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

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.