove that the proposed rendezvous scheme achieves approximately optimal throughput, and analyze the convergence time of this scheme to obtain the approximately optimal throughput.

Multihop wireless mesh networks have potential to meet the growing demand for flexible, self-organizing, large-scale wireless communication systems. However, these networks remain plagued by relatively poor performance compared to traditional infrastructure based networks. With variable number of nodes and diverse network densities, multihop wireless mesh networks can have low overall network capacity, poor internode fairness and high power consumption. Therefore, we present the decentralized Traffic Aware Iterative Water filling (TAIW) power allocation algorithm. TAIW applies techniques from non-cooperative game theory applied to cognitive radio devices to develop a solution that balances network capacity, node fairness and power consumption. Through extensive simulations we show the TAIW can increase inter-node fairness by 300% and reduce power consumption by 80% over current decentralized power allocation algorithms while maintaining near optimal network capacity.

A vast number of broadcasting protocols have been developed for wireless networks. However, most of these protocols assume a single-radio single-channel network model. Employing multiple channels can effectively improve the network capacity in wireless mesh networks. This paper considers minimum cost broadcast (MCB) problem in multi-radio multi-channel wireless mesh networks. We first present the multi-radio multi-channel network model, and then formulate the MCB problem using an integer linear programming model. Our model considers two cases of MCB. In the first case, there already exists a channel assignment in the network, and the formulation minimizes the broadcast cost and reduces interference amongst the adjacent neighbors. In the second case, each node has a set of available channels to be selected. We jointly consider channel assignment and the MCB problem. The joint channel assignment and MCB formulation fully exploits the channel diversity, and also further reduces interference in the network. We propose corresponding centralized and distributed heuristic algorithms to minimize the number of broadcast transmissions with full reliability. In our heuristic algorithms, each node participates in the broadcasting if chosen to maintain the network connectivity or to achieve maximum coverage. Extensive numerical results are presented to demonstrate the performance.

Cognitive radio networking is emerging as a promising paradigm for future wireless networks. In this paper, the delay performance of cognitive radio networks supporting heterogeneous traffic is analyzed. In order to guarantee primary users' (PUs) licensed membership, packets from PUs are distinguished from secondary users (SUs) by employing an absolute priority scheme. Meanwhile, various delay requirements over the packets from SUs are fully considered. The packets from SUs are classified into either delay-sensitive packets or delay-insensitive packets. Moreover, a novel relative priority strategy is designed between these two types of traffic by proposing a “transmission window” strategy. The delay performance of both a single-PU scenario and a multiple-PU scenario is thoroughly investigated employing queueing theory. In the multiple-PU scenario, a dynamic and adaptive channel selection scheme based on learning automata is developed with the objective of reducing the average delay for all SU packets. Numerical experiments are conducted and the results demonstrate the delay performance with respect to varied transmission window sizes. The results in the multiple-PU scenario verify that the proposed learning automata channel selection scheme significantly improves the delay performance of SU packets.

In dynamic spectrum access (DSA), secondary users (SUs) dynamically search and access spectrum bands unused by primary users to communicate. We propose a DSA scheme where it does not require a control channel for coordination and SU nodes do not need to exchange control messages to rendezvous. Every SU node selects its operational channel independently. When a node wants to rendezvous with another node, the former estimates the operational channel of the latter. The scheme ensures that such rendezvous has a high probability of success, while operational channels are diversified to reduce co-channel interference and hence increase throughput. We develop a mathematical model to analyze the performance of the scheme. Both analytical and simulation results show that the scheme achieves very good performance.

The dynamic spectrum access (DSA) capability of cognitive radio networks (CRN) promises to resolve both the spectrum scarcity and the low spectrum utilization problems caused by today's static spectrum access (SSA) policy. With DSA, CRN nodes search the dynamically accessible spectrum bands for communication. In this paper, we study a random DSA scheme, where each node randomly selects its operating band based on the locally detected accessible spectrum bands. This scheme does not need the coordination or exchange of control messages to select a communication band between a sender and a receiver, and is desirable in certain scenarios. We analyze the performance of this random DSA scheme. Numerical results show that the random DSA scheme can achieve 60% of the theoretical maximum performance.

