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

Soft Computing Strategies for Optimized Route Selection in Wireless Sensor Network

https://doi.org/10.36548/jscp.2020.1.001
Wang Haoxiang
Director and lead executive faculty member, GoPerception Laboratory, NY
S. Smys
Professor, Department of CSE, RVS Technical Campus, Coimbatore, India
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How to Cite

Haoxiang, Wang, and S. Smys. 2020. “Soft Computing Strategies for Optimized Route Selection in Wireless Sensor Network”. Journal of Soft Computing Paradigm 2 (1): 1-12. https://doi.org/10.36548/jscp.2020.1.001.
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Keywords

— Soft Computing
— Evolutionary Algorithms
— Performance Analysis
— Energy
— Network Life Time and Packet Delivery Ratio
Published: 24-02-2020

Abstract

The routing in the wireless sensor networks has significant part in enhancing the functioning of the network as the improper routing methodologies and the routing deteriorates the energy of the sensor networks, affecting the lifespan of the network, leading to link failures and the connectivity problems. The necessity to improve the network performance is the main focus of the paper, so the paper presents the performance analysis of the evolutionary algorithms such as Genetic Algorithm, Ant lion optimization, Particle swarm optimization and Ant colony optimization and evaluates the routes obtained using the fuzzy Petri Net model, to find out the optimal route for the wireless sensor networks. The simulation through the python in terms of the some resource validates the optimal path in terms of energy, network life time and the packet delivery ratio.

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