The escalating demand for real-time applications such as cloud gaming and virtual reality presents unique challenges in managing network latency and throughput simultaneously. Traditional congestion control mechanisms, which primarily rely on packet loss as a signal, are inadequate for modern applications requiring high throughput and ultra-low latency. This paper introduces a pluggable implementation of the Low Latency, Low Loss, Scalable throughput (L4S) architecture using eBPF (extended Berkeley Packet Filter) programs to enhance the Explicit Congestion Notification (ECN) mechanism. We specifically focus on replicating the L4S client functionality at the receiver end, which is crucial for the Accurate ECN (AccECN) protocol. By leveraging sched_cls eBPF programs, our design captures and manipulates packet flows at both ingress and egress points, enabling precise congestion feedback and efficient protocol negotiation directly from the data plane. Our approach ensures compatibility with existing network infrastructures and extends L4S benefits to devices operating on legacy kernels. The paper evaluates the implications of this design on network performance, particularly its ability to reduce latency and handle high throughput demands seamlessly. Through this innovation, we aim to accelerate the adoption of L4S across varied network environments, enhancing the quality of experience for latency-sensitive applications without extensive system overhauls.

TLS fingerprinting aids network operators to identify TLS clients running on the hosts communicating to their network. This helps them to identify vulnerable clients which could pose a security threat to their network in the future as they might have an underlying outdated TLS library. This information can be used by them to block or redirect the traffic. Existing software approaches cannot keep up with highspeed networks. This paper presents a P4-based programmable data plane implementation of TLS fingerprinting, based on JA3 scheme, and referred to as P4-TLSfp. P4-TLSfp runs on Tofino switches at line rate to perform fingerprinting and is used to identify the security profile of the clients. Experiments on packets collected from TLS/SSL clients running inside a campus network were conducted. The experimental results show that P4-TLSfp takes approximately 783 ns on the Intel Tofino switch translating to a throughput of$\mathbf{1. 3 2}$Mpps, whereas the JA3, implemented on server, takes approximately$300 \mu \mathrm{s}$.

This paper proposes a Generative AI-based Digital Twin (GDT) platform for automated network feature performance evaluation, designed for Beyond 5G (B5G) networks. The platform addresses the inefficiencies of manual evaluation by utilizing a conditional Generative Adversarial Network (cGAN) to simulate network performance based on historical data and new AI/ML features. The Network GDT integrates a novel Digital Twin Augmenting Condition (DTAC) framework, allowing for real-time simulation and performance evaluation of network features. This system significantly reduces the time and cost associated with manual evaluations, improves decision-making, and optimizes Quality of Service (QoS) and Quality of Experience (QoE). The cGAN-based model dynamically generates synthetic data, enabling comprehensive performance insights and proactive AI solution testing under various network scenarios. Experimental results demonstrate high prediction accuracy for congestion use case, validating the robustness of the proposed system. The platform's dual-phase strategy ensures that AI-based solutions are rigorously tested in simulated environments before deployment in real networks, minimizing risks and enhancing stability. This approach provides a scalable and efficient solution for future B5G networks, paving the way for more reliable and optimized wireless communication systems.

This paper studies auto-scaling of network function instances in a 5G Core network system based on Network Function Virtualization (NFV). Auto-scaling techniques have become essential for handling diverse traffic types while maintaining high Quality of Service (QoS). Scaling refers to the dynamic process of adjusting computational resources, either by increasing or decreasing them, to accommodate varying traffic loads. This paper introduces a hybrid reactive and proactive scaling mechanism. Proactive scaling minimizes Service Level Agreement (SLA) violations for infrastructure providers (IPs), while reactive scaling acts as a safeguard against forecast errors. We evaluate the proposed technique using the discrete event simulator SimPy, and Mininet emulation. Extensive numerical studies under dynamic traffic conditions modeled by a finite Markov chain demonstrate that our approach achieves a latency reduction of 92 % compared to the baseline non-scaling system, and at least$\mathbf{4 6 \%}$reduction compared to existing schemes.

Multi-access Edge Computing (MEC) and Vehicular-Fogs (VFs) are placed nearer to user equipment (UE), reducing propagation latency compared to traditional cloud-based systems and ensuring a high standard of Quality of Service (QoS). Nevertheless, MEC sites can become congested and overloaded during peak traffic periods, such as concerts or sporting events. To address this, offloading techniques can shift intensive computational tasks from devices with limited resources to those with greater capacity, enhancing task performance and thereby increasing battery longevity. This study investigates the offloading within a two-tier framework of MEC and VF, focusing on the offloading of MEC to VF. Maintaining QoS is challenging due to the instability of fog networks caused by high-speed vehicle movement, which disrupts both vehicle-to-vehicle and vehicle-to-infrastructure communications. To mitigate this, we analyze vehicle mobility using a Gauss-Markov Mobility (GMM) model. Our main goal is to reduce the average system cost by optimizing both latency and energy consumption while accounting for vehicle mobility. We approach this challenge as a multi-objective optimization problem and develop a reinforcement learning environment. Additionally, we propose an algorithm based on imitation learning called Weighted-Ratio Based TD3 (WRTD3), an enhancement of the TD3 algorithm, to effectively manage these complexities.

Packet schedulers enable Programmable Data-plane (PDP) switches to schedule packets correctly according to their priority. Existing PDP implementations do not support priority-based scheduling mechanisms required by scheduling policies. Push-in First-out (PIFO) offers a priority queuing abstraction; however, it faces scalability challenges due to the need for packet sorting at line-rate. To address this, approximate schedulers trade scheduling accuracy for implementation simplicity, but suffer from priority inversions. This paper presents Parallel Processing for Priority Ordering (P3PO) architecture, which partitions a global priority queue into multiple smaller, independently sorted queues that operate concurrently. P3PO is implemented using the NetBench simulator, and its performance (FCTs, delays, packet drops) is measured for in-cast traffic patterns. P3PO has FCTs close to PIFO and performs 14-62% better compared to existing approaches for small-sized flows and 47-60% better for large-sized flows. P3PO also reduces the packet drops in the network by 66-95% across different flow sizes.

The increasing demand for low-latency, highthroughput packet processing has driven the exploration of programmable dataplane technologies such as P4 and eBPF/XDP. This paper evaluates the suitability of integrating P4 and XDP, which combines the flexible programmability of P4 running on a programmable data plane switch's pipeline and the expedited processing capabilities of Generic XDP running on the kernel of the hardware switch's CPU. The framework is implemented on the Tofino-1 switch for three different applications: forwarding, filtering and monitoring. The results show that P4+XDP performs similar to P4 in the simple forwarding application, but improves performance in filtering application, such as handling anomaly packets separately. This is attributed to XDP's kernel-bypass capabilities and proximity to the deparser in the Tofino-1 switch, enabling low-latency packet filtering. The studies also show that P4+XDP enhances packet processing by achieving an average latency reduction of 35 %, with values as low as 40 nanoseconds. It provides over 98% packet delivery due to its enhanced processing capability.

The surging popularity of mobile gaming has underscored the need for optimal performance in Real-Time Online Mobile Gaming (RT OMG). However, the concurrent Non-Real-Time (NRT) activities, such as downloads, can often compete with the RT OMG traffic, depriving the users of a seamless gaming experience. This paper presents a study on the drawbacks of using the app bitrate to quantify the RT OMG Quality of Experience (QoE). We propose the Game Stabilizer, a novel machine learning-driven solution to enhance the RT OMG experience. The Game Stabilizer effectively utilizes Wi-Fi network condition information and an End-to-End bandwidth estimate of the link to intelligently manage the NRT bandwidth, giving the users a consistent gameplay experience. Our proposed solution demonstrates promising results, notably reducing latency in the Smartphone gaming experience by up to 60%. This advancement holds significant promise for elevating the overall mobile gaming landscape.

