{"title":"基于随机过程的无线传感器网络重新部署模型框架","authors":"Ravindara Bhatt, R. Datta","doi":"10.1109/WAINA.2013.176","DOIUrl":null,"url":null,"abstract":"In this paper we propose a redeployment scheme of Wireless Sensor Network (WSN) nodes based on a stochastic process. WSN suffers from formation of hole in the network due to its asymmetric deployment, unbalanced energy consumption and intentional destruction of nodes in the network. The dynamic increase in Quality-of-Service (QoS) parameters such as coverage and connectivity also may lead to formation of holes which in turn degrades the performance of the network. Therefore, in order to maintain a desired QoS, a sensor redeployment scheme is important in WSN. During its lifecycle, a sensor node experiences active, sleep, diagnose, vulnerable, repair, and fail states. We analyze the Markov process and obtain the steady state probabilities for all the states. The availability of the nodes is presented with the help of SHARPE tool. Our work utilizes Discrete-Time Markov Chain and a Semi-Markov Process to illustrate the probabilities of WSN node in various states. The required redeployment nodes are then computed based on a stochastic analysis of the system and subject to the QoS requirements of the network.","PeriodicalId":359251,"journal":{"name":"2013 27th International Conference on Advanced Information Networking and Applications Workshops","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A Stochastic Process Based Framework of Redeployment Model for Wireless Sensor Network\",\"authors\":\"Ravindara Bhatt, R. Datta\",\"doi\":\"10.1109/WAINA.2013.176\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we propose a redeployment scheme of Wireless Sensor Network (WSN) nodes based on a stochastic process. WSN suffers from formation of hole in the network due to its asymmetric deployment, unbalanced energy consumption and intentional destruction of nodes in the network. The dynamic increase in Quality-of-Service (QoS) parameters such as coverage and connectivity also may lead to formation of holes which in turn degrades the performance of the network. Therefore, in order to maintain a desired QoS, a sensor redeployment scheme is important in WSN. During its lifecycle, a sensor node experiences active, sleep, diagnose, vulnerable, repair, and fail states. We analyze the Markov process and obtain the steady state probabilities for all the states. The availability of the nodes is presented with the help of SHARPE tool. Our work utilizes Discrete-Time Markov Chain and a Semi-Markov Process to illustrate the probabilities of WSN node in various states. The required redeployment nodes are then computed based on a stochastic analysis of the system and subject to the QoS requirements of the network.\",\"PeriodicalId\":359251,\"journal\":{\"name\":\"2013 27th International Conference on Advanced Information Networking and Applications Workshops\",\"volume\":\"22 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 27th International Conference on Advanced Information Networking and Applications Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WAINA.2013.176\",\"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 27th International Conference on Advanced Information Networking and Applications Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WAINA.2013.176","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Stochastic Process Based Framework of Redeployment Model for Wireless Sensor Network
In this paper we propose a redeployment scheme of Wireless Sensor Network (WSN) nodes based on a stochastic process. WSN suffers from formation of hole in the network due to its asymmetric deployment, unbalanced energy consumption and intentional destruction of nodes in the network. The dynamic increase in Quality-of-Service (QoS) parameters such as coverage and connectivity also may lead to formation of holes which in turn degrades the performance of the network. Therefore, in order to maintain a desired QoS, a sensor redeployment scheme is important in WSN. During its lifecycle, a sensor node experiences active, sleep, diagnose, vulnerable, repair, and fail states. We analyze the Markov process and obtain the steady state probabilities for all the states. The availability of the nodes is presented with the help of SHARPE tool. Our work utilizes Discrete-Time Markov Chain and a Semi-Markov Process to illustrate the probabilities of WSN node in various states. The required redeployment nodes are then computed based on a stochastic analysis of the system and subject to the QoS requirements of the network.