{"title":"Connected K-coverage problem in sensor networks","authors":"Zongheng Zhou, Samir R Das, Himanshu Gupta","doi":"10.1109/ICCCN.2004.1401672","DOIUrl":null,"url":null,"abstract":"In overdeployed sensor networks, one approach to conserve energy is to keep only a small subset of sensors active at any instant. In this article, we consider the problem of selecting a minimum size connected K-cover, which is defined as a set of sensors M such that each point in the sensor network is \"covered\" by at least K different sensors in M, and the communication graph induced by M is connected. For the above optimization problem, we design a centralized approximation algorithm that delivers a near-optimal (within a factor of O(lg n)) solution, and present a distributed version of the algorithm. We also present a communication-efficient localized distributed algorithm which is empirically shown to perform well","PeriodicalId":229045,"journal":{"name":"Proceedings. 13th International Conference on Computer Communications and Networks (IEEE Cat. No.04EX969)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"347","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 13th International Conference on Computer Communications and Networks (IEEE Cat. No.04EX969)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCN.2004.1401672","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 347
Abstract
In overdeployed sensor networks, one approach to conserve energy is to keep only a small subset of sensors active at any instant. In this article, we consider the problem of selecting a minimum size connected K-cover, which is defined as a set of sensors M such that each point in the sensor network is "covered" by at least K different sensors in M, and the communication graph induced by M is connected. For the above optimization problem, we design a centralized approximation algorithm that delivers a near-optimal (within a factor of O(lg n)) solution, and present a distributed version of the algorithm. We also present a communication-efficient localized distributed algorithm which is empirically shown to perform well