Mesh networks enables quick on-demand infrastructure creation and help achieve vital last-mile connectivity. Wi-Fi integration can further enhance the potential and compatibility for the pervasive connectivity requirements in next-generation applications. Despite advancements, Wi-Fi standards still need efforts to meet long-range requirements. Accordingly, this paper proposes a customized handheld platform named WiLong for constructing long-range Wi-Fi Mesh networks in the unlicensed higher bands, 2.4 and 5 GHz. The proposed platform can offer versatile radio profiles by leveraging commercially available hardware and open-source software components, augmented with the addition of IEEE 802.11s mesh link and the B.A.T.M.A.N. advanced routing protocol. Experimental evaluations of the said platform have been conducted across various practical environments, including indoor/outdoor spaces, urban & open bay areas, multi-floor basement car parking, and dense mesh deployments. The experimental results underscore the effectiveness of the WiLong platform in improving long-range Wi-Fi performance while emphasizing the significance of multi-hop networking in demanding ground-to-ground scenarios. These findings highlight the platform’s robustness and versatility. In a selected urban route scenario, the WiLong platform achieved 80% voice and 63% video call bandwidth. Additionally, when configured with 2.4 GHz, the platform reached two floors below in a multi-floor basement car parking.

In the rapidly advancing domain of 5G communication systems, channel decoding, particularly turbo decoding, has emerged as a significantly complex challenge. Turbo decoding is an essential element within communication frameworks, necessitating both efficiency and rapid processing to cater to the demanding data rates and stringent low latency requirements of 5G networks. This paper focuses on the unique contributions of employing a Sparse Recurrent Neural Network (SRNN) architecture, leveraging sparsity to reduce computational load while maintaining high performance significantly. Unlike existing approaches, our method introduces a novel piece-wise linear approximation of the activation function, enhancing efficiency and scalability for NextGen communication systems. Our approach leverages the principles of sparsity and employs a piece-wise linear approximation of the activation function to markedly reduce the computational load of the turbo-decoding process.Comprehensive evaluations demonstrate that our RNN architecture outperforms existing deep learning models in the context of turbo decoding and with a significantly lower computational footprint. This research contributes to the field by providing a scalable, efficient, and less computationally intensive turbo-decoding method, particularly suited for the next-generation cloud systems underlying 5G and beyond communication technologies.

In IEEE 802.11-based access networks (Wi-Fi), the client remains connected to a far-poor Access Point (AP) rather than switching to a near-better AP. This scenario is termed a sticky client problem. This scenario can severely impact the performance of real-time applications. Several standards, such as 802.11k1v/r, are being developed to enhance Wi-Fi roaming capabilities. However, the sticky client problem is yet to be solved completely. This paper proposes Sticky less, a novel method that leverages machine learning to learn the home Wi-Fi network behavior to address the sticky client problem. Initially, Stickyless divides the deployment area of APs into distinct zones, generates training data, and subsequently trains the machine learning module. The Stickyless employs clustering models to recommend selecting the optimal AP within a specific zone by considering the application performance and quality metrics. To conclude, Stickyless assesses performance using a proposed scoring and cascading module. We also developed a prototype to evaluate the Stickyless performance, outperforming the existing methods. The proposed method improves the Wi-Fi roaming experience by reducing stickiness up to 40 %. Thereby, it improves the link quality of the client by an average of 19 % and decreases the packet error rate by up to 3.5 % compared to the existing approaches. We also experimented with popular gaming apps, and Stickyless reduced the latency by up to 7 -fold.

Smartphone consumers use various applications (apps), including online gaming, chat, streaming, video calling, and social networking. The smartphone relies on the network backhaul, such as a Wi-Fi access point, to provide the required Quality of Service (QoS). In its send-and-receive queues, the smartphone processes the packets in a first-in-first-out (FIFO) fashion. Many people worldwide started using video calling apps daily during the pandemic and post-pandemic periods. On the other hand, online gaming apps skyrocketed and continue to engage people. When real-time (RT) video calling and gaming apps race with non-real-time (NRT) traffic, we found a severe degradation in the Quality of Experience (QoE). In this work, we propose an Application Prioritization Engine (APE) framework that will improve user experience by dynamically allocating bandwidth to the different apps in the smartphone. APE helps improve the end-user experience by detecting and prioritizing real-time traffic over concurrent best-effort traffic. We introduced an eBPF (extended Berkeley Packet filter) that can control the NRT traffic to the extent that it does not affect the RT traffic. We evaluate the performance of APE with the top-chart video calling and gaming apps in a live-air scenario. APE enhances video calling performance in poor network conditions by improving the bit rate to 110%. Furthermore, it provides a four-fold gaming latency reduction despite NRT traffic. APE is a tech-transferred, app-agnostic, server-independent solution enabled in the latest Samsung flagship Smartphones with Android 13 OS.

This paper deals with programmable data plane switches that perform flow classification using machine learning (ML) algorithms. This paper describes the implementation-based study of an existing ML-based packet marking scheme called FlowLens. The core algorithm, written in the P4 language, generates features, called flow markers, while processing packets. These flow markers are an efficient formulation of the packet length distribution of a particular flow. Secondly, a controller responsible for configuring the switch, extracting the features periodically, and applying machine learning algorithms for flow classification, is implemented in Python. The generation of flow markers is evaluated using flows in a tree-based topology in Mininet using the P4-enab1ed BMv2 packet switch on the mininet emulator. Classification is performed for the detection of two different types of network attacks: Active Wiretap and Mirai Botnet. In both cases, we obtain a 30-fold reduction in memory footprint with no loss in accuracy demonstrating the potential of running P4-based ML algorithms in packet switches.

This paper deals with network slicing in 5G networks, where a slice is defined as a set of virtual network function (VNF) instances that collaborate to create an end-toend (E2E) virtual network. A set of slices is implemented on a physical substrate network maintained by an infrastructure provider. The virtual network embedding (VNE) problem deals with the deployment of a network slice’s virtual network request on the substrate. Typically, the resources allocated per slice’s request are not shared with other slices due to privacy, security and performance considerations. However, there are situations in which VNF instances might be aggregated across many slices to further increase the utilization ratio of the substrate infrastructure. Given these shareable VNF nodes, deploying the network slices is effectively the embedding of the numerous virtual network where these slices are linked by the shared VNFs. This paper uses a reinforcement learning (RL) approach for the embedding problem. The approach incorporates sharing based virtual network functions in an existing RL scheme designed for virtual node embedding without much additional computation. The proposed scheme is implemented using a policy based RL method; the performance study shows an increase in the reward ratio by up to 20% compared to the non-sharing case, along with an increase in the acceptance percentage of slices.

This article proposes a secure in-network computing system based on a simple reduced instruction set architecture, which can be used for processing artificial intelligence and machine learning models in network devices, in an AI-based Industrial Internet of Things (IoT) system. The architecture exploits the capabilities of upcoming generations of packet processing pipelines in programmable network switches. This instruction set enables processing of data at multiple terabits-per-second, which is beyond the processing power of current servers. Instructions for regular expressions, basic arithmetic, and logical operations are defined as a proof of concept. A packet containing both instruction and data blocks is presented as an input to the pipeline by bundling both the function and its arguments into the packet. The primary challenge in opening up network switches for executing a user-defined code is security. In this context, this article presents a secure execution model (SEM), which provides additional levels of security by deliberately disallowing memory allocation and modifications to persistent state of the network switch. Furthermore, real-life use cases are presented in this article to demonstrate the utility of the proposed instruction set architecture, as also applicable to IoT data processing. This instruction set is implemented in the programming protocol-independent packet processors language, verified on a mininet-based software switch and demonstrated on Xilinx NetFPGA SUME boards. The performance results show line rate packet processing with zero packet loss, at 10 Gb/s, and average packet latency of 3.66${\mu }\text{s}$.

Network Slicing (NS) provides a new business model to the Infrastructure Providers (InP), where multiple tenants request the InP to provide services to its customers. InP decides whether to accept the request or not to maximize the overall profit due to resource limitation. It is generally seen that tenants over-estimate their slices’ maximum requirements. In particular, for elastic slices that have flexible resource requirements, we use the concept of overbooking. Here, we accept slices above actual resource availability. We present a Slice Admission architecture where, a Slice Forecasting Agent (SFA) predicts the future resource (CPU, Memory, Bandwidth) usage of currently active elastic slices for next time window. This predicted information is used by an opportunistic overbooking heuristic, where the system allocates the required resources to each slice. After this, we address the admission control problem using a reinforcement learning (RL) approach that decides to accept/reject an incoming slice request. The performance of our proposed work is compared against three other heuristics (Basic, Prediction, Prediction-RL) that do not use overbooking. Data traces from the Materna data center network were used for prediction. The results show that the proposed work significantly outperforms the other mechanisms in terms of revenue gain and resource utilization.

