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Home / programming language / NS2 / Towards Distributed Optimal Movement Strategy for Data Gathering in Wireless Sensor Networks
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Towards Distributed Optimal Movement Strategy for Data Gathering in Wireless Sensor Networks

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SKU: PROJ7129 Categories: 2017 Projects, Final Year Projects, NS2, Wireless Sensor Networking Tags: Android Project, Asp.Net Project, C# Project, Computer Engineering Final Year Projects, Computer Science Final Year Projects, Electronics Projects Engineering Students Final Year, Engineering Student Project Ideas, Final Semester Projects, Final Year Project Center, Final Year Projects, ieee ECE Projects, ieee EEE Projects, ieee Final Year Projects, IEEE Projects, ieee Projects Networking, Image Processing Projects, J2EE Project, Java Project, Java Project Code, Matlab Project, PHP Project, Students Projects
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Towards Distributed Optimal Movement Strategy for Data Gathering in Wireless Sensor Networks

Abstract— To design a distributed movement strategy for mobile collectors, which can be either physical mobile agents or query/collector packets periodically launched by the sink, to achieve successful data gathering in wireless sensor networks. Formulating the problem as general random walks on a graph composed of sensor nodes, we analyze how much data can be successfully gathered in time under any Markovian random-walk movement strategies for mobile collectors moving over a graph (or network), while each sensor node is equipped with limited buffer space and data arrival rates are heterogeneous over different sensor nodes. In particular, from the analysis, we obtain the optimal movement strategy among a class of Markovian strategies so as to minimize the data loss rate over all sensor nodes, and explain how such an optimal movement strategy can be made to work in a distributed fashion. We demonstrate that our distributed optimal movement strategy can lead to about two times smaller loss rate than a standard random walk strategy under diverse scenarios. In particular, our strategy results in up to 70 percent cost savings for the deployment of multiple collectors to achieve the target data loss rate than the standard random walk strategy. < final year projects >

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