Comparison of bat algorithm, PSO, and GA for improved allocation of wireless sensor networks

Name: Somporn Tiacharoen

Organization : King Mongkut's University of Technology North Bangkok. College of Industrial Technology

keyword: Particle swarm optimization

LCSH: Wireless Sensor Networks

LCSH: Genetic algorithms

Abstract: Wireless sensor networks have a majority of tasks in transmitted and receiving data from sensors, which monitor or control the environment. The drawback in wireless sensor networks is the sensors' power, and energy is limited in a battery. In this article, the researcher proposed a comparison of metaheuristic algorithms are Bat Algorithm, PSO, and GA for improved allocation of wireless sensor networks. For all algorithms, the objective is to reduce coverage hole area. The hole is defined as a space between sensor nodes. Optimization from those algorithms the hole is reduced by sensors node is moved to serve that the position. The simulation result is showing a final location of a sensor node is can serving the overall area. Using the BAT algorithm, the results comparison shows that it better than the GA and PSO methods.

King Mongkut's University of Technology North Bangkok. Central Library

Address: BANGKOK

Email: library@kmutnb.ac.th

Created: 2022

Modified: 2022-10-07

Issued: 2022-10-07

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BibliograpyCitation : In King Mongkut's University of Technology North Bangkok Faculty of Technical Education. The 14th National Conference on Technical Education and the 9th International Conference on Technical Education (NCTechED 14th and ICTechED 9th) (pp.451-455). Bangkok : King Mongkut's University of Technology North Bangkok

eng

©copyrights King Mongkut's University of Technology North Bangkok

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