基于随机过程的无线传感器网络重新部署模型框架

Ravindara Bhatt, R. Datta
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引用次数: 3

摘要

本文提出了一种基于随机过程的无线传感器网络(WSN)节点重新部署方案。无线传感器网络由于部署不对称、能量消耗不平衡、故意破坏网络节点等原因,容易造成网络空穴的形成。覆盖和连通性等服务质量(QoS)参数的动态增加也可能导致漏洞的形成,从而降低网络的性能。因此,为了保持期望的QoS,传感器重新部署方案在WSN中非常重要。在其生命周期中,传感器节点经历活动、睡眠、诊断、脆弱、修复和故障状态。我们分析了马尔可夫过程,得到了所有状态的稳态概率。利用SHARPE工具对节点的可用性进行了分析。我们的工作利用离散时间马尔可夫链和半马尔可夫过程来说明WSN节点在不同状态下的概率。然后根据系统的随机分析和网络的QoS要求计算所需的重新部署节点。
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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.
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