This article deals with providing privacy-preserving access control in Internet of Things (IoT) systems. Here, a user/IoT device requests access to services provided by other IoT devices and multiple requests are combined to a request-specific service chain. An anonymous delegated credential-based system architecture is proposed, where the requester’s identity is not exposed to the services. The article presents the proposed architecture’s various components including the security aspects. Various options for implementing the architecture on resource-full and resource-constrained services are presented. A prototype of the proposed architecture is then implemented using Linux-based containers to emulate the services. Two representative systems, namely, a small-scale home automation system using a short service chain and a large-scale industrial automation system using a long service chain are considered. Timing measurements from the implementation are presented to demonstrate that the architecture is feasible and can be adapted for practical use in large-scale IoT systems.

This paper deals with classifying flows in data center networks, primarily based on the flows’ volume of traffic and duration. Flows are typically classified as long-lived flow or short-lived flow. Long-lived flows throttle the short-lived flows and should be classified at the earliest to select a different path in the network for them. The objectives of the proposed classification scheme are: (i) to support more than two flow classes (three in this paper), (ii) to achieve early classification by observing the first few packets in the flow, (iii) to achieve classification using ML techniques implemented in a programmable data plane switch using the Programming Protocol-independent Packet Processors (P4) language. Our contribution includes an improved hash-and-store algorithm for flow classification. The ML technique considered is Decision Tree, since it can be efficiently implemented in a P4 environment. The techniques have been evaluated using simulation-generated data implemented in a mininet emulator environment and classification accuracy results obtained. Two existing schemes, HashPipe and IdeaFix have also been implemented for comparison. The results show that the proposed scheme can classify a flow within 3 MB of the flow size when we consider more than one feature to classify the flows. This outperforms the existing threshold-based schemes by classifying flows, 3 times faster.

Rate adaptation (RA) is used in IEEE 802.11 WLANs to determine the optimal datarate for a particular channel condition. It becomes especially difficult to determine the optimal datarate for the new High-Throughput WLANs since the number of available datarates in these standards are very high. Moreover, a mobile environment poses additional challenge in RA as the channel conditions will keep on changing from time to time. In this paper, we propose a Contextual Bandits based Rate Adaptation (ContRA) algorithm for mobile users in IEEE 802.11ac standard. Based on the Received Signal Strength Indicator (RSSI) range that the receiver is currently in, the RA algorithm tries to determine the optimal rate from the rate set suitable for packet transmission in that RSSI range. Performance studies show that the proposed RA algorithm is able to adapt to changing channel conditions and quickly choose a suitable datarate for those channel conditions.

Segment Routing (SR) is a source routing paradigm that can significantly reduce the state that must be maintained in individual nodes in order to forward packets. SR involves defining segments in the network, computing the end-to-end route of a flow or packet as a sequence of segments and encoding the route in the packet header as a label stack, where each label is a Segment ID (SID) that identifies a segment. A network where a set of SIDs is used is known as an SR domain. SR is particularly suitable for Software-Defined Networks (SDNs) since the controller can compute the segment routes and configure them at the source of each flow within an SR domain. One type of SID is a Node SID where the Node ID of the tail node of a segment is used to identify the path to that node. When using Node SID, the number of SIDs that any given node must be aware of is |V|, the number of nodes in an SR Domain. However, for large networks, this might be more than the capacity of the forwarding table in a given node. In this paper, a method to partition the domain into subdomains is discussed and the reduction in the requirement for forwarding entries is studied. Experimentation with a test topology shows that a logarithmic reduction in the table size is possible by repeatedly applying this method.

This paper deals with the efficient design of network switch/routers for an optical data center network. Each switch has multiple components such as ingress/egress interfaces, optical and/or electronic buffers, interconnection switching fabric and so on. There are several possible choices available for each of these components. This paper presents a systematic approach to designing the switch architecture using a combination of these component choices, while meeting specified design criteria. It requires formally defining the structure of a switch and enforcing semantics across components. This is formulated as a constraint optimization problem with formal language grammar guiding its search process. This problem formulation is used to identify the best-possible architecture for a hierarchical DCN. Two of the three solutions identified were new and were not reported in literature. These solutions were also validated experimentally.

The Network Function Placement (NFP) problem involves placing Virtual Network Functions (VNFs) in a network in order to meet the Service Function Chain (SFC) requirements of the flows through the network. Simultaneously, the usage of network resources by the VNF instances must be optimized. Prior work primarily treated this as a constraint satisfaction problem, using linear programming to find optimal solutions. In contrast, this paper presents a distributed approach, based on a message-passing network protocol. This approach allows network nodes to negotiate the placement of VNF instances. A discrete-event simulation of the protocol is used to demonstrate it as a viable technique. A non-linearly constrained optimization (NCO) formulation is used to find optimal solutions for comparison and it is shown that the protocol yields nearly optimal solutions.

NS3 is a widely used open source dynamic event driven simulator to test new ideas, algorithms and protocols for networks including LTE cellular systems as guided by 3GPP specifications. This paper presents an addition to the LTE module of NS3 by implementing a wrap around mechanism for the standard 19-site cluster. In the wrap around mechanism, the network is extended to include six additional copies of the original hexagonal cluster, such that all cells have symmetric behavior. This will help obtain a more realistic interference environment. The wrap around mechanism is also extended to smaller 3-site and 7-site clusters which can be used for quick verification before simulating larger network. We also implement a wrap around mechanism for UEs, which allows cells in the simulation to have flexible boundary defined by radio conditions rather than fixed simulation boundary. The simulation results show that the wrap around mechanism, as implemented, provides statistically equivalent interference for all cells in the simulation area. This allows use of the entire simulation data providing statistically valid results in much reduced time.

Data center networks generate high volumes of traffic. In order to reduce packet latency, packet transmissions are often centrally scheduled. Such approaches have been proposed for both packet-switched and hybrid optical-packet switched networks. This paper investigates algorithm design choices for transmission scheduling in a tightly synchronized hybrid optical packet data center network. This problem is studied in two cases: with precedence where the requests are scheduled in the order of arrival, and without precedence, where the requests can be reordered in time. It is shown that the problem without any precedence constraints is NP-complete. For scheduling with precedence constraints, a greedy algorithm is proposed and shown to be optimal. Theoretical approximation for the performance of scheduling with the greedy algorithm is presented. Simulation experiments were performed on a two-tier network with 1024 servers and 64 wavelengths. Parallel implementation aspects of the scheduling algorithm are also discussed.

This paper investigates the time synchronization aspect of transmission scheduling in an optically groomed data center network (OGDCN). The architecture is based on a hybrid optical-packet approach and uses broadcast domains and wavelength division multiplexing for communication. The salient feature of this architecture is that all network paths are readily available in the optical domain and there is no need for optical path establishment. A source-destination pair must tune to a predefined wavelength at a scheduled time during data transfer. Every compute and storage node (CSN) is equipped with one or more tunable optical transceivers. As with any broadcast network, multiple transmitters that share a link segment cannot use the same wavelength on a link at the same time since this would result in collisions. Hence, transmission scheduling is required to prevent collisions and to allot an exclusive time duration for every transmission request. This paper's focus is on the time synchronization aspect that is critical for scheduling. Two schemes — continuous and discrete (slotted) time — are defined and evaluated. The objective of this paper is to understand the various factors affecting performance of these synchronization mechanisms. With the former scheme, clock accuracy has a significant impact on performance. With the latter scheme, propagation delay variance and packet length distribution impact performance in terms of utilization. The paper presents an evaluation of the performance of these mechanisms in the context of the OGDCN architecture. The results show that continuous time is able to better efficiently utilize network resources.

The control of excessive downloads by rogue users in organizational LANs is the subject of this work. Two mechanisms have been used in order to accomplish this. The first mechanism, is TCP rate control (TCR), it is a receiver-based flow control technique that can be used to effectively rate limit rogue users' flows, making more bandwidth available to regular users. The second mechanism, admission control reduces the bandwidth wastage due to users disconnecting out of impatience when user goodputs are low. Using simulation-based experiments, it has been demonstrated that the composite technique, exclusive TCP rate and admission control (xTRAC) provides seamless control of rogue users, while improving response times and goodput by upto 58% during overload. In this way regular users are incentivized and rogue users are penalized leading to long-term control of users.

