Swastik Brahma

A Game Theoretic Framework for Distributed Self-Coexistence Among IEEE 802.22 Networks

The cognitive radio based IEEE 802.22 wireless regional area network (WRAN) is designed to operate in the under-utilized TV bands by detecting and avoiding primary TV transmission bands in a timely manner. Such networks, deployed by competing wireless service providers, would have to self-coexist by accessing different parts of the available spectrum in a distributed manner. Obviously, the goal of every network is to acquire a clear spectrum chunk free of interference from other IEEE 802.22 networks so as to satisfy the QoS of the services delivered to the end-users. In this paper, we study the distributed WRAN self-coexistence problem from a minority game theoretic perspective. We model the spectrum band switching game where the networks try to minimize their cost in finding a clear band. We propose a mixed strategy that the competing networks must adhere to in order to achieve the Nash equilibrium. Simulation experiments have also been conducted and results corroborate with the theoretical analysis.

Enhancements to Cognitive Radio Based IEEE 802.22 Air-Interface

The IEEE 802.22 standard for wireless regional area network is the first standard for cognitive radio that tries to harness the idle or under-utilized spectrum allocated for TV bands. Two major challenges that are faced by IEEE 802.22 are (i) the issue of self co-existence and (ii) the hidden incumbent problem. In this paper, we discuss these two challenges and provide enhancements to the existing IEEE 802.22 air-interface. We use a graph theoretic technique and propose utility graph coloring for allocating spectrum to different IEEE 802.22 base stations so that they can co-exist. The allocation is done such that objectives such as throughput maximization, proportional fairness, and complete fairness are met. We also propose the use of dynamic multiple broadcast messages that resolves the contention among various consumer premise equipments and alleviates the hidden incumbent problem. Through simulation results, we show that the proposed techniques increase the system spectrum utilization and reduce connection set-up delay.

Congestion control and fairness in wireless sensor networks

In this paper we propose a distributed congestion control algorithm for tree based communications in wireless sensor networks, that seeks to adaptively assign a fair and efficient transmission rate to each node. In our algorithm, each node monitors its aggregate output and input traffic rates. Based on the difference of the two, a node then decides either to increase or decrease the bandwidth allocable to a flow originating from itself and to those being routed through it. Since the application requirements in sensor network follows no common trait, our design abstracts the notion of fairness, allowing for the development of a generic utility controlling module. Such separation of the utility and fairness controlling modules enables each one to use a separate control law, thereby portraying a more flexible design. The working of our congestion control is independent of the underlying routing algorithm and is designed to adapt to changes in the underlying routing topology. We evaluate the performance of the algorithm via extensive simulations using an event-driven packet level simulator. The results suggest that the proposed protocol acquires a significantly high goodput of around 95% of the actual transmission rate, converges quickly to the optimal rate, and attains the desired fairness.

Optimal distributed detection in the presence of Byzantines

This paper considers the problem of optimal distributed detection with independent identical sensors in the presence of Byzantine attacks. By considering the attacker to be strategic in nature, we address the issue of designing the optimal fusion rule and the local sensor thresholds that minimize the probability of error at the fusion center (FC).We first consider the problem of finding the optimal fusion rule under the constraint of fixed local sensor thresholds and fixed Byzantine strategy. Next, we consider the problem of joint optimization of the fusion rule and local sensor thresholds for a fixed Byzantine strategy. Then we extend these results to the scenario where both the FC and the Byzantine attacker act in a strategic manner to optimize their own utilities. We model the strategic behavior of the FC and the attacker using game theory and show the existence of Nash Equilibrium. We also provide numerical results to gain insights into the solution.

Self-coexistence among interference-aware IEEE 802.22 networks with enhanced air-interface

Abstract IEEE 802.22 is a cognitive radio-based Wireless Regional Area Network (WRAN) standard that allows opportunistic access to idle or underutilized sub-900 MHz TV bands by unlicensed (secondary) networks. Though most of the standard has been laid out, there is still no consensus on the channel access policies for the uncoordinated secondary networks. Hence, the possibility of interference always exists. Moreover, in the absence of any control channel, the problem of establishing a connection becomes even more challenging, more so in the presence of hidden incumbents. In this paper, we address the above-mentioned self-coexistence problem among the IEEE 802.22 networks and provide novel solutions to improve the IEEE 802.22 air-interface. We use an interference-aware graph-theoretic technique and propose Utility Graph Coloring (UGC) for allocating spectrum to different IEEE 802.22 base stations such that they can coexist with the least interference, thereby maximizing the system spectrum utilization. We also consider allocation fairness among the networks in terms of minimal fairness, proportional fairness, and complete fairness. With the spectrum allocated to the IEEE 802.22 networks, we propose enhancements to the IEEE 802.22 MAC layer to maximize spectrum usage efficiency. In particular, we make use of aggregation and fragmentation of channel carriers, dynamic multiple broadcast messages, and aggressive contention resolution. Through simulation experiments, we show how the proposed techniques can increase the spectral efficiency and spectrum utilization, and still maintain fairness. We show that the spectral efficiency obtained with UGC is more than three times compared to the existing standard. The average number of collisions among the IEEE 802.22 enabled devices is significantly reduced, resulting in low connection setup delay, enhanced system performance, and higher spectrum allocation for data transmissions.

