{"title":"无线传感器网络中存在位置误差的高能效地理路由","authors":"Julien Champ, C. Saad","doi":"10.1109/I-SPAN.2008.49","DOIUrl":null,"url":null,"abstract":"In wireless sensor networks, almost all geographic routing algorithms assume that sensors are accurately located. In this paper, we propose an energy efficient geographic routing algorithm (EEG-Routing). In our method, before the deployment of sensors in their environment, sensor positions are known with position error bounds which are potentially larges. According to this knowledge, it is possible to compute, before the deployment the probability that two sensors communicate. EEG-Routing introduces a new metric which defines, regarding to communication probabilities, energy consumptions and realized progress, communication costs between neighbors. EEG-Routing simultaneously optimizes two criteria: the energy consumption and the delivery rate, in networks where sensors are inaccurately located. Performances are validated by simulations which compare EEG-Routing with an energy-optimal algorithm.","PeriodicalId":305776,"journal":{"name":"2008 International Symposium on Parallel Architectures, Algorithms, and Networks (i-span 2008)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"An Energy-Efficient Geographic Routing with Location Errors in Wireless Sensor Networks\",\"authors\":\"Julien Champ, C. Saad\",\"doi\":\"10.1109/I-SPAN.2008.49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In wireless sensor networks, almost all geographic routing algorithms assume that sensors are accurately located. In this paper, we propose an energy efficient geographic routing algorithm (EEG-Routing). In our method, before the deployment of sensors in their environment, sensor positions are known with position error bounds which are potentially larges. According to this knowledge, it is possible to compute, before the deployment the probability that two sensors communicate. EEG-Routing introduces a new metric which defines, regarding to communication probabilities, energy consumptions and realized progress, communication costs between neighbors. EEG-Routing simultaneously optimizes two criteria: the energy consumption and the delivery rate, in networks where sensors are inaccurately located. Performances are validated by simulations which compare EEG-Routing with an energy-optimal algorithm.\",\"PeriodicalId\":305776,\"journal\":{\"name\":\"2008 International Symposium on Parallel Architectures, Algorithms, and Networks (i-span 2008)\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 International Symposium on Parallel Architectures, Algorithms, and Networks (i-span 2008)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/I-SPAN.2008.49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Symposium on Parallel Architectures, Algorithms, and Networks (i-span 2008)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/I-SPAN.2008.49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Energy-Efficient Geographic Routing with Location Errors in Wireless Sensor Networks
In wireless sensor networks, almost all geographic routing algorithms assume that sensors are accurately located. In this paper, we propose an energy efficient geographic routing algorithm (EEG-Routing). In our method, before the deployment of sensors in their environment, sensor positions are known with position error bounds which are potentially larges. According to this knowledge, it is possible to compute, before the deployment the probability that two sensors communicate. EEG-Routing introduces a new metric which defines, regarding to communication probabilities, energy consumptions and realized progress, communication costs between neighbors. EEG-Routing simultaneously optimizes two criteria: the energy consumption and the delivery rate, in networks where sensors are inaccurately located. Performances are validated by simulations which compare EEG-Routing with an energy-optimal algorithm.