Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network

In Wireless Sensor Network (WSN), high transmission time occurs when search agent focuses on the same sensor nodes, while local optima problem happens when agent gets trapped in a blind alley during searching. Swarm intelligence algorithms have been applied in solving these problems including the An...

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Main Author:	Husna, Jamal Abdul Nasir
Format:	Thesis
Language:	eng eng eng
Published:	2020
Subjects:	T58.5-58.64 Information technology QA Mathematics
Online Access:	https://etd.uum.edu.my/8785/1/Deposit%20Permission_s900065.pdf https://etd.uum.edu.my/8785/2/s900065_01.pdf https://etd.uum.edu.my/8785/3/s900065_references.docx
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spelling	my-uum-etd.87852021-11-01T06:52:48Z Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network 2020 Husna, Jamal Abdul Nasir Ku Mahamud, Ku Ruhana Kamioka, Eiji Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts & Sciences T58.5-58.64 Information technology QA Mathematics In Wireless Sensor Network (WSN), high transmission time occurs when search agent focuses on the same sensor nodes, while local optima problem happens when agent gets trapped in a blind alley during searching. Swarm intelligence algorithms have been applied in solving these problems including the Ant Colony System (ACS) which is one of the ant colony optimization variants. However, ACS suffers from local optima and stagnation problems in medium and large sized environments due to an ineffective exploration mechanism. This research proposes a hybridization of Enhanced ACS and Tabu Search (EACS(TS)) algorithm for packet routing in WSN. The EACS(TS) selects sensor nodes with high pheromone values which are calculated based on the residual energy and current pheromone value of each sensor node. Local optima is prevented by marking the node that has no potential neighbour node as a Tabu node and storing it in the Tabu list. Local pheromone update is performed to encourage exploration to other potential sensor nodes while global pheromone update is applied to encourage the exploitation of optimal sensor nodes. Experiments were performed in a simulated WSN environment supported by a Routing Modelling Application Simulation Environment (RMASE) framework to evaluate the performance of EACS(TS). A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. The outcome of this research contributes an optimized routing algorithm for WSN. This will lead to a better quality of service and minimum energy utilization. 2020 Thesis https://etd.uum.edu.my/8785/ https://etd.uum.edu.my/8785/1/Deposit%20Permission_s900065.pdf text eng staffonly https://etd.uum.edu.my/8785/2/s900065_01.pdf text eng public https://etd.uum.edu.my/8785/3/s900065_references.docx text eng public other doctoral Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng eng
advisor	Ku Mahamud, Ku Ruhana Kamioka, Eiji
topic	T58.5-58.64 Information technology QA Mathematics
spellingShingle	T58.5-58.64 Information technology QA Mathematics Husna, Jamal Abdul Nasir Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
description	In Wireless Sensor Network (WSN), high transmission time occurs when search agent focuses on the same sensor nodes, while local optima problem happens when agent gets trapped in a blind alley during searching. Swarm intelligence algorithms have been applied in solving these problems including the Ant Colony System (ACS) which is one of the ant colony optimization variants. However, ACS suffers from local optima and stagnation problems in medium and large sized environments due to an ineffective exploration mechanism. This research proposes a hybridization of Enhanced ACS and Tabu Search (EACS(TS)) algorithm for packet routing in WSN. The EACS(TS) selects sensor nodes with high pheromone values which are calculated based on the residual energy and current pheromone value of each sensor node. Local optima is prevented by marking the node that has no potential neighbour node as a Tabu node and storing it in the Tabu list. Local pheromone update is performed to encourage exploration to other potential sensor nodes while global pheromone update is applied to encourage the exploitation of optimal sensor nodes. Experiments were performed in a simulated WSN environment supported by a Routing Modelling Application Simulation Environment (RMASE) framework to evaluate the performance of EACS(TS). A total of 6 datasets were deployed to evaluate the effectiveness of the proposed algorithm. Results showed that EACS(TS) outperformed in terms of success rate, packet loss, latency, and energy efficiency when compared with single swarm intelligence routing algorithms which are Energy-Efficient Ant-Based Routing (EEABR), BeeSensor and Termite-hill. Better performances were also achieved for success rate, throughput, and latency when compared to other hybrid routing algorithms such as Fish Swarm Ant Colony Optimization (FSACO), Cuckoo Search-based Clustering Algorithm (ICSCA), and BeeSensor-C. The outcome of this research contributes an optimized routing algorithm for WSN. This will lead to a better quality of service and minimum energy utilization.
format	Thesis
qualification_name	other
qualification_level	Doctorate
author	Husna, Jamal Abdul Nasir
author_facet	Husna, Jamal Abdul Nasir
author_sort	Husna, Jamal Abdul Nasir
title	Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
title_short	Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
title_full	Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
title_fullStr	Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
title_full_unstemmed	Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network
title_sort	hybridization of enhanced ant colony system and tabu search algorithm for packet routing in wireless sensor network
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2020
url	https://etd.uum.edu.my/8785/1/Deposit%20Permission_s900065.pdf https://etd.uum.edu.my/8785/2/s900065_01.pdf https://etd.uum.edu.my/8785/3/s900065_references.docx
_version_	1747828459999068160

Hybridization of enhanced ant colony system and Tabu search algorithm for packet routing in wireless sensor network

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