{"title":"传感器网络中的连通k -覆盖问题","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":"{\"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}","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}
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