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dc.contributor.authorRahat, Alma As-Aad Mohammad
dc.contributor.authorEverson, Richard M.
dc.contributor.authorFieldsend, Jonathan E.
dc.date.accessioned2015-04-29T14:20:51Z
dc.date.issued2015-09-01
dc.description.abstractMesh network topologies are becoming increasingly popular in battery powered wireless sensor networks, primarily due to the extension of network range. However, multi-hop mesh networks suffer from higher energy costs, and the routing strategy employed directly affects the lifetime of nodes with limited energy resources. Hence when planning routes there are trade-offs to be considered between individual and system-wide battery lifetimes. We present a multi-objective routing optimisation approach using hybrid evolutionary algorithms to approximate the optimal trade-off between minimum lifetime and the average lifetime of nodes in the network. In order to accomplish this combinatorial optimisation rapidly, our approach prunes the search space using k-shortest path pruning and a graph reduction method which finds candidate routes promoting long minimum lifetimes. When arbitrarily many routes from a node to the base station are permitted, optimal routes may be found as the solution to a well-known linear program. We present an evolutionary algorithm that finds good routes when each node is allowed only a small number of paths to the base station. On a real network deployed in the Victoria & Albert Museum, London, these solutions, using only three paths per node, are able to achieve minimum lifetimes of over 99% of the optimum linear program solution’s time to first sensor battery failure.en_GB
dc.description.sponsorshipKnowledge Transfer Partnership awarded to the University of Exeter and the IMC Group Ltd,en_GB
dc.identifier.citationVol. 23 (3), pp. 481-507en_GB
dc.identifier.doi10.1162/EVCO_a_00151
dc.identifier.grantnumberKTP008748en_GB
dc.identifier.urihttp://hdl.handle.net/10871/17056
dc.language.isoenen_GB
dc.publisherMIT Pressen_GB
dc.subjectMesh networksen_GB
dc.subjectshortest pathen_GB
dc.subjectevolutionary algorithmsen_GB
dc.subjectmulti-objective optimisationen_GB
dc.subjectnetwork lifetime optimisationen_GB
dc.titleHybrid Evolutionary Approaches to Maximum Lifetime Routing and Energy Efficiency in sensor mesh networksen_GB
dc.typeArticleen_GB
dc.date.available2015-04-29T14:20:51Z
dc.identifier.issn1063-6560
dc.descriptionCopyright © 2015 The MIT Pressen_GB
dc.descriptionThis is the manuscript version of the article accepted for publication in Evolutionary Computationen_GB
dc.identifier.eissn1530-9304
dc.identifier.journalEvolutionary Computationen_GB


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