Fuzzy logic based cluster head selection and data processing in Distributed Sensor Networks

TL;DR: This paper proposes a fuzzy logic based clustering and data processing in DSNs that incorporates energy level of each node, bandwidth, and link efficiency, and the result shows that the proposed approach perform better than LEACH protocol that utilizes minimum energy, latency for cluster formation, and reduce communication overhead.

Abstract: Distributed Sensor Networks (DSNs) is a new generation of real time embedded systems with high computation. The energy and memory resources are being used in a wide variety of applications, where as traditional networking infrastructure is practically infeasible. In all applications of DSNs, expecting great number of distributed sensor nodes. The number of nodes are grouped into efficient clusters, instead of sending data by single node to sink node in DSNs. Clusters are used to perform following parameters in terms of scalability, load balancing, network lifetime, and etc. This paper proposes a fuzzy logic based clustering and data processing in DSNs. This approach incorporates energy level of each node, bandwidth, and link efficiency. The objective of the proposed work is to improve the performance of network in terms of energy consumption, throughput, time for cluster head selection, number of alive nodes, and network lifetime. The simulation result shows that the proposed approach perform better than LEACH protocol that utilizes minimum energy, latency for cluster formation, and reduce communication overhead in DSNs.