Parvathinathan Venkitasubramaniam

Signal processing in random access

In this paper, a cross-layer view for roles of signal processing in random access network and vice versa is presented. The two cases where cross-layer design has a quantifiable impact on system performance are discussed. The first case is a small network (such as wireless LAN) where a few nodes with bursty arrivals communicate with an access point. The design objective is to achieve the highest throughput among users with variable rate and delay constraints. The impact of PHY layer design on MAC protocol is examined and illustrates a tradeoff between allocating resources to the PHY layer and to MAC layer. The second case, in contrast, deals with large-scale sensor networks where each node carries little information but is severely constrained by its computation and communication complexity and most importantly, battery power. This paper emphasizes that the design of signal processing algorithms must take into account the role of MAC and the nature of random arrivals and bursty transmissions.

Sensor networks with mobile access: optimal random access and coding

We consider random access and coding schemes for sensor networks with mobile access (SENMA). Using an orthogonal code-division multiple access (CDMA) as the physical layer, an opportunistic ALOHA (O-ALOHA) protocol that utilizes channel state information is proposed. Under the packet capture model and using the asymptotic throughput as the performance metric, we show that O-ALOHA approaches the throughput equal to the spreading gain with an arbitrarily small power at each sensor. This result implies that O-ALOHA is close to the optimal centralized scheduling scheme for the orthogonal CDMA networks. When side information such as location is available, the transmission control is modified to incorporate either the distribution or the actual realization of the side information. Convergence of the throughput with respect to the size of the network is analyzed. For networks allowing sensor collaborations, we combine coding with random access by proposing two coded random access schemes: spreading code dependent and independent transmissions. In the low rate regime, the spreading code independent transmission has a larger random coding exponent (therefore, faster decay of error probability) than that of the spreading code dependent transmission. On the other hand, the spreading code dependent transmission gives higher achievable rate.

Anonymous Networking Amidst Eavesdroppers

The problem of security against packet timing based traffic analysis in wireless networks is considered in this work. An analytical measure of ldquoanonymityrdquo of routes in eavesdropped networks is proposed using the information-theoretic equivocation. For a physical layer with orthogonal transmitter directed signaling, scheduling and relaying techniques are designed to maximize achievable network performance for any desired level of anonymity. The network performance is measured by the total rate of packets delivered from the sources to destinations under strict latency and medium access constraints. In particular, analytical results are presented for two scenarios: For a single relay that forwards packets from users, relaying strategies are provided that minimize the packet drops when the source nodes and the relay generate independent transmission schedules. A relay using such an independent scheduling strategy is undetectable by an eavesdropper and is referred to as a covert relay. Achievable rate regions are characterized under strict and average delay constraints on the traffic, when schedules are independent Poisson processes. For a multihop network with an arbitrary anonymity requirement, the problem of maximizing the sum-rate of flows (network throughput) is considered. A randomized selection strategy to choose covert relays as a function of the routes is designed for this purpose. Using the analytical results for a single covert relay, the strategy is optimized to obtain the maximum achievable throughput as a function of the desired level of anonymity. In particular, the throughput-anonymity relation for the proposed strategy is shown to be equivalent to an information-theoretic rate-distortion function.

Opportunistic ALOHA and cross layer design for sensor networks

We propose a novel distributed medium access control scheme called opportunistic ALOHA for reachback in sensor networks with mobile agents. Each sensor transmits its information with a probability that is a function of its channel state (propagation channel gain). This function called transmission control is then designed under the assumption that orthogonal CDMA is employed to transmit information. The gains achieved in the throughput by use of transmission control are analyzed and evaluated numerically. The variation of the average number of transmitting users with distance from the collecting agent is analyzed. The proposed reachback protocol can be used in a variety of sensor network applications. We end by giving two examples of how the reachback protocol can be used by the sensor network to transmit information reliably to the collecting agent. The maximum rate at which the information can be reliably transmitted with the proposed schemes is evaluated as a function of the performance parameters of the reachback protocol.

Quantization for Maximin ARE in Distributed Estimation

We consider the design of optimal quantizers for the distributed estimation of a deterministic parameter. In particular, we design deterministic scalar quantizers to maximize the minimum asymptotic relative efficiency (ARE) between quantized and unquantized ML estimators. We first design identical quantizers using the class of score-function quantizers (SFQ). We show that the structure of SFQs generally depend on the parameter value, but can be expressed as thresholds on the sufficient statistic for a large class of distributions. We provide a convergent iterative algorithm to obtain the best SFQ that maximizes the minimum ARE for distributions of that class. We compare the performance of the optimal SFQ with a general quantizer designed without making any restrictions on the structure. This general quantizer is hard to implement due to lack of structure, but is optimal if the iterative design algorithm does not encounter local minima. Through numerical simulations, we illustrate that the two quantizers designed are identical. In other words, the optimal quantizer structure is that of an SFQ. For a distributed estimation setup, designing identical quantizers is shown to be suboptimal. We, therefore, propose a joint multiple quantizer design algorithm based on a person-by-person optimization technique employing the SFQ structure. Using numerical examples, we illustrate the gain in performance due to designing nonidentical quantizers.

