S. Abdelhak, C. S. Gurram, Soumik Ghosh, M. Bayoumi
{"title":"Energy-balancing task allocation on wireless sensor networks for extending the lifetime","authors":"S. Abdelhak, C. S. Gurram, Soumik Ghosh, M. Bayoumi","doi":"10.1109/MWSCAS.2010.5548700","DOIUrl":null,"url":null,"abstract":"Extending the wireless sensor network's lifetime has been the aim of several research efforts. Distributed in-network processing arises as a viable solution to extend the network's lifetime. It avoids assigning heavy computations to a single node which might otherwise lead to its significant energy depletion. Task scheduling and allocation play a major role in the efficiency of the distribution. This work proposes EBSEL, an e̲nergy-b̲alancing task s̲cheduling and allocation heuristic whose main purpose is to e̲xtend the network's l̲ifetime, through energy balancing. Balancing the energy consumption among the nodes can help avoid the disintegration of the network where some nodes die unnecessarily, while others still have high energy reserve. EBSEL was extensively simulated on random task graphs and on a task graph of a real-world application. Compared to related work, EBSEL achieved more than 50% increase in lifetime and up to 5% energy savings per iteration.","PeriodicalId":245322,"journal":{"name":"2010 53rd IEEE International Midwest Symposium on Circuits and Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"33","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 53rd IEEE International Midwest Symposium on Circuits and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MWSCAS.2010.5548700","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 33
Abstract
Extending the wireless sensor network's lifetime has been the aim of several research efforts. Distributed in-network processing arises as a viable solution to extend the network's lifetime. It avoids assigning heavy computations to a single node which might otherwise lead to its significant energy depletion. Task scheduling and allocation play a major role in the efficiency of the distribution. This work proposes EBSEL, an e̲nergy-b̲alancing task s̲cheduling and allocation heuristic whose main purpose is to e̲xtend the network's l̲ifetime, through energy balancing. Balancing the energy consumption among the nodes can help avoid the disintegration of the network where some nodes die unnecessarily, while others still have high energy reserve. EBSEL was extensively simulated on random task graphs and on a task graph of a real-world application. Compared to related work, EBSEL achieved more than 50% increase in lifetime and up to 5% energy savings per iteration.