{"title":"具有去中心化二值检测的传感器网络:聚类和寿命","authors":"G. Ferrari, M. Martalò","doi":"10.1109/SAHCN.2006.288525","DOIUrl":null,"url":null,"abstract":"In this paper, we analyze the lifetime of clustered sensor networks with decentralized binary detection under a physical layer quality of service (QoS) constraint, given by the maximum tolerable probability of decision error at the access point (AP). In order to properly model the network behavior, we consider four different distributions (exponential, uniform, Rayleigh, and lognormal) for the single sensors' lifetime. We show the benefits, in terms of longer network lifetime, of adaptive reclustering. On the other hand, absence of reclustering leads to a shorter network lifetime, and we show the impact of various clustering configurations under different QoS conditions. Our results show that the organization of sensors in a few big clusters is the winning strategy to maximize the network lifetime","PeriodicalId":58925,"journal":{"name":"Digital Communications and Networks","volume":"27 1","pages":"645-650"},"PeriodicalIF":0.0000,"publicationDate":"2006-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sensor Networks with Decentralized Binary Detection: Clustering and Lifetime\",\"authors\":\"G. Ferrari, M. Martalò\",\"doi\":\"10.1109/SAHCN.2006.288525\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we analyze the lifetime of clustered sensor networks with decentralized binary detection under a physical layer quality of service (QoS) constraint, given by the maximum tolerable probability of decision error at the access point (AP). In order to properly model the network behavior, we consider four different distributions (exponential, uniform, Rayleigh, and lognormal) for the single sensors' lifetime. We show the benefits, in terms of longer network lifetime, of adaptive reclustering. On the other hand, absence of reclustering leads to a shorter network lifetime, and we show the impact of various clustering configurations under different QoS conditions. Our results show that the organization of sensors in a few big clusters is the winning strategy to maximize the network lifetime\",\"PeriodicalId\":58925,\"journal\":{\"name\":\"Digital Communications and Networks\",\"volume\":\"27 1\",\"pages\":\"645-650\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Digital Communications and Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SAHCN.2006.288525\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Communications and Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SAHCN.2006.288525","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sensor Networks with Decentralized Binary Detection: Clustering and Lifetime
In this paper, we analyze the lifetime of clustered sensor networks with decentralized binary detection under a physical layer quality of service (QoS) constraint, given by the maximum tolerable probability of decision error at the access point (AP). In order to properly model the network behavior, we consider four different distributions (exponential, uniform, Rayleigh, and lognormal) for the single sensors' lifetime. We show the benefits, in terms of longer network lifetime, of adaptive reclustering. On the other hand, absence of reclustering leads to a shorter network lifetime, and we show the impact of various clustering configurations under different QoS conditions. Our results show that the organization of sensors in a few big clusters is the winning strategy to maximize the network lifetime