Sarkar, Saswati
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Publication Fair Allocation of Utilities in Multirate Multicast Networks: A Framework for Unifying Diverse Fairness Objectives(2002-06-01) 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.Publication An Adaptive Strategy for Maximizing Throughput in MAC layer Wireless Multicast(2004-05-24) Chaporkar, Prasanna; Bhat, Anita; 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.Publication RIDA: Robust Intrusion Detection in Ad Hoc Networks(2005-05-02) Subhadrabandhu, Dhanant; Sarkar, Saswati; Anjum, FarooqWe focus on detecting intrusions in wireless ad hoc networks using the misuse detection technique. We allow for detection modules that periodically fail to detect attacks and also generate false positives. Combining theories of hypothesis testing and approximation algorithms, we develop a framework to counter different threats while minimizing the resource consumption. We obtain computationally simple optimal rules for aggregating and thereby minimizing the errors in the decisions of the nodes executing the intrusion detection software (IDS) modules. But, we show that the selection of the optimal set of nodes for executing the IDS is an NP-hard problem. We present a polynomial complexity selection algorithm that attains a guaranteeable approximation bound. We also modify this algorithm to allow for seamless operation in time varying topologies, and evaluate the efficacy of the approximation algorithm and its modifications using simulation. We identify a selection algorithm that attains a good balance between performance and complexity for attaining robust intrusion detection in ad hoc networks.Publication Maximum Damage Malware Attack in Mobile Wireless Networks(2010-03-01) 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.Publication Arbitrary Throughput Versus Complexity Tradeoffs in Wireless Networks Using Graph Partitioning(2008-11-01) 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 ∊.Publication A Jointly Optimum Scheduling and Memory Management for Matching Based Service(2002-12-10) Sarkar, SaswatiWe consider resource allocation in a system which must process and subsequently deliver jobs from N input terminals to N output terminals as per matching constraints. Jobs are stored in a common memory before processing and transfer. The resource allocation objective is to minimize the job loss due to memory overflow. We present optimal scheduling and memory management policies for attaining this objectives for N = 2 and symmetric traffic. We identify certain characteristics of the optimal strategy for N = 2 and asymmetric traffic, and present a near optimal heuristic for this case. We obtain a heavy traffic lower bound for the optimal discounted cost function for the general case of arbitrary N and arbitrary traffic. We use this lower bound to propose a heuristic strategy whose performance is close to the optimal strategy in this case. The policies proposed in this paper substantially outperform the existing strategy for the system, which was designed and proved to be optimal under the assumption of infinite storage.Publication Throughput and Fairness Guarantees Through Maximal Scheduling in Wireless Networks(2008-02-01) Chaporkar, Prasanna; Kar, Koushik; Luo, Xiang; Sarkar, SaswatiThe question of providing throughput guarantees through distributed scheduling, which has remained an open problem for some time, is addressed in this paper. It is shown that a simple distributed scheduling strategy, maximal scheduling, attains a guaranteed fraction of the maximum throughput region in arbitrary wireless networks. The guaranteed fraction depends on the "interference degree" of the network, which is the maximum number of transmitter–receiver pairs that interfere with any given transmitter–receiver pair in the network and do not interfere with each other. Depending on the nature of communication, the transmission powers and the propagation models, the guaranteed fraction can be lower-bounded by the maximum link degrees in the underlying topology, or even by constants that are independent of the topology. The guarantees are tight in that they cannot be improved any further with maximal scheduling. The results can be generalized to end-to-end multihop sessions. Finally, enhancements to maximal scheduling that can guarantee fairness of rate allocation among different sessions, are discussed.Publication A Framework for Misuse Detection in Ad Hoc Networks—Part I(2006-02-01) Subhadrabandhu, Dhanant; Sarkar, Saswati; Anjum, FarooqWe consider ad hoc networks with multiple, mobile intruders. We investigate the placement of the intrusion detection modules for misuse-based detection strategy. Our goal is to maximize the detection rate subject to limited availability of communication and computational resources. We mathematically formulate this problem, and show that computing the optimal solution is NP-hard. Thereafter, we propose two approximation algorithms that approximate the optimal solution within a constant factor, and prove that they attain the best possible approximation ratios. The approximation algorithms though require recomputation every time the topology changes. Thereafter, we modify these algorithms to adapt seamlessly to topological changes. We obtain analytical expressions to quantify the resource consumption versus detection rate tradeoffs for different algorithms. Using analysis and simulation, we evaluate these algorithms, and identify the appropriate algorithms for different detection rate and resource consumption tradeoffs.Publication Spectrum Auction Framework for Access Allocation in Cognitive Radio Networks(2010-12-17) Kasbekar, Guarav S.; Sarkar, SaswatiIn cognitive radio networks, there are two categories of networks on different channels: primary networks, which have high-priority access, and secondary networks, which have low-priority access. We develop an auction-based framework that allows networks to bid for primary and secondary access based on their utilities and traffic demands. The bids are used to solve the access allocation problem, which is that of selecting the primary and secondary networks on each channel either to maximize the auctioneer’s revenue or to maximize the social welfare of the bidding networks, while enforcing incentive compatibility. We first consider the case when the bids of a network depend on which other networks it will share channels with. When there is only one secondary network on each channel, we design an optimal polynomial- time algorithm for the access allocation problem based on reduction to a maximum matching problem in weighted graphs. When there can be two or more secondary networks on a channel, we show that the optimal access allocation problem is NP-complete. Next, we consider the case when the bids of a network are independent of which other networks it will share channels with. We design a polynomial-time dynamic programming algorithm to optimally solve the access allocation problem when the number of possible cardinalities of the set of secondary networks on a channel is upper-bounded. Finally, we design a polynomial-time algorithm that approximates the access allocation problem within a factor of 2 when the above upper bound does not exist.Publication Arbitrary Throughput Versus Complexity Tradeoffs in Wireless Networks using Graph Partitioning(2006-11-10) Ray, Saikat; Sarkar, SaswatiSeveral 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 and require a computation time that is 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. We subsequently develop a framework for attaining arbitrary close approximations for the maximum throughput region in arbitrary networks and interference models 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 ε > 0, the maximum throughput region can be approximated in these networks using a computation time that depends only on the maximum node degree and ε.