Dynamic spectrum access (DSA) promises to resolve spectrum scarcity and low spectrum utilization caused by today's static spectrum access (SSA) policy. In DSA, secondary users dynamically search and access spectrum bands that are temporarily unused by primary users. In this paper, we propose a control-free DSA algorithm for cognitive radio networks (CRN). Our algorithm enables each CRN node to select its operation band without coordination and exchange of control messages with neighbors. The contribution of our algorithm is that such an independently selected band can reach neighbors with high probability, while streamlining control complexity and overhead in DSA. We develop an analytical model to evaluate performance. Numerical results show that our control-free DSA algorithm can achieve very good performance.

In many practical applications of wireless sensor networks, it is crucial to accomplish the localization of sensors within a given time bound. We find that the traditional definition of relative localization is inappropriate for evaluating its actual overhead. To address this problem, we define a novel problem called essential localization, and present the first rigorous study on the essential localizability of a wireless sensor network within a given time bound. We propose an efficient distributed algorithm for time-bounded essential localization over a sensor network, and evaluate the performance of our algorithm with extensive simulations.

Wireless mesh networks (WMNs) have recently emerged as a promising broadband access infrastructure for next-generation wireless networking. Several approaches that exploit directional antennas have been proposed in the literature to increase the performance of WMNs. In this paper, we study the interference optimization multicast problem in WMNs where nodes are equipped with directional antennas. Interference can make a significant impact on the performance of multi-hop wireless networks. Directional transmissions can greatly reduce radio interference, increase spatial reuse, and enable more efficient MAC designs. We first present the definition of interference with directional transmissions that are suitable for designing multicast algorithms, and formulate minimum interference multicast problems using a linear programming model. We then propose a heuristic algorithm to solve the problem. Our model and algorithm are good for both single multicast session and multiple multicast sessions. Multicast routing found by our interference-aware algorithm tends to have less channel collisions.

Abstract One of the most challenging security concerns for network administrators is the presence of rogue access points (RAPs). The challenge is to detect and disable a RAP before it poses a serious security risk. In this paper, we propose a statistical based approach to detect RAPs using a Hidden Markov Model (HMM), which is applied to passively measure packet‐header data collected at a gateway router. The main idea is to process the sequence of packet traces in order to distinguish the normal packets from the abnormal ones. Our approach utilizes variations in packet inter‐arrival time to differentiate between authorized access points and RAPs. We used the inter‐arrival time of a packet as a distinguishing parameter because it varies drastically for a normal activity and an intrusive activity. We developed our HMM by analyzing Denial of Service (DoS) attacks of 802.11 based wireless local area networks. Our trained HMM can detect the presence of a RAP promptly within a second with extreme accuracy (very low false positive and false negative ratios are obtained). The success of our approach lies in the fact that it leverages knowledge about the behavior of the traffic characteristics of 802.11 based wireless local area networks and the properties of DoS attacks. Experiments were also performed to improve the accuracy of our HMM model. Our approach is scalable and non‐intrusive, requiring little deployment cost and effort, and is easy to manage and maintain. Copyright © 2010 John Wiley & Sons, Ltd.

In this paper we present throughput analysis for a contention-based dynamic spectrum sharing model. We consider two scenarios of allocating channels to primary users, fixed allocation and random allocation. In fixed allocation, the number of primary users allocated to a channel is fixed all the time, but the number of users in different channels may be different. In random allocation, each primary user dynamically and randomly selects a channel in each time slot. We assume that the spectrum band of primary users is divided into multiple channels and the time is slotted. Primary users allocated to a specific channel compete to access this channel in each time slot. Secondary users are able to dynamically detect the idle channels in each time slot, and compete to access these channels. We develop analytical models for the throughput of primary users and secondary users in both scenarios and examine the impact of the number of secondary users on the throughput of the system. For a given number of primary users, channels and traffic generation probability, we aim to find the number of secondary users to maximize the total throughput of both primary users and secondary users. Our solutions match closely with the numerical results.

