Elongate the Network Lifetime using Adaptive Network-Based Fuzzy Inference System in Wireless Sensor Networks

Abstract

The Wireless Sensor Networks is the collection of sensor nodes that can sense the environment and send it to the sink or access point for further processing based on the requirement. It works on the principle of ”less effort and more comfort.” These sensors collect the sensed data and transfer it to the access point. The Network framework is critical in selecting the optimum distance and degree of data-access point connectivity for effective communication between source, intermediate destinations, and the final destination. For this, Energy-efficient clustering is the ultimate mechanism for long-term energy efficiency in most Networks. To achieve long-term energy efficiency, we choose to enhance the LEACH protocol as it is a well-known protocol for energy efficiency and prolongs the network lifetime. Still, the cons of the LEACH protocol are it uses a random approach for cluster formation. It does not consider the node’s residual energy for choosing the head node from each cluster. We enhanced the LEACH protocol by using an Adaptive network-based fuzzy inference system by overcoming the mentioned cons. We conducted a simulation to test the efficiency of our proposed routing protocol. It is better in terms of throughput, lifetime, energy dissipation, and the first node dies, quarter node dies, percent of node die, and several nodes alive after completion of rounds. Also, we compared our approach with two of the existing state of art approaches like LEACH using the Conventional approach, LEACH using the Fuzzy approach, and Multi-Criteria Cluster Head Delegation.