With data center network traffic growing significantly, power-efficient optical and hybrid optical architectures are considered as an alternate to packet switching. Typically, hybrid optical architectures use fast optical switching elements to ensure any-to-any route reachability. In this paper, an optically groomed data center network (OGDCN) framework is proposed. The proposed framework supports any-to-any route reachability without using fast optical switching elements in the network. Different components can be combined to realize an OGDCN, as described in this paper. The framework is evaluated and compared to other architectures in terms of scalability and power consumption. A particular OGDCN realization is presented and is shown to be better than other architectures in terms of power consumption. The power consumption is lower by at least 47% than the next best existing architecture proposed in the literature.

In current generation LTE networks, user mobility leads to high levels of signaling traffic from the eNodeB (Evolved Node B) to the Evolved Packet Core (EPC) for maintaining the GPRS Tunneling Protocol (GTP) and Proxy Mobile IPv6 (PMIPv6) tunnel. Further, the presence of Packet Gateway (PGW) at the network edge introduces additional delay for every signaling procedure. In this paper, we propose an improved EPC architecture based on Software Defined Networking (SDN) concepts. This architecture (logically) centralizes the control plane functionality of EPC thereby eliminating the use of mobility management protocols and reducing mobility related signaling costs. The architecture utilizes the global network view feature of SDN for mobility management. The proposed architecture has been implemented in the ns-3 simulator framework. The results quantify the performance of the proposed architecture in terms of signaling cost, tunneling cost, handover latency and scalability.

With the proliferation of mobile devices, ubiquitous connectivity is becoming more and more desirable. Enterprise Wireless Local Area Network (WLAN) technologies provide such connectivity in several environments. In such deployments, configuration and management is done centrally using the vendor independent Control and Provisioning of Wireless Access Points (CAPWAP) protocol. However, the controllers provide little to no room for network programmability. In this paper, we propose a Software Defined Networking (SDN) framework for enterprise WLANs. This framework will provide network programmability allowing the network administrators to deploy customized applications for utilizing the WLANs. We also propose a seamless, client-unaware mobility mechanism which runs on the proposed framework.

Recently, there has been a tremendous growth in mobile network traffic. Network providers are looking for techniques that selectively offload the mobile data traffic onto WiFi (IEEE 802.11) networks to balance the load and improve network performance. Several architectures based on Proxy Mobile IPv6 (PMIPv6) have been proposed to support seamless data offloading. The demerits of PMIPv6 include lack of flow mobility and single point of failure. There exist architectures that extend PMIPv6 to support flow mobility, but still face the problem of overhead at the gateway and single point of failure. In this paper, we propose Seamless Internetwork Flow Mobility (SIFM), a new architecture that overcomes these drawbacks and provides seamless data offload supporting flow mobility. Both the PMIPv6 and the SIFM architectures have been implemented and evaluated incorporating salient LTE and WiFi network features in the ns-3 simulator. The performance studies validate that seamless mobility can be achieved for clients in both of these architectures. The results show that for the best possible (scenario dependent) offload value, the SIFM architecture shows an improvement of 13.86%, 29.05% and 11.33% whereas the PMIPv6 architecture shows an improvement of 7.96%, 19.52% and 7.83% in terms of delay, packet loss and throughput respectively compared to no offload scenario in each architecture. Further, we also show that the support for flow mobility in the SIFM architecture provides the flexibility to move selective flows to another network. This helps in achieving better performance gain compared to moving all the flows of the user as done in the PMIPv6 architecture.

In the context of an IP network, we investigate an interesting case of the inverse shortest path problem using the concept of network centrality. For a given network, the centrality distribution associated with the links of a network can be determined based on the number of shortest paths passing through each link. An entropy measure for this distribution is defined, and we then forumulate the inverse shortest problem in terms of maximizing this entropy. We then obtain a centrality distribution that is as broadly distributed as possible subject to the topology constraints. An appropriate change in the weight of a link alters the number of shortest paths that pass through it, thereby modifying the centrality distribution. The idea is to obtain a centrality distribution that maximizes the entropy. This problem is shown to be NP-hard, and a heuristic approach is proposed. An application to handling link failure scenarios in Open Shortest Path First routing is discussed.

The Content Centric Networking (CCN) architectural framework is designed with the central abstraction of content distribution rather than host-to-host connectivity. CCN has several advantages such as inherent router caching, lower content retrieval time and network load reduction. However, it also faces various challenges such as scalability, deployment and storage issues. In particular, the routing state information that needs to be maintained in the CCN routers leads to very high memory requirements that might not be met using current technologies. If the routing state information stored in the routers is reduced, it leads to flooding of interest packets increasing congestion in the network. The objective of this paper is to propose techniques that avoid congestion due to interest flooding in CCN while having low router memory requirements. We have proposed three different algorithms to address this problem and present their performance using discrete-event simulation models.

In this paper, we present efficient data reliability mechanisms for a communication network supporting wide area monitoring applications in the electrical Smart Grid. Reliability of data packets, especially control packets, is deemed a critical requirement. Reliability can be achieved by sending multiple copies of the data packet on disjoint paths. However, this is inefficient in terms of bandwidth usage. In this paper, we present two algorithms for reliable data transfer that can handle single link and double link failures respectively. The proposed mechanisms reduce the bandwidth requirement while improving data reliability by combining multi-path transmissions and error coding techniques. The performance of the mechanisms has been studied using discrete-event simulation models. Our simulation results show that the proposed mechanism is able to reduce the bandwidth requirement by 30-54%. Also, there is a significant improvement in data reliability with values reaching close to 100%.

Various Centrality measures such as Degree, Closeness, and Betweenness were introduced in order to analyze networks and understand both the global dynamics of the networks and the roles played by individual nodes. It will be worthwhile to rank the centrality measures of each node and an index of the distribution of centrality measures in the entire network. In this paper, we define the notion of entropy of centrality measures, which extends the concept of centrality to the whole network. We show that this measure has wide range of applications, in network design, from designing maximally efficient networks to identifying dominance of one node or link in the context of entire network. In particular, we present an application to tactical wireless networks.

In this paper, we examine the effects of a power saving scheme in Passive Optical Networks (PON). Buffers in network equipment have been a cause of concern since they consume significant power. In a PON, the Optical Network Unit (ONU) buffers client node packets before forwarding to the Optical Line Terminal (OLT). We propose a scheme that reduces or eliminates buffers in the ONU thereby providing reduction in cost and power. However, this can potentially increase the packet delay due to buffering at the client node. This paper analyzes the delay performance using simulated and theoretical models. The increase in delay due to buffering at the EN instead of the ONU is found to be less than 300 microseconds, for the studied workloads; the total packet delay is also less than 800 microseconds. This is within the access network delay budget (typically 2 milliseconds) for different traffic types and loads.

Designing a multi-hop wireless network is a challenge mainly because of high bit error rates and the inherent broadcast nature of the medium creating interference. To improve the capacity, protocols based on spatial reuse of frequencies with multiple orthogonal channels have been introduced. This is particularly useful in complete wireless environments such as wireless mesh networks and wireless sensor networks (WSN). Based on initial testbed experiments on WSN testbeds, we show that there is a gap between reality and simulation models due to overheads in implementing these protocols. In order to support QoS guarantees in critical paths for such networks, we present a generic channel allocation scheme based on k-distance coloring problem, for multiple channel networks. The scheme is designed keeping in mind the real time deployment issues in wireless networks. We report the results from experiments conducted using a IEEE 802.15.4 based testbed consisting of Xbow MicaZ nodes and results obtained using the OMNET4 simulation environment.

In this paper, we investigate problems related to optical wavelength division multiplexing (WDM) networks that use the virtual concatenation (VCAT) mechanism of synchronous optical network (SONET) technology. VCAT, an end-to-end mechanism, allows SONET based optical WDM networks to carry traffic in

In this paper, we study the effects of mobility on network parameters in hierarchical ad hoc networks. Several mobility models have been designed and studied to mimic the behavior of real world mobility in networks. They have been successful in modeling the movement of mobile nodes in simulations. However, in this work, we show that several mobility models fall short of extending the same result to hierarchical networks. Most mobility models can only predict the movement of nodes in a single cell or cluster. When mobile nodes start moving into adjacent clusters, the time required for handoff and other protocol overhead issues alter the throughput. This leads to drastic drop in throughput and increased latency in packet delivery. Also, commonly used routing protocols do not adequately support handling high mobility and frequent route discovery issues. We evaluate the performances of various routing protocols and mobility models in a highly mobile hierarchical ad hoc network using NS2 simulation.

