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Fuzzy logic based Unequal Clustering in wireless sensor network for minimizing Energy consumption

机译:无线传感器网络中基于模糊逻辑的不等分聚类,可最大程度地降低能耗

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Energy consumption and lifetime of WSN are the most important research challenges to be resolved. For load balancing and efficient data collection in the network, clustering is used. Sensors in each cluster send the data to their corresponding cluster heads. The cluster head performs data aggregation and transmission of the aggregated data to the base station. Farther sensor nodes data are aggregated by cluster heads and send to the base station. This leads to a heavy traffic and faster depletion of energy to the nodes that are nearer to the sink. To enhance the energy conservation, for suppressing hot spot problem and for load balance achievement, we propose an algorithm namely as ECUCF (Energy Conserved Unequal Clusters with Fuzzy logic). Based on the distances of the nodes from the base station, the network is divided into three different sectors. For designing unequal clusters in each sector, a fuzzy logic approach is followed. The cluster heads that are nearer to the base station are designed to be of smaller sizes whereas the cluster heads that are situated farther away from the sink to have higher cluster sizes. The proposed algorithm ECUCF is simulated using MATLAB environment. The performances obtained are compared with the performances of other clustering schemes like LEACH (equal clustering algorithm) and FBUC (unequal clustering algorithm). From the simulated results, it is found that the performances of ECUCF are much improved as compared to LEACH and FBUC in maximizing the number of clusters, increasing the number of live nodes in the network and extending the lifetime of nodes on each round of operation.
机译:无线传感器网络的能耗和生命周期是需要解决的最重要的研究挑战。为了在网络中实现负载平衡和有效的数据收集,请使用群集。每个群集中的传感器将数据发送到其相应的群集头。簇头执行数据聚合并且将聚合的数据传输到基站。群集头聚集更多的传感器节点数据,并将其发送到基站。这导致交通繁忙,并且能量更快地耗尽到更靠近接收器的节点。为了增强节能效果,抑制热点问题和实现负载平衡,我们提出了一种算法,即ECUCF(带有模糊逻辑的节能不等式簇)。根据节点到基站的距离,将网络分为三个不同的扇区。为了在每个扇区中设计不相等的簇,遵循了模糊逻辑方法。离基站较近的簇头被设计为较小的尺寸,而离信宿较远的簇头被设计为具有更大的簇尺寸。所提出的算法ECUCF是在MATLAB环境下进行仿真的。将获得的性能与其他聚类方案(如LEACH(相等聚类算法)和FBUC(不等聚类算法))的性能进行比较。从模拟结果中发现,与LEACH和FBUC相比,ECUCF的性能在最大程度地提高了群集数,增加了网络中的活动节点数并延长了每一轮操作中节点的寿命方面都得到了改善。

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