Journal of Soft Computing Paradigm
IRO Journals
Volume 2 — Issue 1 — March 2020

Intelligent and Adaptive Multi-Objective Optimization in WANET Using Bio Inspired Algorithms

https://doi.org/10.36548/jscp.2020.1.002
Subarna Shakya
Professor, Department of Electronics and Computer Engineering, Central Campus, Institute of Engineering, Pulchowk, Tribhuvan University, Pulchowk,Lalitpur, Nepal
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Shakya, Subarna. 2020. “Intelligent and Adaptive Multi-Objective Optimization in WANET Using Bio Inspired Algorithms”. Journal of Soft Computing Paradigm 2 (1): 13-23. https://doi.org/10.36548/jscp.2020.1.002.
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Keywords

— Adhoc Network
— Wireless Adhoc Network (WANET)
— Bio Inspired Computing
— Genetic Bee Colony Algorithm
— Adaptive and Intelligent Routing
Published: 27-03-2020

Abstract

A WANET is a specific type of Adhoc network with a community of specialized, self-organizing mobile devices. Because of the complex existence of mobile devices and wireless networking, the adhoc network communicating in wireless manner faces many problems related to the topological organizations , battery capacity limitations that results in energy restrictions, transmission of information, etc. The significant attributes of an adhoc network communicating in wireless manner are the quality of service and the percentage of energy used. Nowadays as the bio-inspired computing plays a major role in the research field. Specifically bio-inspired algorithms motivated by nature's actions are used immensely to accomplish optimization in issues faced in communication. Massive works have been reported in the recent years to enhance the quality of service utilizing the Bio-inspired computing due to its intelligent and adaptive nature. The paper proposes the intelligent and an adaptive routing employing the bio inspired genetic bee colony algorithm and the ant colony optimization to have optimized energy utilization maximizing the longevity of the network. The proposed method is evaluated suing the network simulator-2 on the basis of the energy utilization, longevity and the service quality (Throughput) of the network, the results observed for the method put forth were better compared to the existing methods.

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