We investigate the problem of scheduling in OFDM-based multihop relay networks with special emphasis on IEEE 802.16j based WiMAX networks. In such networks, scheduling is the problem of determining the user to be serviced at a given instant of time on a given sub-channel, while possibly exploiting multiuser and frequency diversities opportunistically in optimizing the desired objectives. In, the authors propose a heuristic opportunistic scheduling algorithm, GenArgMax, for such networks. In this paper, we study the drawbacks in algorithm GenArgMax. We present new opportunistic MAC scheduling algorithms that remedy these drawbacks. We compare performance of the proposed algorithms using detailed discrete event simulation based studies. Results show that the proposed algorithms improve the system throughput by over 40%, for 40-user 3-hop networks.

This paper presents an implementation based study of multi-channel medium access control protocols in hardware constrained wireless sensor network (WSN) nodes with 802.15.4 radio. In the network architecture presented, each sensor node has a single radio transceiver that can be tuned to any of the available sixteen non-overlapping channels. The simplest way to select data channel is to use a common channel signaling between the nodes. We have conducted experiments to verify whether control channel congestion can occur in case of 802.15.4 radios using MicaZ and TelosB motes. The throughput results show the per-node throughput does not decline as significantly with increasing number of senders, with the proposed multi-channel protocol.

This paper proposes a hierarchical two-step localization method for heterogeneous sensor networks. The network consists of three types of nodes: anchor nodes with known locations, a few nodes equipped with both Ultra-Wide Band (UWB) and RF radios, and a large number of sensor nodes called Lite Nodes. By using a hierarchical network architecture and UWB technology, only a small number of anchor nodes are needed. The localization method works in two steps. First, UWB nodes estimate their locations by using the built-in high-precision distance measurement and locations of anchor nodes. Next, Lite Nodes use UWB nodes as references to estimate their locations. The performance of iterative and non-iterative localization methods are compared. It is observed through simulations that iterative method produces much smaller localization error. The effects of UWB node placement and other parameters such as measurement noise, number of anchor nodes, and communication ranges on the resulting localization error are also presented.

In this paper, we study wireless links that are enhanced using adaptive modulation and coding (AMC) techniques. In particular, we consider a cross-layer protocol approach that modifies the behavior of the Transmission Control Protocol (TCP) using AMC techniques. An application of the proposed system for an IEEE 802.16 (WiMAX) based Wireless Metropolitan Area Network (WMAN) is presented. The performance of the system has been studied using discrete event simulation models in ns2 and compared to TCP-Reno and TCP-Tahoe schemes. The results indicate that in our system, queueing delay and packet drops that result due to buffer overrun are minimized. We also show that our system achieves better throughput fairness when multiple flows share a bottle-necked access link.

Ultra-wideband (UWB) communications is receiving significant attention recently due to its high data rates and low power, low interference transmission. This paper considers the issue of utilizing these advantages of UWB to design improved Wireless Sensor Networks (WSNs). In particular, we consider data gathering in wireless sensor networks using a mobile node for data collection. We first propose a network architecture where a mobile node equipped with both a UWB transceiver and a narrowband RF transceiver is used to collect data from sensor nodes. The sensor nodes are equipped with a narrowband RF transceiver and only a UWB transmitter (not receiver). This approach is chosen to strike a balance between cost of each sensor node and speed of data transfer, since a UWB transmitter is much less complex and expensive than a UWB receiver. We then propose a mobile Data Gathering (DGR) algorithm to find a minimal set of points in the sensor network, which will serve as data gathering points for the mobile node. We use a Voronoi diagram of the network as a starting point, considering each sensor node in the network as a site in the Voronoi diagram and finnding points in the network where data from multiple sites (sensor nodes) can be collected. We then use a weight function designed to reduce the number of these data collection points, and generate a new smaller set of points, such that the mobile node can collect data from multiple sites from each such point. With the aid of a discrete-event simulation model, we show significant savings in the total time for data collection while providing a high level of network coverage.

In this paper, we consider the problem of employing UltraWideBand (UWB) radio technology in Wireless Sensor Networks. UWB promises very high data rates (of the order of few hundred Mbps), in-built localization features and low power consumption. However, UWB radios have a high acquisition time (in the order of milliseconds). As a result, distributed Medium Access Control (MAC) solutions based on a Request/Response mechanisms suffer from increased overhead when employed in UWB based networks. To mitigate the effect of UWB acquisition time, we propose a node architecture that uses dual radios on the sensor nodes: a primary UWB-based radio for data transmission and an auxiliary narrowband RF-based radio for control information and signaling. We introduce two techniques for Medium Access based on this architecture. In the first technique, we employ the narrowband channel for the exchange of RTS/CTS (as defined in IEEE 802.11 standard) information and thus enable collision-free data transmission in the UWB space. In the second technique, we employ the concept of wake-up radios to provide signaling for data transmission. We employ a distributed channel assignment technique by which neighbors agree on a wake-up channel for each node. This channel is then used to signal the receiver of an impending transmission. Through extensive simulation studies, we demonstrate that both the techniques deliver considerable improvements in delay performance and increase the network throughput over the traditional single radio UWB solution.

Utra-Wide Band (UWB) technology can provide high data rate and accurate localization at low energy cost. It is considered to be very useful for wireless sensor networks. We propose a reinforcement learning based geographic routing algorithm for UWB sensor networks. A comprehensive reward function is proposed in the learning algorithm to consider node energy, delay, routing failure, and network lifetime. The algorithm performance is evaluated in NS2 and compared with GPSR. Simulation results demonstrate that the proposed algorithm can improve network robustness and network lifetime to be 75% to 213% better than GPSR

In this paper, we address the problem of node placement in a hierarchical heterogeneous wireless sensor network. We consider a two-tiered wireless sensor network where the resource constrained lite nodes (LNs) are used for sensing the environment and high-end sophisticated nodes (SNs) are added to aggregate and forward data. We intend to place minimum number of SNs to handle the traffic generated by LNs and ensure that the SNs form a connected network. We formulate the node placement problem as an optimization problem and use three different algorithms to solve it; namely, binary integer linear programming (BILP), greedy algorithm (GREEDY) and genetic algorithm (GA). We also propose a hybrid approach (HYBRID) combining BILP, GREEDY and GA to improve results. It was found through simulations that GA performed better for random LN deployment. However, using HYBRID, results comparable to original GA could be obtained in only 11.46 % of the time required for the original GA. We support the results with statistical tests.

In this paper, we consider the problem of traffic grooming in optical wavelength division multiplexed (WDM) mesh networks under static traffic conditions. The objective of this work is to minimize the network cost and in particular, the electronic port costs incurred for meeting a given performance goal. In earlier work, we have shown the benefits of limited grooming switch architectures, where only a subset of wavelengths in a network are equipped with expensive SONET Add Drop Multiplexers (SADM) that provide the grooming functionality. In this work, we also consider the wavelength conversion capability of such groomers. This can be achieved using a digital cross-connect (DCS) in the grooming switch to switch low-speed connections between the SADMs (and hence, between wavelengths). The grooming switch thus avoids the need for expensive optical wavelength converters. Based on these observations, we propose a limited conversion based grooming architecture for optical WDM mesh networks. The local ports at every node in this architecture can be one of three types: an add- drop port, a grooming port that allows wavelength conversion or a grooming port that does not allow wavelength conversion. The problem studied is: given a static traffic model, where should the different ports be placed in a network? We formulate this as an optimization problem using an Integer Linear Programming (ILP) and present numerical results for the same. We also present a heuristic based approach to solve the problem for larger networks.

