{"title":"基于能量感知生成树的无线传感器网络能量预测备份路径","authors":"Yao Lu, Jianping Chen, I. Comsa, P. Kuonen","doi":"10.1109/CyberC.2013.73","DOIUrl":null,"url":null,"abstract":"In order to decrease the energy consumption and to prolong the network lifetime, the energy-aware spanning tree as a data aggregation technique has been used in wireless sensor networks. Nevertheless, the energy constraint caused by the global reconstruction still severely influences the performance of the sensor system. Our approach aims to reduce the occurrence of the global reconstruction through the backup path. In addition, in order to prevent the redundant paths, a dynamic prediction method is proposed in order to adaptively estimate the possibility of the node failure. The theoretical analysis and simulations demonstrate the efficient performance of the proposed approach.","PeriodicalId":133756,"journal":{"name":"2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Backup Path with Energy Prediction Based on Energy-Aware Spanning Tree in Wireless Sensor Networks\",\"authors\":\"Yao Lu, Jianping Chen, I. Comsa, P. Kuonen\",\"doi\":\"10.1109/CyberC.2013.73\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to decrease the energy consumption and to prolong the network lifetime, the energy-aware spanning tree as a data aggregation technique has been used in wireless sensor networks. Nevertheless, the energy constraint caused by the global reconstruction still severely influences the performance of the sensor system. Our approach aims to reduce the occurrence of the global reconstruction through the backup path. In addition, in order to prevent the redundant paths, a dynamic prediction method is proposed in order to adaptively estimate the possibility of the node failure. The theoretical analysis and simulations demonstrate the efficient performance of the proposed approach.\",\"PeriodicalId\":133756,\"journal\":{\"name\":\"2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CyberC.2013.73\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CyberC.2013.73","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Backup Path with Energy Prediction Based on Energy-Aware Spanning Tree in Wireless Sensor Networks
In order to decrease the energy consumption and to prolong the network lifetime, the energy-aware spanning tree as a data aggregation technique has been used in wireless sensor networks. Nevertheless, the energy constraint caused by the global reconstruction still severely influences the performance of the sensor system. Our approach aims to reduce the occurrence of the global reconstruction through the backup path. In addition, in order to prevent the redundant paths, a dynamic prediction method is proposed in order to adaptively estimate the possibility of the node failure. The theoretical analysis and simulations demonstrate the efficient performance of the proposed approach.