EEUCWFL: Energy Efficient Unequal Clustering With Multi-Input Multi-Output Fuzzy Logic

Abstract

The Wireless Sensor Network (WSN) consists a group of sensors and a Base Station (BS) or sink. Sensors gather data from the sensing area and send these data to BS, either directly or through multi-hop data transmission. There are several methods of efficient data transmission. Clustering is one of them. WSN uses the many different algorithms for making the cluster to transmit the data from the physical environment to the BS. Clustering makes the WSN Network efficient and improves the network lifetime. Other data transmission methods like direct transmission consumes very much energy so the life span of the sensor nodes becomes low in comparison to the clustering algorithm. The disadvantage of multi-hop data transmission of clustering algorithm is that a cluster head closer to sink has to forward the data of its own cluster as well as the data of near by clusters. So the node near base station dies sooner. This problem is known as hot-spot problem. The solution of hot-spot problem is unequal clustering. Nodes near base station should be smaller in size to balance the remaining energy of the nodes. In this paper, we have proposed a clustering algorithm (EEUCWFL) which uses multi-input multi-output fuzzy logic to select an optimal cluster head with unequal cluster size. We compared our proposed algorithm with three best known algorithms LEACH, EEUC and CHEF. The Results show that our proposed algorithm optimize energy consumption and improves the network lifetime.