基于模糊逻辑的无线传感器网络分簇协议性能分析
Performance Analysis of Clustering Protocol Using Fuzzy Logic for Wireless Sensor Network
摘要：
为了更有效地收集信息，无线传感器网络（WSNs）被划分成簇。大多数提出的聚类算法不考虑基站的位置。这种情况导致热点问题的多跳无线传感器网络。在本文中，我们分析了模糊聚类算法（FCA），其目的是延长生命周期的无线传感器网络。该算法根据传感器节点的剩余能量和到基站的距离参数来调整簇头半径。这有助于减少靠近基站或电池电量较低的传感器节点的簇内工作。模糊逻辑用于处理簇头半径估计中的不确定性。从首节点死亡率、半数存活率和能量效率指标等方面比较了该算法与低能耗自适应分簇层次（LEACH）算法的性能。我们的仿真结果表明，模糊聚类方法的性能优于LEACH。因此，FCA是一种稳定且节能的聚类算法。
英文摘要：
In order to gather information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. Most proposed clustering algorithms do not consider the location of the base station. This situation causes hot spot problems in multi-hop WSNs. In this paper, we analyze a fuzzy clustering algorithm (FCA) which aims to prolong the lifetime of WSNs. This algorithm adjusts the cluster-head radius considering the residual energy and distance to the base station parameters of the sensor nodes. This helps to decrease the intra-cluster work of the sensor nodes which are closer to the base station or have lower battery level. Fuzzy logic is utilized for handling the uncertainties in cluster-head radius estimation. We compare this algorithm with the low energy adaptive clustering hierarchy (LEACH) algorithm according to the parameters of first node dies half of the nodes alive and energy-efficiency metrics. Our simulation results show that the fuzzy clustering approach performs better than LEACH. Therefore, the FCA is a stable and energy-efficient clustering algorithm.
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