{"title":"基于能量的无线传感器网络目标定位中能量消耗与性能平衡的多目标方法","authors":"Zhenxing Luo, T. Jannett","doi":"10.1109/SECON.2012.6196991","DOIUrl":null,"url":null,"abstract":"In this paper, we utilized a multi-objective approach to balance energy consumption and performance in wireless sensor networks (WSNs) that use a maximum likelihood estimation (MLE) approach for energy-based target localization. First, we developed measures that allow energy consumption and performance to be balanced in one-dimensional sensor arrays. Next, we extended these methods for two-dimensional arrays, employing approximations that facilitate computation of the energy consumption. Simulations were run to generate the Pareto-optimal fronts for both one-dimensional and two-dimensional sensor arrays. The Pareto-optimal fronts are useful in determining optimum points in practice.","PeriodicalId":187091,"journal":{"name":"2012 Proceedings of IEEE Southeastcon","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":"{\"title\":\"A multi-objective method to balance energy consumption and performance for energy-based target localization in wireless sensor networks\",\"authors\":\"Zhenxing Luo, T. Jannett\",\"doi\":\"10.1109/SECON.2012.6196991\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we utilized a multi-objective approach to balance energy consumption and performance in wireless sensor networks (WSNs) that use a maximum likelihood estimation (MLE) approach for energy-based target localization. First, we developed measures that allow energy consumption and performance to be balanced in one-dimensional sensor arrays. Next, we extended these methods for two-dimensional arrays, employing approximations that facilitate computation of the energy consumption. Simulations were run to generate the Pareto-optimal fronts for both one-dimensional and two-dimensional sensor arrays. The Pareto-optimal fronts are useful in determining optimum points in practice.\",\"PeriodicalId\":187091,\"journal\":{\"name\":\"2012 Proceedings of IEEE Southeastcon\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"31\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Proceedings of IEEE Southeastcon\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SECON.2012.6196991\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Proceedings of IEEE Southeastcon","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SECON.2012.6196991","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A multi-objective method to balance energy consumption and performance for energy-based target localization in wireless sensor networks
In this paper, we utilized a multi-objective approach to balance energy consumption and performance in wireless sensor networks (WSNs) that use a maximum likelihood estimation (MLE) approach for energy-based target localization. First, we developed measures that allow energy consumption and performance to be balanced in one-dimensional sensor arrays. Next, we extended these methods for two-dimensional arrays, employing approximations that facilitate computation of the energy consumption. Simulations were run to generate the Pareto-optimal fronts for both one-dimensional and two-dimensional sensor arrays. The Pareto-optimal fronts are useful in determining optimum points in practice.