Clustering WSN using Fuzzy Logic and Genetic Algorithm

In general, wireless sensor networks possess a number of sensor nodes that are capable of sensing, computing and communicating. Usually these are placed in atmosphere to get the data related to natural parameters like temperature, humidity, pressure etc,. In order to sense, compute and communicate the data, the sensor node utilizes some amount of energy from its battery source. The main drawback of wireless sensor networks is that each sensor node is energy limited, which means that a node can survive and function for a limited period of time. Thus the sensor node’s have small lifetime. This affects the whole sensor network lifetime. But it can be improved by undergoing a technique called Clustering. Many protocols were presented to perform this clustering. The main task in clustering is the election of cluster head. Previously LEACH protocol was used, where it ended up with random distribution of sensor nodes in the Wireless sensor network. Here we come up with fuzzy logic and genetic algorithm to elect the cluster head. Here, the Fuzzy module is used in sensor node and the genetic algorithm in the Base Station or SINK. First step involves in the process of nomination for being a cluster head takes place and the second step involves in selecting the best among the nominated nodes as a cluster head for that particular cluster. Thus the nomination process in first step uses the Fuzzy Logic and the selection process in the second step uses the Genetic Algorithm. This could really optimize the energy consumption of sensor node and thereby increase the network lifetime.