{"title":"Maximizing Network Lifetime for Estimation in Multi-Hop Wireless Sensor Networks","authors":"Junlin Li, G. Al-Regib","doi":"10.1109/ICCCN.2008.ECP.150","DOIUrl":null,"url":null,"abstract":"In this paper, we consider distributed estimation in energy-limited wireless sensor networks from lifetime-distortion perspective, where the goal is to maximize the network lifetime for a given distortion requirement. To take into account both local quantization and multi-hop transmission, which are essential to save transmission energy and thus prolong the network lifetime, the network lifetime maximization problem is formulated as a nonlinear programming (NLP) problem, where there are three factors needed to be optimized jointly: (i) source coding at each sensor, (ii) source throughput of each sensor, and (iii) multi-hop routing path. Furthermore, we show that this NLP problem can be decoupled without loss of optimality and reformulated as a linear programming (LP) problem. The proposed algorithm is optimal and the simulation results show that a significant gain is achieved by the proposed algorithm compared with heuristic methods.","PeriodicalId":314071,"journal":{"name":"2008 Proceedings of 17th International Conference on Computer Communications and Networks","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Proceedings of 17th International Conference on Computer Communications and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCN.2008.ECP.150","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In this paper, we consider distributed estimation in energy-limited wireless sensor networks from lifetime-distortion perspective, where the goal is to maximize the network lifetime for a given distortion requirement. To take into account both local quantization and multi-hop transmission, which are essential to save transmission energy and thus prolong the network lifetime, the network lifetime maximization problem is formulated as a nonlinear programming (NLP) problem, where there are three factors needed to be optimized jointly: (i) source coding at each sensor, (ii) source throughput of each sensor, and (iii) multi-hop routing path. Furthermore, we show that this NLP problem can be decoupled without loss of optimality and reformulated as a linear programming (LP) problem. The proposed algorithm is optimal and the simulation results show that a significant gain is achieved by the proposed algorithm compared with heuristic methods.