A.A. Abouzeid 2006 Publications

In this paper we focus on characterizing the average end-to-end delay and maximum achievable per-node throughput in random access multihop wireless ad hoc networks with stationary nodes. We present an analytical model that takes into account the number of nodes, the random packet arrival process, the extent of locality of traffic, and the back off and collision avoidance mechanisms of random access MAC. We model random access multihop wireless networks as open G/G/1 queuing networks and use diffusion approximation to evaluate closed form expressions for the average end-to-end delay. The mean service time of nodes is derived and used to obtain the maximum achievable per-node throughput. The analytical results obtained here from the queuing network analysis are discussed with regard to similarities and differences from the well established information-theoretic results on throughput and delay scaling laws in ad hoc networks. We also investigate the extent of deviation of delay and achievable throughput in a real world network from the analytical results presented in this paper. We perform extensive simulations and verify that the analytical results closely match the results obtained from simulations

In order to adapt to the time-varying nature of wireless channels, various channel-adaptive schemes have been proposed to exploit inherent spatial diversity in wireless ad hoc networks where there are usually alternate forwarding nodes available at a given forwarding node. However, existing schemes along this line are designed based on heuristics, implying room for performance enhancement. Thereby, to seek a theoretical foundation for improving spatial diversity gain, we formulate the selection of the next-hop relay as a sequential decision problem and derive a general 'optimal stopping relaying (OSR)' framework for designing such spatial-diversity schemes. As a particular example, assuming Rayleigh fading channels, we implement an OSR strategy to optimize information efficiency (IE) in a protocol stack consisting of greedy perimeter stateless routing (GPSR) and IEEE 802.11 MAC protocols. We present an analysis of the algorithm for a single node. In addition, we perform extensive simulations (using QualNet) to evaluate the end-to-end performance of the proposed forwarding strategy. The results demonstrate the superiority of OSR over other existing schemes

In this paper, we propose an 'in-network' diversity combining scheme for image transport over wireless sensor networks. We consider a wireless sensor network with both wireless link impairments and node failures. We analyze two performance metrics of the proposed image transport scheme: energy consumption and received image quality distortion. Our analysis models key aspects of the network including forward error correction, path diversity, and the multi-hop nature of ad-hoc networks. The channel model used is a two-state Markov model describing errors on the bit level. We also use a two-state Markov model of node transitions between an 'on' and 'off' state. Reed-Solomon coding is used for forward error correction. Theoretical and simulation results show the robustness improvement. This work also helps in understanding the tradeoffs between image quality distortion and energy consumption as a function of various 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. [All rights reserved Elsevier]

We study a novel 'coverage by directional sensors' problem with tunable orientations on a set of discrete targets. We propose a maximum coverage with minimum sensors (MCMS) problem in which coverage in terms of the number of targets to be covered is maximized whereas the number of sensors to be activated is minimized. We present its exact integer linear programming (ILP) formulation and an approximate (but computationally efficient) centralized greedy algorithm (CGA) solution. These centralized solutions are used as baselines for comparison. Then we provide a distributed greedy algorithm (DGA) solution. By incorporating a measure of the sensors residual energy into DGA, we further develop a sensing neighborhood cooperative sleeping (SNCS) protocol which performs adaptive scheduling on a larger time scale. Finally, we evaluate the properties of the proposed solutions and protocols in terms of providing coverage and maximizing network lifetime through extensive simulations. Moreover, for the case of circular coverage, we compare against the best known existing coverage algorithm

In this paper we focus on characterizing the average end-to-end delay and maximum achievable per-node throughput in random access multihop wireless ad hoc networks with stationary nodes. We present an analytical model that takes into account the number of nodes, the random packet arrival process, the extent of locality of traffic, and the back off and collision avoidance mechanisms of random access MAC. We model random access multihop wireless networks as open G/G/1 queuing networks and use the diffusion approximation in order to evaluate closed form expressions for the average end-to-end delay. The mean service time of nodes is evaluated and used to obtain the maximum achievable per-node throughput. The analytical results obtained here from the queuing network analysis are discussed with regard to similarities and differences from the well established information-theoretic results on throughput and delay scaling laws in ad hoc networks. We perform extensive simulations and verify that the analytical results closely match the results obtained from simulations.