Achieving efficient bandwidth utilization in multi-channel sensor networks is a challenging research problem. In this paper, we present a cognitive load balance algorithm for single-hop multi-channel sensor networks. Based on the load distribution of all base stations, our algorithm dynamically alternates the communication channels. As a result, the extra load from over-loaded channels is directed to under-loaded channels with a computed switch probability. In this paper, we also prove that a high throughput can be achieved if the load is balanced. The performance of the load balance algorithm is evaluated through both theoretical analysis and simulation study.

Opportunistic spectrum access presents a new approach to wireless spectrum utilization and management. In this paper, we propose a non-cooperative based OSA approach: learning-based approach to allow multiple secondary users to achieve maximal throughput in an unslotted opportunistic spectrum access (OSA) network. In this approach, collisions among secondary users are taken into consideration while making channel sensing decisions. Spectrum maps for secondary users are estimated based on occurrence of collisions. Our approach allows secondary users to achieve maximal throughput by seeking independent spectrum opportunities without exchanging any control information among secondary users. Numerical results show that the learning-based approach obtains near-optimal performance in most of the scenarios.

This paper introduces a high-performance vehicle detection algorithm for a parking management system based on wireless sensor technology. The parking lot is represented as a wireless sensor network cluster modeled as an m × n grid in a rectangle of size I × h. A wireless sensor node is deployed in each grid and one gateway is set for the cluster. The status of each parking space is detected by a sensor node and the result is reported to the gateway. To reduce the false positive rate caused by various sources of interference, we developed a high-performance vehicle detection algorithm to filter out the noises from the passing-by cars and the environment. The performance of the algorithm is verified through extensive simulation. The three scenarios of low, medium and high interference levels are simulated. Results suggest that our proposed vehicle detection algorithm can effectively detect the status of parking lot with zero false positive rate at the low and medium interference levels, and 3.3% at high interference level.

Time synchronization is a key component in numerous wireless sensor network applications. Most of the current software based time synchronization approaches suffer from communication overhead and lack of scalability. In this paper, we propose a hardware based approach based on voltage controlled crystal oscillator and phase locked loop techniques to achieve and maintain sub microsecond level time synchronization. Our approach does not require any exchange of synchronization messages with neighboring nodes. Performance evaluations in Matlab demonstrate sub microsecond accuracy and robustness to infrequent loss of WWVB signal. The principle advantages of our solution is scalability, accuracy, and low communication overhead.

A vast number of broadcasting protocols have been developed for wireless networks. To the best of our knowledge, however, most of these protocols assume a single-radio single channel network model and/or a generalized physical model, which does not take into account the impact of interference. In this paper, we present a Distributed Interference-aware Broadcasting (DIB) protocol for multi-radio multi-channel mesh networks. The protocol has two phases. In the first phase, each node constructs a local structure by removing bad links and channels. In the second phase, a high-performance broadcasting tree is built by using message passing procedures. Our research distinguishes itself in a number of ways. First, a multi-radio multi-channel mesh network model is used. Second, comprehensive link and channel quality metrics are defined to fully take into account interferences. Third, four design principles have been identified in the tree building process to combat inter-node and intra-node interferences. Finally, a comprehensive performance metric, called power, is defined which includes reliability, receiving redundancy, latency, and goodput. Analytical and simulation studies verify that the DIB protocol is able to achieve 100% reliability, less broadcasting redundancy, low broadcasting latency, and high goodput.

A vast amount of broadcasting protocols has been developed for wireless ad hoc networks. To the best of our knowledge, however, these protocols assume a single-radio single-channel and single-rate network model and/or a generalized physical model, which does not take into account the impact of interference. In this paper, we present a set of broadcasting protocols to simultaneously achieve 100% reliability, minimum broadcasting latency, and minimum redundant transmissions. Our research distinguishes itself in a number of ways. First, a multi-radio multi-channel and multi-rate mesh network model is used. Second, the broadcasting tree is constructed by using local information without the global network topological information. Third, a comprehensive link quality metric is defined to fully take into account the interference. The link quality information is also made available to broadcasting protocols. Fourth, three performance metrics that include reliability, latency, and redundancy are simultaneously considered. Simulations are conducted to evaluate the proposed protocols and compare the performance improvement to other protocols.

