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标题：An Adaptive Cluster based routing in WSN using Energy-Position dissemination and Integer linear programming
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作者：Anubha Deshmukh ; Ankita Gupta
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：10
DOI：10.15680/IJIRCCE.2015.0310175
出版社：S&S Publications
摘要：A wireless sensor network comprises of a proportion of low-cost sensors that have an inadequate energyresource. Voluminous applications together with environment monitoring use a clustering methodology for competentenergy consumption. An efficient power saving arrangement & intelligent mechanism requirements to be designeddeveloped for the reasonable energy consumption in the WSN to improve lifetime of network. The cluster-based techniqueis one of significant approaches to reduce energy consumption in the WSNs. This research work is taking traditionalprobabilistic clustering protocol concepts; also consider heterogeneity in wireless sensor network as an effective way toincrease the network lifetime and stability. We are proposing a Distributed Energy- position based clustering scheme whichis also optimized through Integer Linear Programming for efficient routing in wireless sensor network, the main intention isto make an optimized cluster head selection process and adaptive cluster formation which depends upon current networkconditions and resource status.To perform ideal distribution for the sensor node clusters, average distance between sensornodes is calculated & used to select residual energy & concept of the network density for selecting appropriate clustering bythe location head nodes. The lifetime of the WSN is extended by using uniform cluster location & balancing networkloading among clusters. Experimental results shows that with this network designing the network lifetime and stabilityperiod increases extensively.
关键词：Wireless sensor network; Energy efficient clustering; integer linear programming; routing; Energy;Distribution; network density; Network Lifetime; Adaptive clustering