Citation

Ab. Aziz, Kamarulzaman and Ab Aziz, Nor Azlina and Abdul Aziz, Nor Hidayati and Ibrahim, Zuwairie (2019) Simulated Kalman Filter Optimization Algorithm for Maximization of Wireless Sensor Networks Coverage. In: 2019 International Conference on Computer and Information Sciences, ICCIS 2019, 3-4 April 2019, Sakaka, Saudi Arabia.

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Abstract

Simulated Kalman Filter (SKF) is a population based optimization algorithm inspired by the Kalman filtering method. It had been successfully used for optimization of many engineering problems. In this work SKF is applied for wireless sensor networks (WSN) coverage optimization problem, where the objective is to maximize the area covered by the sensors in a region of interest. Coverage is an important issue in WSN. It is used as one of the measurement metric for a WSN's quality of service. Many metaheuristics algorithms had been applied to solve this problem. Here, SKF is tested over several WSN and found to be able to perform better than particle swarm optimization (PSO) and genetic algorithm (GA) in improving WSN coverage.

Item Type:	Conference or Workshop Item (Paper)
Uncontrolled Keywords:	Wireless sensor networks
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	07 Jan 2022 03:03
Last Modified:	21 Dec 2022 06:23
URII:	http://shdl.mmu.edu.my/id/eprint/8952

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