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Fuzzy Based Energy Competent Cluster Head Selection in Wireless Sensor Networks

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Wireless Sensor Network (WSN) is a wireless communication System based on embedded system and sensor system, which is equipped with lots of low-cost micro low-power sensor nodes. Nowadays, WSN has been widely applied in various fields for their merits, such as smart home, environmental monitoring, and military surveillance, disaster relief operations etc .The wireless sensor network checks physical and environmental status, data is collected and sent to the base station via network. Clustering combines several sensor nodes to form a cluster and elects a head for the clusters formed. Cluster formation and cluster head selection plays major role in Wireless Sensor Networks (WSNs).In order to select a Cluster Head various parameter such as residual energy, centrality, number of neighbors, distance to base station etc., can be considered. . This paper focuses on coordination of sensor nodes in a network and selection of best node which keeps information of affiliated sensor node for communication with cluster head of other clusters using fuzzy logic.BFO algorithm also used for optimization .This model improves the network lifetime and efficiency of the Cluster Head.
Keywords: cluster head,fuzzy logic and BFO
WSN is an autonomous sensor used to monitor environmental conditions such as sound, pressure, etc. It helps to transfer the data via the networks to the destination. It is build-up of many nodes where each one of the nodes connected to one another. A common application of WSN is area monitoring, environmental/earth sensing, air pollution monitoring etc. The main characteristics of WSN are ease of use, mobility of nodes, energy harvesting, resilience.WSN use LAN or WAN for communication via gateway. Major issue in WSN is the nodes are not in similar size ,the data transferring efficiency may be vary, for this purpose clustering method is adopted and particular node can be selected as cluster head(CH).Cluster is the process of grouping the objects which are similar among them and are dissimilar to the other cluster. Its main aim is to determine the unlabeled data in intrinsic group. Clustering technique can be performed by using many different methods. In this system, Fuzzy logic is used for clustering process and to evaluate true or false, yes or no, high or low etc. The reason for using fuzzy logic is decision making purpose. It is mainly designed for reduce the development cycle. It can provide more user-friendly and efficient performance. In this paper four parameters are used for applying fuzzy logic, they are residual energy, centrality, distance to base station and number of nodes. By using this fuzzy logic fitness of each node can be found and analyze all the fitness value for select the cluster head among all the nodes by implementing the BFO algorithm. It is a global optimization algorithm for distributed optimization and control over the nodes .It is used to find the best solutions for difficult problem. For cluster head selection in our paper, BFO algorithm is used. This algorithm chooses the energetic nodes and eliminates the weakest nodes. As a result of this system improves the network life time and efficiency of the cluster head.


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