Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage

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 obj...

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Main Authors: Nor Azlina, Ab. Aziz, Zuwairie, Ibrahim, Kamarulzaman, Ab Aziz, Nor Hidayati, Abdul Aziz
Format: Conference or Workshop Item
Language:English
Published: IEEE 2019
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/24943/
http://umpir.ump.edu.my/id/eprint/24943/1/40.1%20Simulated%20kalman%20filter%20optimization%20algorithm%20for%20maximization.pdf
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author Nor Azlina, Ab. Aziz
Zuwairie, Ibrahim
Kamarulzaman, Ab Aziz
Nor Hidayati, Abdul Aziz
author_facet Nor Azlina, Ab. Aziz
Zuwairie, Ibrahim
Kamarulzaman, Ab Aziz
Nor Hidayati, Abdul Aziz
author_sort Nor Azlina, Ab. Aziz
building UMP Institutional Repository
collection Online Access
description 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.
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format Conference or Workshop Item
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institution Universiti Malaysia Pahang
institution_category Local University
language English
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publishDate 2019
publisher IEEE
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spelling ump-249432019-10-23T08:13:59Z http://umpir.ump.edu.my/id/eprint/24943/ Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage Nor Azlina, Ab. Aziz Zuwairie, Ibrahim Kamarulzaman, Ab Aziz Nor Hidayati, Abdul Aziz TJ Mechanical engineering and machinery 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. IEEE 2019-05 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24943/1/40.1%20Simulated%20kalman%20filter%20optimization%20algorithm%20for%20maximization.pdf Nor Azlina, Ab. Aziz and Zuwairie, Ibrahim and Kamarulzaman, Ab Aziz and Nor Hidayati, Abdul Aziz (2019) Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage. In: International Conference on Computer and Information Sciences, ICCIS 2019 , 3 - 4 April 2019 , Jouf University, Aljouf, Kingdom of Saudi Arabia. pp. 1-5.. ISBN 978-153868125-1 (Published) https://doi.org/10.1109/ICCISci.2019.8716387
spellingShingle TJ Mechanical engineering and machinery
Nor Azlina, Ab. Aziz
Zuwairie, Ibrahim
Kamarulzaman, Ab Aziz
Nor Hidayati, Abdul Aziz
Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
title Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
title_full Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
title_fullStr Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
title_full_unstemmed Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
title_short Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
title_sort simulated kalman filter optimization algorithm for maximization of wireless sensor networks coverage
topic TJ Mechanical engineering and machinery
url http://umpir.ump.edu.my/id/eprint/24943/
http://umpir.ump.edu.my/id/eprint/24943/
http://umpir.ump.edu.my/id/eprint/24943/1/40.1%20Simulated%20kalman%20filter%20optimization%20algorithm%20for%20maximization.pdf