Anonymous Networking with Minimum Latency in Multihop Networks

The problem of security against timing based traffic analysis in multihop networks is considered in this work. In particular, the relationship between the level of anonymity provided and the quality of service, as measured by network latency, is analyzed theoretically. Using an information theoretic measure of anonymity of routes in eavesdropped networks is considered, and packet scheduling strategies are designed to guarantee any desired level of anonymity. In particular, for individual relays, scheduling strategies based on mixing are designed so that the incoming and outgoing transmission epochs do not reveal any information. The proposed strategies utilize a limited fraction of dummy transmissions, and a significant reduction in packet latency at individual relays is demonstrated analytically for Poisson distributed arrivals. To minimize overall network latency, a randomized selection strategy is considered to choose the set of relays that use the designed scheduling strategies. The random selection is optimized for the desired level of anonymity using a well known distortion rate optimization in information theory. The tradeoff between overall network latency and anonymity in the network is characterized for centralized and decentralized scheduling strategies.

On the anonymity of Chaum mixes

The information-theoretic analysis of Chaum mixing under latency constraints is considered. Mixes are relay nodes that collect packets from multiple users and modify packet timings to prevent an eavesdropper from identifying the sources of outgoing packets. In this work, an entropy-based metric of anonymity is proposed to quantify the performance of a mixing strategy under strict delay constraints. Inner and outer bounds on the maximum achievable anonymity are characterized as functions of traffic load and the delay constraint. The bounds are shown to have identical first derivatives at low traffic loads.

Quantization For Distributed Estimation in Large Scale Sensor Networks

We study the problem of quantization for distributed parameter estimation in large scale sensor networks. Assuming a maximum likelihood estimator at the fusion center, we show that the Fisher information is maximized by a score-function quantizer. This provides a tight bound on best possible MSE for any unbiased estimator. Furthermore, we show that for a general convex metric, the optimal quantizer belongs to the class of score function quantizers. We also discuss a few practical applications of our results in optimizing estimation performance in distributed and temporal estimation problems

Toward an analytical approach to anonymous wireless networking

Communications in a wireless network are susceptible to unauthorized traffic analysis by eavesdroppers. Although cryptography can protect the contents of communication, the transmission times of packets alone can reveal significant networking information such as source- destination pairs and routes of traffic flow. This article focuses on analytical approaches to anonymous networking for the prevention of information retrieval through packet timing analysis. In particular, an analytical measure for route anonymity is proposed using information theoretic equivocation. Based on the metric, provably anonymous countermeasures are described for wireless ad hoc and sensor networks, where traffic is subjected to strict constraints on medium access and latency. A key objective is to bridge a long standing gap between the information theoretic approach to secrecy in communication, and a more pragmatic approach of Chaum mixing used in anonymous systems on the Internet. The efficacy of the proposed approach is demonstrated using an orthogonal transmitter directed signaling network.

A game-theoretic approach to anonymous networking

Anonymous wireless networking is studied when an adversary monitors the transmission timing of an unknown subset of the network nodes. For a desired quality of service (QoS), as measured by network throughput, the problem of maximizing anonymity is investigated from a game-theoretic perspective. Quantifying anonymity using conditional entropy of the routes given the adversarys observation, the problem of optimizing anonymity is posed as a two-player zero-sum game between the network designer and the adversary: The task of the adversary is to choose a subset of nodes to monitor so that anonymity of routes is minimum, whereas the task of the network designer is to maximize anonymity by choosing a subset of nodes to evade flow detection by generating independent transmission schedules. In this two-player game, it is shown that a unique saddle-point equilibrium exists for a general category of finite networks. At the saddle point, the strategy of the network designer is to ensure that any subset of nodes monitored by the adversary reveals an identical amount of information about the routes. For a specific class of parallel relay networks, the theory is applied to study the optimal performance tradeoffs and equilibrium strategies. In particular, when the nodes employ transmitter-directed signaling, the tradeoff between throughput and anonymity is characterized analytically as a function of the network parameters and the fraction of nodes monitored. The results are applied to study the relationships between anonymity, the fraction of monitored relays, and the fraction of hidden relays in large networks.