{"title":"无线传感器网络时间同步改进","authors":"Q. Gao, Baomin Xu","doi":"10.1109/SPCA.2006.297535","DOIUrl":null,"url":null,"abstract":"Wireless sensor networks (WSN) have emerged as an interesting and important research area in the last few years. Though the clock accuracy and precision requirements are often stricter than in traditional distributed systems, strict energy constraints limit the resources available to meet these goals. In this paper, we present a Bayesian approach to reduce time measurement uncertainty associated with message delivery delay. Our approach combines prior knowledge of time measurements from upstream nodes, measured time and measurement uncertainty of downstream nodes in order to obtain a more accurate time estimate. We verify the efficiency of this approach via simulations. For a 4 hop network, time synchronization precision with Bayesian estimation is about 4 times better than without it. We modeled a 100 hop network and show that time synchronization accuracy does not degrade significantly with the increase in number of hops being synchronized. Our approach is based on existing time synchronization algorithms and uses only local processing so that it does not add extra traffic","PeriodicalId":232800,"journal":{"name":"2006 First International Symposium on Pervasive Computing and Applications","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Time Synchronization Improvement for Wireless Sensor Networks\",\"authors\":\"Q. Gao, Baomin Xu\",\"doi\":\"10.1109/SPCA.2006.297535\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wireless sensor networks (WSN) have emerged as an interesting and important research area in the last few years. Though the clock accuracy and precision requirements are often stricter than in traditional distributed systems, strict energy constraints limit the resources available to meet these goals. In this paper, we present a Bayesian approach to reduce time measurement uncertainty associated with message delivery delay. Our approach combines prior knowledge of time measurements from upstream nodes, measured time and measurement uncertainty of downstream nodes in order to obtain a more accurate time estimate. We verify the efficiency of this approach via simulations. For a 4 hop network, time synchronization precision with Bayesian estimation is about 4 times better than without it. We modeled a 100 hop network and show that time synchronization accuracy does not degrade significantly with the increase in number of hops being synchronized. Our approach is based on existing time synchronization algorithms and uses only local processing so that it does not add extra traffic\",\"PeriodicalId\":232800,\"journal\":{\"name\":\"2006 First International Symposium on Pervasive Computing and Applications\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2006 First International Symposium on Pervasive Computing and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPCA.2006.297535\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 First International Symposium on Pervasive Computing and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPCA.2006.297535","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Time Synchronization Improvement for Wireless Sensor Networks
Wireless sensor networks (WSN) have emerged as an interesting and important research area in the last few years. Though the clock accuracy and precision requirements are often stricter than in traditional distributed systems, strict energy constraints limit the resources available to meet these goals. In this paper, we present a Bayesian approach to reduce time measurement uncertainty associated with message delivery delay. Our approach combines prior knowledge of time measurements from upstream nodes, measured time and measurement uncertainty of downstream nodes in order to obtain a more accurate time estimate. We verify the efficiency of this approach via simulations. For a 4 hop network, time synchronization precision with Bayesian estimation is about 4 times better than without it. We modeled a 100 hop network and show that time synchronization accuracy does not degrade significantly with the increase in number of hops being synchronized. Our approach is based on existing time synchronization algorithms and uses only local processing so that it does not add extra traffic