CDLN - CLUSTER DISTANCE BASED DATA FORWARDING AND OPTIMAL LEADER ELECTION USING FUZZY INFERENCE IN WIRELESS NETWORK

Abstract

Professor, Department of Information Science &Engineering SDM College of Engineering & Technology Dharwad Karnataka,India Email: [email protected] Abstract: Wireless networks in general can consume a lot of energy and incur losses if they do not have the right protocols to properly add packets to the destination. Similarly, if the connectivity of the network nodes is different, its resource losses will be higher. Thus, the network will quickly disconnect and cause very high losses. As well as wireless nodes, this sends various data, so energy losses are high. This proposed method CDLN – cluster distance-based data forwarding and optimal leader election using fuzzy inference in wireless network -is designed to take care of all these and formulate routing accordingly. In this method, the cluster set is formed and the main leader and assistant leaders are selected. Thus, when the main leader is disconnected, the assistant cluster acts to prevent network loss. Because the transmission ranges in this network are different sizes, the cluster set will have different members. These cluster sets are formed in a fuzzy inference mode and set up with precise leaders and routing, thus reducing energy costs, network life time and the number of dead nodes. It can also be seen in the output that the network lasts longer.