A.A. Abouzeid 2004 Publications

The problem of energy efficient image transmission over a resource constrained multi-hop wireless network is considered. Two methods of data exchange in distributed wavelet transform are proposed and investigated with respect to energy consumption and image quality. An energy-balancing distributed JPEG2000 image compression scheme which uses a combination of tiling of images and load balancing by nodes rotation is proposed. Simulation results show that the proposed scheme prolongs the system lifetime by up to 4 times and has a normalized total energy consumption comparable to centralized image compression

We consider transmitting images in a multihop wireless network with the minimal total power consumption while satisfying an end-to-end image quality constraint. Contrary to popular belief, we show that maximum compression before transmission does not always provide minimal energy consumption, especially in the case of dense sensor networks with complex signal processing algorithms. We formulate the minimal energy transmission problem as an optimization problem and present a heuristic algorithm for it. The proposed algorithm selects the optimal image compression parameters to minimize total energy dissipation given the network conditions and image quality constraints. Simulation results show up to 80% reduction in the total power consumption achieved by using the proposed adaptive algorithm compared to nonadaptive algorithms

While several cluster based routing algorithms have been proposed for ad hoc networks, there is a lack of formal mathematical analysis of these algorithms. Specifically, there is no published investigation of the relation between routing overhead on one hand and route request pattern (traffic) on the other. This paper provides a mathematical framework for quantifying the overhead of a cluster-based routing protocol. We explicitly model the application-level traffic in terms of the statistical description of the number of hops between a source and a destination. The network topology is modelled by a regular two-dimensional grid of unreliable nodes, and expressions for various components of the routing overhead are derived. The results show that clustering does not change the traffic requirement for infinite scalability compared to flat protocols, but reduces the overhead by a factor of O(1/M) where M is the cluster size. The analytic results are validated against simulations of random network topologies running a well known (D-hop max-min) clustering algorithm