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Termite: A Swarm Intelligent Routing Algorithm For Mobile Wireless Ad-Hoc Networks

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Abstract

A biologically inspired algorithm is presented to route messages in mobile wireless ad-hoc networks. Such computer networks are primarily characterized by their quickly changing topologies due to frequent node mobility. The principles of swarm intelligence are used to define a probabilistic algorithm for which routing through paths of maximum utility is an emergent property. This adaptive algorithm, dubbed \emph{Termite}, uses stigmergy to reduce the amount of control traffic needed to maintain performance. Strong routing robustness is achieved through the use of multiple paths; each packet is routed randomly and independently. Once the basic operation of Termite is verified, alternative metric estimation techniques are tested via simulation. Optimal system parameters are selected by testing over orders of magnitude. A simple analytical model is built in order to explain the simulation results. The model also used to propose two heuristics for determining the optimal pheromone decay rate. All of the enhancements to Termite, now known as \emph{ReTermite}, are consolidated and tested against Ad-hoc On-demand Distance Vector (AODV), a leading ad-hoc routing algorithm. ReTermite is shown to be superior in many primary metrics and the reasons for this explained. Previous heuristic models are also compared to simulation results.

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The work presented in this thesis was made possible with the generous support of DARPA ITO under the project name, "Self-Configuring Wireless Sensor Networks," and of NSF - CRCD, Microsoft, and Hewlett Packard under the project title, "The Ad Hoc Classroom: Integrating Emerging Wireless Communications and Networking Technologies into Mainstream Computer Science and Electrical Engineering Curricula."

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2005-01-04T18:22:41Z

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Swarm Intelligence; Mobile Wireless Ad-Hoc Network

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dissertation or thesis

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