Open Access

ARTICLE

Optimal Routing Protocol for Wireless Sensor Network Using Genetic Fuzzy Logic System

S. Zulaikha Beevi, Abdullah Alabdulatif^*

Computer Department, College of Sciences and Arts in Ar Rass, Qassim University, Ar Rass, Saudi Arabia

* Corresponding Author: Abdullah Alabdulatif. Email:

(This article belongs to the Special Issue: Next - Generation Secure Solutions for Wireless Communications, IoT and SDNs)

Computers, Materials & Continua 2022, 70(2), 4107-4122. https://doi.org/10.32604/cmc.2022.020292

Received 18 May 2021; Accepted 20 July 2021; Issue published 27 September 2021

Abstract

The wireless sensor network (WSN) is a growing sector in the network domain. By implementing it many industries developed smart task for different purposes. Sensor nodes interact with each other and this interaction technique are handled by different routing protocol. Extending the life of the network in WSN is a challenging issue because energy in sensor nodes are quickly drained. So the overall performance of WSN are degraded by this limitation. To resolve this unreliable low power link, many researches have provided various routing protocols to make the network as dependable and sustainable as possible. While speeding up the data delivery is also considered to be an effective approach to save energy. To achieve this objective, we propose a new energy efficient routing protocol using genetic fuzzy logic system. Our primary objective is to save energy by sending data packets via the shortest path. Numerous studies have proved that the clustering protocol plays an important role in prolonging the life of the sensor node in the WSN. Keeping up with this our second objective is selection of head node from a cluster. This cluster head is selected based on the availability of maximum residual energy among the nodes, lifetime of head-to-head link, and its minimum distance to the base station. The genetic fitness approach is proposed for optimal routing and the selection of cluster head (CH) is employed with fuzzy logic system. As a result, the genetic fuzzy logic system (GFLS) can effectively accelerate the process to solve this problem. MATLAB is used to deploy nodes in WSN. The performance is calculated in terms of efficiency, delay, packet delivery rate and network throughput. The performance is compared with previous pertinent work. The proposed approach has elevated its performance around 8% in packet delivery and 6% in overall network throughput.

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Keywords

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