{"title":"Data centric multi-shift sensor scheduling for wireless sensor networks","authors":"Jialin Zhang, Y. Hu","doi":"10.1109/ICASSP.2013.6638530","DOIUrl":null,"url":null,"abstract":"A multi-shift sensor scheduling method is proposed to extend the operating lifespan of a wireless sensor network. Sensor nodes in the WSN are partitioned into N subnetworks and the operating schedule is partitioned into N shifts of equal duration. Exploiting spatial correlations among sensor nodes, data collected using each subnetwork can well approximate the data collected using original sensor network. Each sub-network also form a connected component to ensure proper data collection. This task is formulated as a NP-hard constrained subset selection problem. A polynomial time heuristic algorithm leveraging breath-first search and subspace approximation is proposed. Simulations using a real world data set demonstrate superior performance and extended lifespan of this proposed method.","PeriodicalId":183968,"journal":{"name":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2013.6638530","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
A multi-shift sensor scheduling method is proposed to extend the operating lifespan of a wireless sensor network. Sensor nodes in the WSN are partitioned into N subnetworks and the operating schedule is partitioned into N shifts of equal duration. Exploiting spatial correlations among sensor nodes, data collected using each subnetwork can well approximate the data collected using original sensor network. Each sub-network also form a connected component to ensure proper data collection. This task is formulated as a NP-hard constrained subset selection problem. A polynomial time heuristic algorithm leveraging breath-first search and subspace approximation is proposed. Simulations using a real world data set demonstrate superior performance and extended lifespan of this proposed method.