Traffic management in wireless sensor networks: Decoupling congestion control and fairness

In this paper, we propose a distributed congestion control algorithm for tree based communications in wireless sensor networks, that seeks to adaptively assign a fair and efficient transmission rate to each node. In our algorithm, each node monitors its aggregate output and input traffic rate. Based on the difference of the two, a node then decides to increase (if the output rate is more) or decrease (if the input rate is more) the bandwidth allocable to a flow originating from itself and to those being routed through it. Since the application requirements in sensor network follow no common trait, our design abstracts the notion of fairness, allowing for the development of a generic utility controlling module. Such separation of the utility and fairness controlling modules enable each one to use a separate control law, thereby portraying a more flexible design. The working of our congestion control is independent of the underlying routing algorithm and is designed to adapt to changes in the underlying routing topology. We evaluate the performance of the algorithm via extensive simulations using an event-driven packet level simulator. The results suggest that the proposed protocol acquires a significantly high goodput of around 95% of the actual transmission rate, converges quickly to the optimal rate, and attains the desired fairness.

Optimal Byzantine attacks on distributed detection in tree-based topologies

This paper considers the problem of optimal Byzantine attacks or data falsification attacks on distributed detection mechanism in tree-based topologies. First, we show that when more than a certain fraction of individual node decisions are falsified, the decision fusion scheme becomes completely incapable. Second, under the assumption that there is a cost associated with attacking each node (which represent resources invested in capturing a node or cloning a node in some cases), we address the problem of minimum cost Byzantine attacks and formulate it as the bounded knapsack problem (BKP). An algorithm to solve our problem in polynomial time is presented. Numerical results provide insights into our solution.

Distributed Bayesian Detection in the Presence of Byzantine Data

In this paper, we consider the problem of distributed Bayesian detection in the presence of Byzantines in the network. It is assumed that a fraction of the nodes in the network are compromised and reprogrammed by an adversary to transmit false information to the fusion center (FC) to degrade detection performance. The problem of distributed detection is formulated as a binary hypothesis test at the FC based on 1-bit data sent by the sensors. The expression for minimum attacking power required by the Byzantines to blind the FC is obtained. More specifically, we show that above a certain fraction of Byzantine attackers in the network, the detection scheme becomes completely incapable of utilizing the sensor data for detection. We analyze the problem under different attacking scenarios and derive results for different non-asymptotic cases. It is found that existing asymptotics-based results do not hold under several non-asymptotic scenarios. When the fraction of Byzantines is not sufficient to blind the FC, we also provide closed form expressions for the optimal attacking strategies for the Byzantines that most degrade the detection performance.

Power control with jammer location uncertainty: A Game Theoretic perspective

This paper presents a Game Theoretic framework for the analysis of distributed spectrum sharing in a Cognitive Radio Network (CRN) prone to jamming attacks. We consider competitive interactions between a selfish secondary user (SU) transmitter-receiver pair and a jammer under realistic physical interference constraints. Assuming incomplete knowledge of the jammers location in the network, the SU chooses its transmission power strategy, subject to a total power budget, with the objective of satisfying a minimum signal-to-interference plus noise ratio (SINR) constraint at the intended receiver.We model the strategic power allocation problem as an incomplete and imperfect information game and investigate self-enforcing strategies of the SU and the jammer. The solution of the game corresponds to Nash Equilibria (NE) points. We carry out the equilibrium analysis for this game by considering the mixed strategy solution space and provide closed form expressions of the equilibria points. Numerical examples are presented for illustration.

Distributed Detection in Tree Topologies With Byzantines

In this paper, we consider the problem of distributed detection in tree topologies in the presence of Byzantines. The expression for minimum attacking power required by the Byzantines to blind the fusion center (FC) is obtained. More specifically, we show that when more than a certain fraction of individual node decisions are falsified, the decision fusion scheme becomes completely incapable. We obtain closed-form expressions for the optimal attacking strategies that minimize the detection error exponent at the FC. We also look at the possible countermeasures from the FCs perspective to protect the network from these Byzantines. We formulate the robust topology design problem as a bi-level program and provide an efficient algorithm to solve it. We also provide some numerical results to gain insights into the solution.