{"title":"无线视频传感器网络的网络寿命建模与优化","authors":"Junni Zou, Chong Tan, Ruifeng Zhang, H. Xiong","doi":"10.1109/ICC.2010.5502437","DOIUrl":null,"url":null,"abstract":"This paper studies the power consumption performance and resource allocation optimization in wireless video sensor networks. Network coding based multipath routing, network flow control and video encoding bit rate are jointly optimized, aiming to maximize the network lifetime at a given power budget and video quality requirement. Importantly, to concretely measure the network coding power utilized on error recovery, a generalized power consumption model for network coding is first developed in this paper. Through the Lagrange dual and subgradient approach, a fully decentralized algorithm is proposed to solve the target convex optimization problem. Numerical results validate the convergence and performance of the proposed algorithm.","PeriodicalId":6405,"journal":{"name":"2010 IEEE International Conference on Communications","volume":"14 1","pages":"1-6"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Modeling and Optimization of Network Lifetime in Wireless Video Sensor Networks\",\"authors\":\"Junni Zou, Chong Tan, Ruifeng Zhang, H. Xiong\",\"doi\":\"10.1109/ICC.2010.5502437\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies the power consumption performance and resource allocation optimization in wireless video sensor networks. Network coding based multipath routing, network flow control and video encoding bit rate are jointly optimized, aiming to maximize the network lifetime at a given power budget and video quality requirement. Importantly, to concretely measure the network coding power utilized on error recovery, a generalized power consumption model for network coding is first developed in this paper. Through the Lagrange dual and subgradient approach, a fully decentralized algorithm is proposed to solve the target convex optimization problem. Numerical results validate the convergence and performance of the proposed algorithm.\",\"PeriodicalId\":6405,\"journal\":{\"name\":\"2010 IEEE International Conference on Communications\",\"volume\":\"14 1\",\"pages\":\"1-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICC.2010.5502437\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICC.2010.5502437","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Modeling and Optimization of Network Lifetime in Wireless Video Sensor Networks
This paper studies the power consumption performance and resource allocation optimization in wireless video sensor networks. Network coding based multipath routing, network flow control and video encoding bit rate are jointly optimized, aiming to maximize the network lifetime at a given power budget and video quality requirement. Importantly, to concretely measure the network coding power utilized on error recovery, a generalized power consumption model for network coding is first developed in this paper. Through the Lagrange dual and subgradient approach, a fully decentralized algorithm is proposed to solve the target convex optimization problem. Numerical results validate the convergence and performance of the proposed algorithm.