Mobile sensors cover more area over a period of time than the same number of stationary sensors. However, the quality of coverage achieved by mobile sensors depends on the velocity, mobility pattern, number of mobile sensors deployed and the dynamics of the phenomenon being sensed. The gains attained by mobile sensors over static sensors and the optimal motion strategies for mobile sensors are not well understood. In this paper we consider the problem of event capture using mobile sensors. The events of interest arrive at certain points in the sensor field and fade away according to arrival and departure time distributions. An event is said to be captured if it is sensed by one of the mobile sensors before it fades away. For this scenario we analyze how the quality of coverage scales with the velocity, path and number of mobile sensors. We characterize the cases where the deployment of mobile sensors has no advantage over static sensors and find the optimal velocity pattern that a mobile sensor should adopt. We also present algorithms for two motion planning problems: (i) for a single sensor, what is the minimum speed and sensor trajectory required to satisfy a bound on event loss probability and (ii) for sensors with fixed speed, what is the minimum number of sensors required to satisfy a bound on event loss probability. When events occur only along a line or a closed curve our algorithms return optimal velocity for the minimum velocity problem. For the minimum sensor problem, the number of sensors used is within a factor two of the optimal solution. For the case where the events occur at arbitrary points on a plane we present heuristic algorithms for the above motion planning problems and bound their performance with respect to the optimal. The results of this paper have wide range of applications in areas like surveillance, wildlife monitoring, hybrid sensor networks and under-water sensor networks.

We present an information theoretic analysis of the minimum routing overhead incurred for reliable routing of packets using location-based routing. We formulate the minimum routing overhead problem as a rate-distortion problem and derive a lower bound on the minimum routing overhead incurred. We also characterize the deficit in transport capacity caused by the routing overheads. It is observed that for high mobility and packet arrival rates, the routing overheads may consume the entire capacity of a network.

Wireless mesh networks (WMNs) are emerging as a popular means of providing connectivity to communities in both affluent and poor parts of the world. The presence of backbone mesh routers and the use of multiple channels and interfaces allow mesh networks to have better capacity than infrastructure-less multihop ad hoc networks. In this paper we characterize the average delay and capacity in WMNs that utilize random medium access (MAC).We model residential area WMNs as open G/G/1 queuing networks. The analytical model takes into account the density of the mesh clients and mesh routers, the random packet arrival process, the degree of locality of traffic and the collision avoidance mechanism of random access MAC. The diffusion approximation method is used to obtain closed form expressions for (a) end-to-end packet delay and (b) maximum achievable per-node throughput. The analytical results describe how the performance of WMNs scales with the number of mesh routers and clients. The results obtained from simulations agree closely with the analytical results. For the asymptotic case (as the network size grows indefinitely), we discuss how the results obtained using the proposed queuing network framework compare against previous well known results on asymptotic capacity of infrastructure-less ad hoc networks.

In this paper we focus on characterizing the average end-to-end delay and maximum achievable per-node throughput in random access multihop wireless ad hoc networks with stationary nodes. We present an analytical model that takes into account the number of nodes, the random packet arrival process, the extent of locality of traffic, and the back off and collision avoidance mechanisms of random access MAC. We model random access multihop wireless networks as open G/G/1 queuing networks and use diffusion approximation to evaluate closed form expressions for the average end-to-end delay. The mean service time of nodes is derived and used to obtain the maximum achievable per-node throughput. The analytical results obtained here from the queuing network analysis are discussed with regard to similarities and differences from the well established information-theoretic results on throughput and delay scaling laws in ad hoc networks. We also investigate the extent of deviation of delay and achievable throughput in a real world network from the analytical results presented in this paper. We perform extensive simulations and verify that the analytical results closely match the results obtained from simulations.

In this paper, we study a novel “coverage by directional sensors” problem with tunable orientations on a set of discrete targets. We propose a Maximum Coverage with Minimum Sensors (MCMS) problem in which coverage in terms of the number of targets to be covered is maximized whereas the number of sensors to be activated is minimized. We present its exact Integer Linear Programming (ILP) formulation and an approximate (but computationally efficient) centralized greedy algorithm (CGA) solution. These centralized solutions are used as baselines for comparison. Then we provide a distributed greedy algorithm (DGA) solution. By incorporating a measure of the sensors residual energy into DGA, we further develop a Sensing Neighborhood Cooperative Sleeping (SNCS) protocol which performs adaptive scheduling on a larger time scale. Finally we evaluate the proposed solutions and protocol in terms of providing coverage and maximizing network lifetime through extensive simulations.

.

Link reversal routing (LRR) is a local, distributed, and low-overhead technique used to maintain loop free routes in mobile wireless ad hoc networks. We explore the problem of load balancing the packet traffic in the network when using the LRR created routes. We study a fundamental LRR algorithm and identify usual situations which cause the load to be unbalanced. We propose three modifications to the LRR algorithm such that the load is distributed in a more uniform manner. The modifications preserve all the desirable qualities of LRR algorithms such as loop free routes, local response to topology change, low overhead and are completely distributed in nature. We perform simulations in order to evaluate the performance of the proposed modifications for both single-path and multi-path scenarios. The simulation results show that the modifications enable LRR to provide a much improved load balancing and ensure higher network lifetime.