IEEE 802.11b Wireless Local Area Networks (WLAN) and Bluetooth Wireless Personal Area Networks (WPAN) provide complimentary services using the same unlicensed radio frequency band of operation. As the benefits of utilizing these services become increasingly apparent, the likelihood of mutual interference may also increase. In this paper an algorithm called Interference-Aware Adaptive Frequency Hopping (IAFH) is proposed and implemented on Bluetooth devices to mitigate the interference between WLAN and WPAN. An analytical channel model of IAFH based on the standard path loss-log normal shadowing-AWGN and Rayleigh multi-path fading channel model is developed to evaluate the performance of the 802.11b devices in the presence of Bluetooth devices. Numerical analysis of the model is done in MATLAB to calculate the throughput of the system using the existing algorithms and the proposed algorithm and the results are compared.

We first give a comprehensive taxonomy of rouge access points (APs), which includes a new class of rouge APs never addressed in the literature before. Then, we propose an efficient rogue AP protection system termed as RAP for commodity Wi-Fi networks. In RAP, novel techniques are introduced to detect rouge APs and to improve network resilience. Our system has the following nice properties: i) it requires neither specialized hardware nor modification to existing standards; ii) the proposed mechanism can be integrated with an AP in a plugin manner; iii) it provides a cost-effective security enhancement to Wi-Fi networks by incorporating free but mature software tools; iv) it can protect the network from adversaries capable of using customized equipment and violating the IEEE 802.11 standard.

The hop distance based routing protocol (HDR) is an on-demand based routing protocol suited for mobile ad hoc networks integrated with wired networks. HDR considers an efficient way to build multi-hop routes with low routing overhead, through efficient route discovery and route maintenance mechanisms. HDR does this by utilizing the hop count information between mobile nodes and access points to localize the route discovery and maintenance within a limited area in order to reduce routing overhead. HDR is an adaptive protocol and does not require any user or network dependent predefined inputs in order to operate. Simulation results show that HDR is highly efficient in reducing node participation and overhead in route request operations.

One of the notoriously difficult problems in quality of service (QoS) routing in mobile ad-hoc networks (MANET) is to ensure that the established path for a connection does not break before the end of the data transmission. This paper addresses the issue of reducing path breakage during data transmission, even if geographic location information is not available. Using delay-constrained QoS routing as an example, we propose a novel algorithm that we call ticket-based probing with stability estimation (TBP-SE) as an enhancement for the multi-path distributed QoS routing scheme proposed in Chen, S et al. (1999). Models are created to estimate relative link and path stability. During path discovery, the estimated relative stability is used to direct tickets along paths featuring high stability. Among multiple detected paths, the one with the highest relative stability is selected. Through extensive simulations, we show that our algorithm significantly improves the stability of established paths in terms of average relative path stability, path breakage speed, and percentage of data transmissions completed before path breakage

Fault tolerant algorithms are often designed under the t-out-of-n assumption, which is based on the assumption that all processes or components fail independently with equal probability. However, real systems may exhibit dependent failures. Cores and survivor sets are used to build an abstraction model for dependent process failures. Using this abstraction, we design an algorithm to solve consensus problem crash failures. Our algorithm uses the processes in all cores to broadcast messages. Each core reaches agreement separately and even simultaneously in some round with no failure in the core. In the worst-case, the decision can be made in the round that is equal to the size of the minimal core. Our algorithm guarantees that all processes eventually decide on the same value regardless the initial values. We prove the correctness of our algorithm and give the lower bound of the number of rounds to solve consensus problem.

To support the exponentially increasing demand with quality of service (QoS) requirements, input queued switches show great promise. Scheduling algorithms for input-queued switches must provide high throughput, individual flow QoS guarantee; and high network utilization. Most existing algorithms cannot satisfy the above three tasks. Based on a well-known scheduler, longest port first (LPF), this paper presents two algorithms, (i) worst-case LPF (WLPF), and (ii) prioritized LPF (PLPF), that support voice traffic QoS under the bursty and hot-spot traffic stream. Simulation results are presented that show that both of them improve the voice traffic QoS.