In this paper, we consider a circuit-switched optical wavelength division multiplexed (WDM) network that offers protection services to the connections established in the network. A dynamic traffic model, where connection requests arrive based on some stochastic arrival process, is considered. In earlier work, the notion of partial protection was introduced for a WDM network with sub-wavelength capacity allocation capabilities, as in TDM-WDM networks, for a dynamic traffic model. Here, instead of setting up a backup path with the same capacity as the primary, the backup path is established with capacity that is less than the primary path's capacity, where the amount of backup path capacity is specified by the user. Intuitively, this will reduce backup path requirements, thereby increasing the number of connections accepted. In (J. Fang et al., 2005), the mechanism presented attempted to provide the maximum available protection bandwidth while ensuring that the minimum backup requirements are met. However, this can still result in wasted protection bandwidth if failures do not occur. In this paper, we present a mechanism to further improve the performance of partial protection schemes for dynamic traffic. When failure occurs, the connection is carried on the backup with reduced capacity. However, the system tries to identify additional spare capacity on the same backup path, on either the same wavelength or a different wavelength. The objective is to increase the amount of backup capacity at the time of failure, so that the connection's end user does not see a noticeable drop in bandwidth allocated. We present a heuristic connection admission control algorithm that prevents backup contention that occurs when backup paths of connections affected by a failure contend (share) for resources. A detailed performance evaluation of the mechanisms for different network topologies and other system parameters is presented. For one of the cases studied, the connection acceptance probability is increased from 95% to 99%, while providing nearly 100% backup capacity, when failure occurred. The mechanism proposed to counter backup contention is seen to provide an average of 120% reduction in the contention among backup paths of connections traversing a link, especially when the number of wavelengths in each link is small.

In this paper, we consider performance improvements for a sparse groomed wavelength routed optical wavelength division multiplexed (WDM) network. In such networks, the wavelength capacity per channel can be as high as 40 Gbps whereas the individual session requests can be much lower. Traffic grooming, that multiplexes several sessions on a wavelength, is a widely studied technique to reduce the effects of this capacity mismatch. In this paper, we consider an electronic traffic groomed network that consists of SONET/SDH groomers at the core optical cross connect (OXC) nodes. Since these groomers are expensive, reducing the number of groomers needed is an important design goal. A sparse groomed network is defined as one where only a subset of the core network nodes possess grooming capability in addition to optical switching; other nodes only possess optical switching and optical add/drop capabilities. In order to improve the overall blocking probability, we present a mechanism for reserving wavelengths between the grooming nodes in a network. The performance of the mechanism is studied using discrete event simulation techniques for various topologies and system parameters. The results show that when we reserve enough wavelengths for groomed traffic, the performance of the network is improved by up to 100% and up to 76% for ARPANET and NSFNET topologies respectively.

In this paper, we consider the problem of survivable network design in traffic groomed optical WDM mesh networks with sub-wavelength capacity connections. In typical survivable network designs, individual sessions are provided either full protection or no protection. We consider a quality of protection (QoP) framework where a connection is provided partial protection, i.e. when a link failure occurs on the primary path, the protection bandwidth provided on the backup path is less than or equal to the primary bandwidth. Each connection request specifies the primary bandwidth and a minimum backup bandwidth required. The network will guarantee at least the minimum backup bandwidth and, if capacity is available, higher backup bandwidth up to the primary path's bandwidth. The advantage of such a model is that it can reduce backup capacity requirements based on connection needs leading to lower blocking probability and lower network costs. We consider two scenarios: (i) a network with static traffic and formulate the problem of providing partial protection in groomed networks as an integer linear program (ILP); and (ii) a network with dynamic traffic that is analyzed using discrete-event simulation models. The results quantify the gain in blocking probability for different partial protection scenarios.

This paper studies the problem of IP traffic grooming in optical wavelength division multiplexed (WDM) mesh networks. Two different grooming architectures are considered: (i) IP/MPLS grooming, and (ii) SONET grooming. The IP/MPLS grooming approach provides a fine level of grooming granularity realized via software based implementations, but has router processing related bottlenecks. The SONET grooming approach is realized in dedicated hardware, but is more expensive and typically offers limited grooming granularity choices. This paper also considers multipath routing as used in SONET virtual concatenation (VCAT) techniques. A detailed comparison of the different grooming options in terms of blocking probability, lightpath utilization and survivability issues is presented. The simulation analysis helps quantify the improved performance of finer granularity grooming approaches over the coarser SONET-based approaches

In this paper, we consider the problem of determining primary and backup paths for survivable optical WDM mesh networks. We propose a distributed routing mechanism, called least resource consumption routing (LRCR), that tries to minimize the combined cost of the primary and the backup path. The proposed cost model includes the effect of various factors such as mean load, variance of the load on the route, number of converters required by the route and the length of the route. Further, we model the route cost in such a way that it is extensible to include any new parameters and vary their relative importance. The performance results for the NSFNET topology and a 30-node random network, show that the proposed scheme leads to at least 30% improvement in terms of blocking probability and reduces the amount of converters required per node by about 80% compared to other proposed techniques in literature.

Recent approval by the Federal Communications Commission (FCC) has led to considerable interest in exploiting ultra wideband (UWB) access on an unlicensed basis in the 3.1-10.6 GHz band. Currently, the IEEE TG802.15.3a standards group is in the process of developing an alternative high-speed link layer design conformable with the IEEE 802.15.3 wireless personal area network (WPAN) multiple access (MAC) protocol. One of the proposals, based on the concept of orthogonal frequency division multiplexing (OFDM), divides the spectrum into multiple bands and achieves channelization through the use of different time-frequency codes. These multiple channels can help satisfy the increasing demand for higher bandwidth in order to support high data rate multimedia applications. In this paper, we present a multi-channel scheduling algorithm that simultaneously utilizes the various channels available in the UWB network.

This paper presents survivability mechanisms that attempt to improve the overall restoration efficiency of dynamic link restoration in optical WDM mesh networks. The proposed mechanisms make use of network state information such as link load in order to identify critical network sections (such as links or segments) that are subsequently protected by selectively assigning backup capacity ahead of failures. The first approach, termed "threshold based selective link restoration", utilizes existing link load information to identify critical links, and the second approach, termed "threshold based selective segment restoration", employs data-analysis techniques to identify critical segments. The overall goal of the proposed algorithms is to improve the restoration efficiency by providing a trade-off between proactive protection and reactive restoration. The experimental results indicate that under high loads, the proposed approaches maintain a consistent restoration efficiency that is at least 10% when compared to dynamic restoration.

In this paper, we propose a new call admission control scheme called dual threshold bandwidth reservation, or DTBR scheme. The main novelty is that it builds upon a complete sharing approach, in which the channels in each cell are shared among the different traffic types and multiple thresholds are used to meet the specific quality-of-service (QoS) requirements. We present a detailed comparative study based on mathematical and simulation models, and quantitatively demonstrate that the DTBR is capable of providing the QoS guarantee for each type of traffic, while at the same time leading to much better channel efficiency. We further show that the DTBR scheme with elastic data service can offer both service guarantee and service differentiation for voice and data services, and enhance the bandwidth utilization.

This paper studies the performance of TCP transport protocol over an optical burst-switched (OBS) wavelength division multiplexed (WDM) wide-area network. Typically, an OBS network consists of optical core routers and electronic edge routers connected by WDM links. At the network ingress nodes, IP packets are assembled into bursts that are routed through the core network and disassembled at the network egress nodes. This paper studies the effects of OBS network characteristics and parameters on TCP's delay and throughput performance: (i) burstification (burst-assembly and disassembly) delays, (ii) data-burst scheduling and (iii) variation of burst packet parameters (i.e. burst size, burst time-outs), and (iv) burst drop probability. Detailed results based on an ns2-based simulator, that has been extended to incorporate WDM and OBS networking, are presented.

This paper studies the problem of designing survivable optical wavelength division multiplexed (WDM) networks. A wavelength-routed wide area backbone network supporting circuit-switched traffic is considered. This paper also considers the use of optical wavelength conversion technology which has been shown to help improve network performance. However, wavelength conversion is still an expensive technology and using optical conversion could potentially result in signal quality degradation. In survivable networks, protection against failures is provided using backup paths that are determined when a session is established. In this paper, we present three primary and backup route computation mechanisms that attempt to improve overall network performance compared to existing solutions. One of the key design goals is to reduce the number of required converters per node. First, we present a routing algorithm, termed conversion free primary routing (CFPR) that computes primary paths without wavelength conversion, as far as possible. Next, we present a converter multiplexing technique that is used to share wavelength converters among multiple backup paths. This significantly reduces the number of connections blocked due to wavelength converter unavailability and reduces the number of wavelength converters required at each node, thus reducing system cost. Finally, we propose a backup path relocation scheme that migrates existing backup paths, whenever needed, to accommodate more primary paths and also to obtain primary routes with fewer hops. This is done to improve network utilization and reduce blocking probability. The proposed techniques are analyzed in detail using a discrete-event simulation model. The results show that significant reduction in blocking probability is possible with the proposed mechanisms. The number of converters required at each node to achieve a given blocking probability is also seen to be four times lower, compared to existing architectures based on static shortest path routing.

