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PublicationArbitrary Throughput Versus Complexity Tradeoffs in Wireless Networks Using Graph Partitioning(2008-11-01) Sarkar, Saswati; Sarkar, Saswati; Ray, SaikatSeveral policies have recently been proposed for attaining the maximum throughput region, or a guaranteed fraction thereof, through dynamic link scheduling. Among these policies, the ones that attain the maximum throughput region require a computation time which is linear in the network size, and the ones that require constant or logarithmic computation time attain only certain fractions of the maximum throughput region. In contrast, in this paper we propose policies that can attain any desirable fraction of the maximum throughput region using a computation time that is largely independent of the network size. First, using a combination of graph partitioning techniques and Lyapunov arguments, we propose a simple policy for tree topologies under the primary interference model that requires each link to exchange only 1 bit information with its adjacent links and approximates the maximum throughput region using a computation time that depends only on the maximum degree of nodes and the approximation factor. Then we develop a framework for attaining arbitrary close approximations for the maximum throughput region in arbitrary networks, and use this framework to obtain any desired tradeoff between throughput guarantees and computation times for a large class of networks and interference models. Specifically, given any ∊ ≻ 0, the maximum throughput region can be approximated in these networks within a factor of 1- ∊ using a computation time that depends only on the maximum node degree and ∊. PublicationMaximum Damage Malware Attack in Mobile Wireless Networks(2010-03-01) Khouzani, MHR; Sarkar, Saswati; Altman, Eitan; Khouzani, MHR; Sarkar, Saswati; Altman, EitanMalware attacks constitute a serious security risk that threatens to slow down the large scale proliferation of wireless applications. As a first step towards thwarting this security threat, we seek to quantify the maximum damage inflicted on the system owing to such outbreaks and identify the most vicious attacks. We represent the propagation of malware in a battery-constrained mobile wireless network by an epidemic model in which the worm can dynamically control the rate at which it kills the infected node and also the transmission range and/or the media scanning rate. At each moment of time, the worm at each node faces the following trade-offs: (i) using larger transmission range and media scanning rate to accelerate its spread at the cost of exhausting the battery and thereby reducing the overall infection propagation rate in the long run or (ii) killing the node to inflict a large cost on the network, however at the expense of loosing the chance of infecting more susceptible nodes at later times. We mathematically formulate the decision problems and utilize Pontryagin Maximum Principle from optimal control theory to quantify the damage that the malware can inflict on the network by deploying optimum decision rules. Next, we establish structural properties of the optimal strategy of the attacker over time. Specifically, we prove that it is optimal for the attacker to defer killing of the infective nodes in the propagation phase for a certain time and then start the slaughter with maximum effort. We also show that in the optimal attack policy, the battery resources are used according to a decreasing function of time, i.e., mostly during the initial phase of the outbreak. Finally, our numerical investigations reveal a framework for identifying intelligent defense strategies that can limit the damage by appropriately selecting network parameters. PublicationA Framework for Routing and Congestion Control for Multicast Information Flows(2002-10-01) Sarkar, Saswati; Sarkar, Saswati; Tassiulas, LeandrosWe propose a new multicast routing and scheduling algorithm called multipurpose multicast routing and scheduling algorithm (MMRS). The routing policy load balances among various possible routes between the source and the destinations, basing its decisions on the message queue lengths at the source node. The scheduling is such that the flow of a session depends on the congestion of the next hop links. MMRS is throughput optimal. In addition, it has several other attractive features. It is computationally simple and can be implemented in a distributed, asynchronous manner. It has several parameters which can be suitably modified to control the end-to-end delay and packet loss in a topology-specific manner. These parameters can be adjusted to offer limited priorities to some desired sessions. MMRS is expected to play a significant role in end-to-end congestion control in the multicast scenario. PublicationImproving Performance Through Channel Diversity in the Presence of Bursty Losses(2005-08-29) Guérin, Roch A; Sarkar, Saswati; Guérin, Roch