A.A. Abouzeid 2005 Publications

Efficient compression and transmission of images in a resource-constrained multihop wireless network is considered. Distributed image compression is proposed as a means to overcome the computation and/or energy limitation of individual nodes by sharing the processing of tasks. It has the additional benefit of extending the overall lifetime of the network by distributing the computational load among otherwise idle processors. Two design alternatives for energy efficient distributed image compression are proposed and investigated with respect to energy consumption and image quality. Simulation results show that the proposed scheme prolongs the system lifetime at a normalized total energy consumption comparable to the centralized image compression. [All rights reserved Elsevier]

In this paper, information theoretic techniques are used to derive analytic expressions for the minimum expected length of control messages exchanged by proactive routing in a two-level hierarchical ad hoc network. Several entropy measures are introduced and used to bound the memory size necessary for the storage of the routing tables. The entropy rates of the topology sequences are used to bound the communication routing overhead-both the interior routing overhead within a cluster and the exterior routing overhead across clusters. A scalability analysis of the routing overheads with regard to the number of nodes and the cluster size is provided under three different network scaling modes. Finally, practical design issues are studied by providing the optimal cluster sizes that asymptotically minimize (i) the memory requirement for each cluster head; (ii) the total control message routing overhead

This paper presents a mathematical and simulative framework for quantifying the overhead of reactive routing protocols, such as dynamic source routing and ad hoc on-demand distance vector, in wireless variable topology (ad hoc) networks. A model of the routing-layer traffic, in terms of the statistical description of the distance between a source and a destination, is presented. The model is used to study the effect of the traffic on the routing overhead. Two network models are analyzed; a Manhattan grid model for the case of regular node placement, and a Poisson model for the case of random node placement. We focus on situations where the nodes are stationary but unreliable. For each network model, expressions of various components of the routing overhead are derived as a function of the traffic pattern. Results are compared against ns-2 simulations, which corroborate the essential characteristics of the analytical results. One of the key insights that can be drawn from the mathematical results of this paper is that it is possible to design infinitely scalable reactive routing protocols for variable topology networks by judicious engineering of the traffic patterns to satisfy the conditions presented in this paper

In this paper, we propose an 'in-network' diversity combining scheme for image transport in wireless sensor networks. We consider a wireless sensor network with both wireless link impairments and node failures. We investigate two performance metrics of the proposed image transport scheme: energy consumption and received image quality distortion. Simulation results show that the proposed image transport scheme improves the robustness to network errors at the expense of low energy overhead. This improvement is more noticeable in case of high node failure probability and long distance between the source and the destination. Our work also helps in understanding the tradeoffs between image quality distortion and energy consumption with different network parameters such as the number of hops between the source and the destination, the average channel error rate, and the average node failure rate.

In this paper we develop a model for random walk search mechanism in unstructured P2P networks. Using the model we obtain analytical expressions for the performance metrics of random walk search in terms of the popularity of the resource being searched for and the parameters of random walk. We propose an equation based adaptive search mechanism that uses estimate of popularity of a resource in order to choose the parameters of random walk such that a targeted performance level is achieved by the search. We also propose a low-overhead method for maintaining an estimate of popularity that utilizes feedback (or lack there-off) obtained from previous searches. Simulation results show that the performance of equation based adaptive search is significantly better than the non-adaptive random walk.