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Node Clustering in Wireless Sensor Networks using Fuzzy Logic: Survey

机译:使用模糊逻辑的无线传感器网络中的节点聚类:测量

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Selecting a deserving node as a cluster head (CH) has a symbolic impact on the energy efficient working of Wireless Sensor Networks (WSNs). With the reduction in network’s energy utilization, its lifetime can be increased up to a great extent. Clustering is a mechanism that helps in addressing both these issues efficiently. However, clustering also faces few challenges like making adequate decision during cluster head selection. This challenge arises due to the uncertain and dynamic nature of WSNs originated because of the random deployment of the sensor nodes in them. This paper tries to illustrate the potential of one of the soft computing paradigms i.e. fuzzy logic in overwhelming these issues in clustering WSNs. Since, Fuzzy Logic (FL) has the capability of simulating the mental process of human mind to observe, learn and understand things in the presence of uncertainty. So, this paper presents a systematic review of different fuzzy and hybrid fuzzy based approaches for handling clustering in WSNs.
机译:选择值得波动节点作为群集头(CH)对无线传感器网络(WSN)的节能工作具有符号影响。随着网络能源利用率的降低,其寿命可以在很大程度上增加。群集是一种有助于提供有效解决这些问题的机制。然而,聚类也面临着在群集头选择期间做出足够的决定的挑战很少。由于WSN的不确定和动态性,因此由于它们的随机部署而产生的,因此出现了这种挑战。本文试图说明一个软计算范例中的潜力,即在聚类WSN中压倒这些问题的模糊逻辑。由于模糊逻辑(FL)具有模拟人类心灵的心理过程,以观察,学习和理解存在不确定性的情况。因此,本文介绍了对WSN中的处理聚类的不同模糊和混合模糊基于基于模糊和混合模糊的方法的系统审查。

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