A; Sarkar, SaswatiAs more applications migrate to IP networks, ensuring a consistent level of service is increasingly important. One option is for the network to offer service guarantees. Another is to leverage the path diversity that the Internet intrinsically offers. Our focus is on understanding if and when one can indeed take advantage of multiple disjoint paths to improve performance. We consider an environment where loss patterns are bursty and where coding is used to provide robustness against packet losses. We assume that only long-term loss statistics are known about each path, and we seek to identify the best strategy for sending packets over the available paths. Our contributions are two-fold. First we demonstrate that even with minimal knowledge of channel characteristics and using simple transmission policies, path diversity can help significantly improve performance. Second, we derive an efficient method for identifying optimal policies, and more importantly characterize when having access to multiple paths can be of benefit. PublicationAn Adaptive Strategy for Maximizing Throughput in MAC layer Wireless Multicast(2004-05-24) Chaporkar, Prasanna; Sarkar, Saswati; Sarkar, SaswatiBandwidth efficiency of wireless multicast can be improved substantially by exploiting the fact that several receivers can be reached at the MAC layer by a single transmission. The multicast nature of the transmissions, however, introduces several design challenges, and systematic design approaches that have been used effectively in unicast and wireline multicast do not apply in wireless multicast. For example, a transmission policy that maximizes the stability region of the network need not maximize the network throughput. Therefore, the objective is to design a policy that decides when a sender should transmit in order to maximize the system throughput subject to maintaining the system stability. We present a sufficient condition that can be used to establish the throughput optimality of a stable transmission policy. We subsequently design an adaptive stable policy that allows a sender to decide when to transmit using simple computations based only on limited information about current transmissions in its neighborhood, and without using any information about the network statistics. The proposed policy attains the same throughput as the optimal offline stable policy that uses in its decision process past, present, and even future network states. We prove the throughput optimality of this policy using the suffi- cient condition and the large deviation results. We present a MAC protocol for acquiring the local information necessary for executing this policy, and implement it in ns-2. The performance evaluations demonstrate that the optimal strategy significantly outperforms the existing approaches in adhoc networks consisting of several multicast and unicast sessions. PublicationFair Allocation of Utilities in Multirate Multicast Networks: A Framework for Unifying Diverse Fairness Objectives(2002-06-01) Sarkar, Saswati; Sarkar, Saswati; Tassiulas, LeandrosWe study fairness in a multicast network. We assume that different receivers of the same session can receive information at different rates. We study fair allocation of utilities, where utility of a bandwidth is an arbitrary function of the bandwidth. The utility function is not strictly increasing, nor continuous in general. We discuss fairness issues in this general context. Fair allocation of utilities can be modeled as a nonlinear optimization problem. However, nonlinear optimization techniques do not terminate in a finite number of iterations in general. We present an algorithm for computing a fair utility allocation. Using specific fairness properties, we show that this algorithm attains global convergence and yields a fair allocation in polynomial number of iterations. PublicationEconomy of Spectrum Access in Timy Varying Multichannel Networks(2010-10-01) Khouzani, M.H.R.; Sarkar, Saswati; Khouzani, M.H.R.; Sarkar, SaswatiWe consider a wireless network consisting of two classes of potentially mobile users: primary users and secondary users. Primary users license frequency channels and transmit in their respective bands as required. Secondary users resort to unlicensed access of channels that are not used by their primary users. Primaries impose access fees on the secondaries which depend on access durations and may be different for different primary channels and different available communication rates in the channels. The available rates to the secondaries change with time depending on the usage status of the primaries and the random access quality of channels. Secondary users seek to minimize their total access cost subject to stabilizing their queues whenever possible. Our first contribution is to present a dynamic link scheduling policy that attains this objective. The computation time of this policy, however, increases exponentially with the size of the network. We