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دانلود رایکان مقاله انگلیسی ISI با موضوع بررسی الگوریتم های خوشه بندی در شبکه های حسگر بی سیم

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بررسی الگوریتم های خوشه بندی در شبکه های حسگر بی سیم

عنوان انگلیسی مقاله:

A survey on clustering algorithms for wireless sensor networks

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3. Clustering algorithms for WSNs

Generally, WSNs involve a large number of sensors ranging in the hundreds or even thousands. Clustering is an effective mean for managing such high population of nodes. In this section we present a literature survey of published distributed algorithms for clustering WSNs. Given that scalability is regarded as the main advantage of network clustering, the surveyed algorithms are grouped according to their convergence rate into two subsections for variable and constant convergence time algorithms, respectively.

3.1. Variable convergence time algorithms

Time is a significant factor in the convergence of clustering algorithms. Some of the proposed clustering algorithms such as LCA [48], RCC [52] and CLUBS [53], have O(n) convergence time, where n represent the number of sensor nodes in the network. It is thus practical to implement these types of clustering algorithms to the networks having small number of nodes. However, convergence time has enhanced dramatically in some recent algorithms, e.g. [17], and showed their suitability for networks having large number of nodes. In general, variable convergence time algorithms enable more control of the cluster properties than the constant time ones