Adaptive clustering and routing using fuzzy decision model in WSN
T. Prabakaran, N. Karthikeyan · International Journal of Mobile Network Design and Innovation · 2015
In most of the clustering process, selection of reliable and efficient cluster head selection is important issue. In most of the clustering process, failure of CH occurs due to energy depletion and if the distance between sink and CH is more it ultimately leads to failure in transmission. In order to overcome this issue an adaptive clustering and routing using fuzzy decision model in WSN is proposed. In the proposed technique, first the optimal number of nodes in the cluster is found based on energy level of each node and transmission range is found. Also the size of cluster is found to determine the density of the network. Finally, selection of CH is done using the fuzzy decision model which includes the parameter such as energy level, quality of link, distance of node to sink, data rate and degree of heterogeneity. The advantage of proposed technique is that it provides network with most reliable CH for transmission of the packet.