next present an approximate scheduling scheme based on graph partitioning that is distributed and attains arbitrary trade-offs between aggregate access cost and computation times of the schedules, irrespective of the size of the network. Our performance guarantees hold for general arrival and primary usage statistics and multihop networks. Each secondary user is, however, primarily interested in minimizing the cost it incurs, rather than in minimizing the aggregate cost. Thus, it will schedule its transmissions so as to minimize the aggregate cost only if it perceives that the aggregate cost is shared among the users as per a fair cost sharing scheme. Using concepts from cooperative game theory, we develop a rational basis for sharing the aggregate cost among secondary sessions and present a cost sharing mechanism that conforms to the above basis. PublicationBack Pressure Based Multicast Scheduling for Fair Bandwidth Allocation(2005-09-01) Sarkar, Saswati; Sarkar, Saswati; Tassiulas, LeandrosWe study the fair allocation of bandwidth in multicast networks with multirate capabilities. In multirate transmission, each source encodes its signal in layers. The lowest layer contains the most important information and all receivers of a session should receive it. If a receiver’s data path has additional bandwidth, it receives higher layers which leads to a better quality of reception. The bandwidth allocation objective is to distribute the layers fairly. We present a computationally simple, decentralized scheduling policy that attains the maxmin fair rates without using any knowledge of traffic statistics and layer bandwidths. This policy learns the congestion level from the queue lengths at the nodes, and adapts the packet transmissions accordingly. When the network is congested, packets are dropped from the higher layers; therefore, the more important lower layers suffer negligible packet loss. We present analytical and simulation results that guarantee the maxmin fairness of the resulting rate allocation, and upper bound the packet loss rates for different layers. PublicationA coalitional game model for spectrum pooling in wireless data access networks(2008-01-27) Sarkar, Saswati; Sarkar, Saswati; Singh, Chandramani; Kumar, AnuragWe consider a setting in which several operators offer downlink wireless data access services in a certain geographical region. Each operator deploys several base stations or access points, and registers some subscribers. In such a situation, if operators pool their infrastructure, and permit the possibility of subscribers being served by any of the cooperating operators, then there can be overall better user satisfaction, and increased operator revenue. We use coalitional game theory to investigate such resource pooling and cooperation between operators.We use utility functions to model user satisfaction, and show that the resulting coalitional game has the property that if all operators cooperate (i.e., form a grand coalition) then there is an operating point that maximizes the sum utility over the operators while providing the operators revenues such that no subset of operators has an incentive to break away from the coalition. We investigate whether such operating points can result in utility unfairness between users of the various operators. We also study other revenue sharing concepts, namely, the nucleolus and the Shapely value. Such investigations throw light on criteria for operators to accept or reject subscribers, based on the service level agreements proposed by them. We also investigate the situation in which only certain subsets of operators may be willing to cooperate. PublicationChannel Assignment Algorithms Satisfying Cochannel and Adjacent Channel Reuse Constraints in Cellular Mobile Networks(2002-09-01) Sarkar, Saswati; Sarkar, Saswati; Sivarajan, Kumar NImproved channel assignment algorithms for cellular networks were designed by modeling the interference constraints in terms of a hypergraph . However, these algorithms only considered cochannel reuse constraints. Receiver filter responses impose restrictions on simultaneous adjacent channel usage in the same cell or in neighboring cells. We first present some heuristics for designing fixed channel assignment algorithms with a minimum number of channels satisfying both cochannel and adjacent channel reuse constraints. An asymptotically tight upper bound for the traffic carried by the system in the presence of arbitrary cochannel and adjacent channel use constraints was developed in . However, this bound is computationally intractable even for small systems like a regular hexagonal cellular system of 19 cells. We have obtained approximations to this bound using the optimal solutions for cochannel reuse constraints only and a further graph theoretic approach. Our approximations are computationally much more efficient and have turned out to track very closely the exact performance bounds in most cases of interest.