This paper studies the scheduling problem for multiple channels in a wireless local area network environment, where the resource unit assumes to be fixed length slot. The common assumption is: each user can transmits or receive through different channels sequentially, but not simultaneously. In this paper, three scheduling algorithms are proposed. Among them, CSSA schedules each station in contiguous mode, so each station occupies a single channel. The two algorithms, NCSRRA and NCRRA, schedule stations in noncontiguous mode, in that some stations will occupy at least two channels. The CSSA achieves the highest scheduling efficiency, but with relatively high scheduling complexity. The NCSRRA and NCRRA achieve in high efficiency with significantly low complexity.

We study routing and wavelength assignment for a circuit-switched time division multiplexed (TDM) wavelength-routed (WR) optical WDM network. In a conventional WR network, an entire wavelength is assigned to a given session (or circuit). This can lead to lower channel utilization when the individual sessions do not need the entire channel bandwidth. We consider a TDM-based approach to reduce this inefficiency. In this architecture, each wavelength is partitioned in the time-domain into fixed-length time-slots organized as a TDM frame. Multiple sessions are multiplexed on each wavelength by assigning a sub-set of the TDM slots to each session. Thus, given a session request with a specified bandwidth, the goal is to determine the route, wavelength and time-slot assignment (RWTA) that meets the request. This is similar to routing and wavelength assignment in WR networks. We present a family of RWTA algorithms and study the blocking performance. We use the existing shortest-path routing algorithm with a new link cost function, least resistance weight (LRW) function, that incorporates wavelength utilization information. We employ the known least loaded (LL) wavelength selection and present three variations of the least-loaded time-slot (LLT) algorithm. Simulation based analyses are used to compare the proposed TDM architecture to traditional WR networks, both with and without wavelength conversion. The goal is to compare the benefits of TDM and wavelength conversion towards improving performance in WR networks. The results show that the use of TDM provides substantial gains, especially for multi-fiber networks.

Gathering sensed information in an energy efficient manner is critical to operating the sensor network for a long period of time. The LEACH protocol presented by Heinzelman et al. (2000) is an elegant solution where clusters are formed to fuse data before transmitting to the base station. In this paper, we present an improved scheme, called PEGASIS (power-efficient gathering in sensor information systems), which is a near-optimal chain-based protocol that minimizes energy. In PEGASIS, each node communicates only with a close neighbor and takes turns transmitting to the base station, thus reducing the amount of energy spent per round. Simulation results show that PEGASIS performs better than LEACH. For many applications, in addition to minimizing energy, it is also important to consider the delay incurred in gathering sensed data. We capture this with the energy /spl times/ delay metric and present schemes that attempt to balance the energy and delay cost for data gathering from sensor networks. We present two new schemes to minimize energy /spl times/ delay using CDMA and non-CDMA sensor nodes. We compared the performance of direct, LEACH, and our schemes with respect to energy /spl times/ delay using extensive simulations for different network sizes. Results show that our schemes perform 80 or more times better than the direct scheme and also outperform the LEACH protocol.

In this paper we consider the problem of data collection from a sensor web consisting of N nodes, where nodes have packets of data in each round of communication that need to be gathered and fused with other nodes' packets into one packet and transmitted to a distant base station. Nodes have power control in their wireless communications and can transmit directly to any node in the network or to the base station. With unit delay cost for each packet transmission, if all nodes transmit data directly to the base station, then both high energy and high delay per round will occur. In our prior work [6], we developed an algorithm to minimize the energy cost per round, where a linear chain of all the nodes are formed to gather data, and nodes took turns to transmit to the base station. If the goal is to minimize the delay cost, then a binary combining scheme can be used to accomplish this task in about log N units of delay with parallel communications and incurring a slight increase in energy cost. The goal is to find data gathering schemes that balance the energy and delay cost, as measured by energy*delay. We conducted extensive simulation experiments with a number of schemes for this problem with 100 nodes in playing fields of 50m x 50m and 100m x 100m and the base station located at least 100 meters and 200 meters, respectively, from any node. With CDMA capable sensor nodes, a chain-based binary scheme performs best in terms of energy*delay. If the sensor nodes are not CDMA capable, then parallel communications are possible only among spatially separated nodes, and a chain-based 3 level hierarchy scheme performs well. These schemes perform 60 to 100 times better than direct scheme and also outperform a cluster based scheme, called LEACH [3]. 1.

Optical dense wavelength division multiplexed (DWDM) networks are an attractive candidate for the next generation Internet and beyond. In this paper, we consider the wide area wavelength routed backbone network with circuit-switching. Given a session request, the routing and wavelength assignment (RWA) problem is to calculate a path between two nodes, and also assign a set of wavelengths along this path. We use Dijkstra's shortest path algorithm, suitably modified for DWDM networks, for computing the shortest paths. We consider WDM aware weight functions which include factors such as available wavelengths per link, distance, and total wavelengths per link. We study and compare the performance of these weight functions in terms of blocking probability, link utilization and average delay.

This paper considers the problem of providing signaling support for quality of service (QoS) in wireless and mobile networks. In particular, it proposes an architecture based on the differentiated services (Diffserv) framework being developed for wired networks. The architecture presents the need for an explicit signaling protocol that is necessary since Diffserv uses an implicit mechanism. The class-based queuing (CBQ) algorithm has been used for scheduling user requests and has also been modified to handle several wireless-specific features. This includes user mobility, packet loss characterization, lower wireless bandwidth, and battery power constraints. The framework and mechanisms have been implemented in a wireless testbed for the FreeBSD operating system using Pentium workstations and WaveLAN wireless equipment. Experimental results from this testbed show the validity of the proposed Diffserv model and also provide performance analyses.

This paper describes scheduling algorithms for scheduling traffic in wireless data networks with multiple channels per cell. The paper assumes that a reservation-based MAC protocol is used. The main objective of the scheduling algorithms is to reduce the computation time while maximizing the utilization of the network resources, thereby improving the system throughput. In this paper, we consider two type of systems-single priority and multiple priority. For each system, two different algorithms are considered depending on whether slots are allocated contiguously or not. A performance study that considers network utilization, computation time, and the throughput for 2 Mbps and 10 Mbps data streams for the above algorithms is presented.

User mobility management is one of the important components of mobile multimedia systems. In a cell-based network, a mobile should be able to seamlessly obtain transmission resources after handoff to a new basestation. This is essential for both service continuity and quality of service assurance. We present strategies for accommodating continuous service to mobile users through estimating resource requirements of potential handoff connections. A diverse mix of heterogeneous traffic with diverse resource requirements is considered. We investigate static and dynamic resource allocation schemes. The dynamic scheme probabilistically estimates the potential number of connections that will be handed off from neighboring cells, for each class of traffic. The performance of these strategies in terms of connection blocking probabilities for handoff and local new connection requests are evaluated. The performance is also compared to a scheme previously proposed by Yu and Leung (see IEEE Journal on Selected Areas in Communications, vol.15, p.1208-25, 1997). The results indicate that using dynamic estimation and allocation, we can significantly reduce the dropping probability for handoff connections.

Traditional computer networking courses primarily tend to provide students with hands-on software development and network performance experience with TCP/IP and Ethernet networks. Our objectives are to enhance the curriculum of networking courses and the expertise of students by introducing next-generation networks such as wireless and ATM networks. To facilitate this, we have established a wireless ATM network instructional facility (NIF) at Washington State University (WSU). Projects based on ATM networks and wireless networks have been introduced in a course on undergraduate computer networks taught at WSU during Spring 1998. This paper describes the laboratory setup, the projects and assignments, and the feedback obtained from the students.

