A Gradient-Assisted Energy-Efficient Backpressure Scheduling Algorithm for Wireless Sensor Networks

dc.contributor.authorJiao, Zhenzhen
dc.contributor.authorTian, Rui
dc.contributor.authorZhang, Baoxian
dc.contributor.authorLi, Cheng
dc.date.issued2015
dc.description.abstractBackpressure based scheduling has revealed remarkable performance in wireless multihop networks as reported in a lot of previous work. However, its lack of consideration on energy use efficiency is still an obstacle for backpressure based algorithms to be deployed in resource-constrained wireless sensor networks (WSNs). In this paper, we focus on studying the design of energy efficient backpressure based algorithm. For this purpose, we propose a gradient-assisted energy-efficient backpressure scheduling algorithm (GRAPE) for WSNs. GRAPE introduces a new link-weight calculation method, based on which gradient information and nodal residual energy are taken into account when making decisions on backpressure based transmission scheduling. According to the decisions made by this new method, packets are encouraged to be forwarded to nodes with more residual energy. We theoretically prove the throughput-optimality of GRAPE. Simulation results demonstrate that GRAPE can achieve significant performance improvements in terms of energy use efficiency, network throughput, and packet delivery ratio as compared with existing work.
dc.description.noteMemorial University Open Access Author's Fund
dc.format.volume2015
dc.identifier.issn1550-1477
dc.identifier.urihttp://dx.doi.org/10.1155/2015/460506
dc.identifier.urihttps://hdl.handle.net/20.500.14783/9138
dc.language.isoen
dc.publisherHindawi Publishing Corporation
dc.relation.urihttp://www.hindawi.com/
dc.titleA Gradient-Assisted Energy-Efficient Backpressure Scheduling Algorithm for Wireless Sensor Networks
dc.typearticle
mem.campusSt. John's Campus
mem.departmentEngineering and Applied Science
mem.divisionsFacEngineering
mem.fullTextStatuspublic
mem.idNumber10.1155/2015/460506
mem.isPublishedpub
mem.refereedTrue
oaire.citation.issueInternational Journal of Distributed Sensor Networks

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