User mobility management is one of the important components of mobile multimedia systems. In a cell-based network, a mobile should be able to seamlessly obtain transmission resources after handoff to a new base station. This is essential for both service continuity and quality of service assurance. In this paper, we present strategies for accommodating continuous service to mobile users through estimating resource requirements of potential handoff connections. A diverse mix of heterogeneous traffic with diverse resource requirements is considered. The investigate static and dynamic resource allocation schemes. The dynamic scheme probabilistically estimates the potential number of connections that will be handed off from neighboring cells, for each class of traffic. The performance of these strategies in terms of connection blocking probabilities for handoff and local new connection requests are evaluated. The performance is also compared to a scheme previously proposed by Yu and Leung (see IEEE J. Select. Areas Commun., vol.15, p.1208-25, 1997). The results indicate that using dynamic estimation and allocation, we can significantly reduce the dropping probability for handoff connections.

This paper describes the design and analysis of the scheduling algorithm for energy conserving medium access control (EC-MAC), which is a low-power medium access control (MAC) protocol for wireless and mobile ATM networks. We evaluate the scheduling algorithms that have been proposed for traditional ATM networks. Based on the structure of EC-MAC and the characteristics of wireless channel, we propose a new algorithm that can deal with the burst errors and the location-dependent errors. Most scheduling algorithms proposed for either wired or wireless networks were analyzed with homogeneous traffic or multimedia services with simplified traffic models. We analyze our scheduling algorithm with more realistic multimedia traffic models based on H.263 video traces and self-similar data traffic. One of the key goals of the scheduling algorithms is simplicity and fast implementation. Unlike the time-stamped based algorithms, our algorithm does not need to sort the virtual time, and thus, the complexity of the algorithm is reduced significantly.

Energy efficiency is an important issue in mobile wireless networks since the battery life of mobile terminals is limited. Conservation of battery power has been addressed using many techniques. This paper addresses energy efficiency in medium access control (MAC) protocols for wireless networks. The paper develops a framework to study the energy consumption of a MAC protocol from the transceiver usage perspective. This framework is then applied to compare the performance of a set of protocols that includes IEEE 802.11, energy-conserving MAC (EC-MAC), PRMA, multiservices dynamic reservation-TDMA (MDR-TDMA), and distributed-queueing request update multiple access (DQRUMA). The performance metrics considered are transmitter and receiver usage times for packet transmission and reception. The analysis here shows that protocols that aim to reduce the number of contentions perform better from a energy consumption perspective. The receiver usage time, however; tends to be higher for protocols that require the mobile to sense the medium before attempting transmission.

Mobile computers typically have limited energy for computing and communications due to short battery lifetimes. Encoding, decoding, and transmission of video information require significant computing and communication resources. Low power encoding and decoding schemes have been researched extensively. In this paper, we focus on processing encoded video for transmission under low battery power conditions. Such processing, while conserving battery power, attempts to reduce deterioration of video quality.

This paper describes the design and analysis of the scheduling algorithm for EC-MAC (energy conserving medium access control) (Sivalingam et al.), a low-power medium access control (MAC) protocol for wireless and mobile ATM networks. Based on the structure of EC-MAC and the characteristics of the wireless channel, we propose a new algorithm which can deal with the bursty errors and the location-dependent errors. Most scheduling algorithms proposed for either wired or wireless networks were analyzed with homogeneous traffic or multimedia services with simplified traffic models. We analyze our scheduling algorithm with more realistic multimedia traffic models. One of the key goals of the scheduling algorithm is simplicity and fast implementation. Unlike the time-stamp based algorithm, our algorithm does not need to sort the virtual time, thus reducing the complexity of the algorithm significantly.

Efforts are underway to enhance the Internet with quality of service (QoS) capabilities for transporting real-time data. The ReSerVation Protocol (RSVP) provides a signaling mechanism for end-to-end QoS negotiation. The issue of wireless networks and mobile hosts being able to support applications that require QoS has become very significant. Reservation of resources and the maintenance of QoS for the mobile as it moves from one region to another creates a new set of challenges. We describe an architecture where a modified RSVP protocol helps provide QoS support for mobile hosts. The modified RSVP protocol has been implemented in an experimental wireless and mobile testbed to study the feasibility of our approach.

This paper presents a media access protocol designed for LIGHTING, a WDM testbed currently under construction which has been designed for high-performance supercomputer interconnection. The architecture is based on a dynamically reconfigurable hierarchical WDM network that is being constructed to interconnect a large number of supercomputers and create a distributed shared memory (DSM) environment. This paper describes the network media access protocol based on a single tunable transmitter and single tunable receiver (TT-TR) per node. The protocol exploits the bimodal traffic characteristics of a DSM system. The primary objectives of the protocol design are reduced average latency per packet, support of broadcast/multicast, and support of collisionless communication. The proposed approach is compared to an earlier protocol based on one tunable transmitter and one fixed receiver (TT-FR) per node. The performance of the protocol in terms of average latency and channel utilization is analyzed for varying system characteristics such as number of nodes and channels.

This paper investigates the performance of media access protocols based on on-line scheduling for an optically connected star-coupled system with wavelength division multiple access channels. Hybrid access protocols combining reservation and pre-allocation of receiver channels have been previously proposed. Transmission consisted of a reservation phase followed by a data phase. Each node was allowed to place a reservation for one WDM channel. This protocol is extended in this paper by allowing reservations on multiple channels and using simple on-line scheduling algorithms. Existing scheduling algorithms (all are off-line) for similar reservation problems tend to have high implementation and computational complexity. We require that scheduling algorithms be real-time and amenable to hardware implementation. The performance of the extended protocol incorporating two simple on-line scheduling algorithms is presented in this paper. We show that the slight increased computational overhead with scheduling is justified by reduced packet latency and higher utilization, especially for client-server traffic.

Scalable, hierarchical, all-optical wavelength division multiplexed (WDM) networks for interconnection in distributed cluster-based computing systems have been recently considered. Hybrid access protocols combining reservation and pre-allocation have been studied for this type of network which supports a distributed shared memory (DSM) environment. The objectives of the protocols are reduced average latency per packet, support of broadcast/multicast, collisionless communication, and exploitation of inherent DSM tragic characteristics. This paper compares random and static access strategies on the control channel to establish reservation for data packets. Random access provides reduced packet latency under light traffic conditions and has simpler implementation. Static access is free of collisions and instability but has longer control cycle lengths. The performance of the network is analyzed through simulation models with varying system parameters such as number of nodes and channels. Dynamic schemes which switch between random and static access and vice-versa are also considered.

Scalable, hierarchical, all-optical, WDM networks for processor interconnection have been previously considered. The paper introduces an access protocol for this type of network which supports a distributed shared memory environment. The objectives of the protocol are reduced average latency per packet, support of broadcast multicast, collisionless communication, and the exploitation of the inherent distributed shared memory traffic characteristics. A hybrid strategy, in terms of channel reservation, is described that trades maximum capacity for reduced communication latency to improve system response. The performance of the protocol is analyzed through analytic and simulation models with varying system parameters such as number of nodes and channels. The performance of the new protocol is compared to a TDM-based protocol and their relative merits and demerits are examined.>

Media access control protocols for an optically interconnected star-coupled system with preallocated wavelength-division multiple-access channels are discussed. The photonic network is based on a passive star-coupled configuration in which high topological connectivity is achieved with low complexity and excellent fault tolerance. The channels are preallocated to the nodes with the proposed approach, and each node has a home channel it uses either for data packet transmission or data packet reception. The performance of a generalized random access protocol is compared to an approach based on interleaved time multiplexing. Semi-Markov analytic models are developed to investigate the performance of the two protocols. The analytic models are validated through extensive simulation. The performance is evaluated in terms of network throughput and packet delay with variations in the number of nodes, data channels, and packet generation rate.>

Media access control protocols for an optically interconnected star-coupled system with pre-allocated WDMA channels are introduced and compared. The photonic network is based on a passive star-coupled WDM–based configuration with high topological connectivity and low complexity. The channels are pre-allocated to the nodes with this approach, where each node has a home channel that it uses either for all data packet transmissions or all data packet receptions. A home channel may be shared if the number of nodes exceeds the number of channels in the system. This approach does not require both tunable transmitters and tunable receivers. The performance of a generalized random access protocol is compared to a protocol based on interleaved time multiplexing. Both protocols are designed to operate in a multiple-channel multiple-access environment and require each node to possess a tunable transmitter and a fixed (or slow tunable) receiver. Semi-markov analytic models are developed to investigate the performance of the two protocols. The analytic models are validated through simulation and performance is evaluated in terms of network throughput and packet delay with variations in system parameters.