Adaptive Wind Driven Optimization based Energy Aware Clustering Scheme for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) are utilised in a variety of applications due to their capacity to capture and transmit environmental data. Clustering has emerged as an efficient method for improving energy efficiency in WSNs. To resolve these issues, we propose an Adaptive Wind Driven Optimisation...

Full description

Bibliographic Details
Main Authors: K. Muthulakshmi, Sundar Prakash Balaji, S. Stephe, J. Vijayalakshmi
Format: Article
Language:English
Published: Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2024-01-01
Series:Tehnički Vjesnik
Subjects:
Online Access:https://hrcak.srce.hr/file/454990
_version_ 1797206187730534400
author K. Muthulakshmi
Sundar Prakash Balaji
S. Stephe
J. Vijayalakshmi
author_facet K. Muthulakshmi
Sundar Prakash Balaji
S. Stephe
J. Vijayalakshmi
author_sort K. Muthulakshmi
collection DOAJ
description Wireless Sensor Networks (WSNs) are utilised in a variety of applications due to their capacity to capture and transmit environmental data. Clustering has emerged as an efficient method for improving energy efficiency in WSNs. To resolve these issues, we propose an Adaptive Wind Driven Optimisation based Energy Aware Clustering Scheme (AWDO-EACS) for WSNs. The AWDO-EACS model presents an extended form of the Wind Driven Optimisation (WDO) algorithm, designated AWDO, with optimised inherent term values. The proposed model takes into account multiple objectives, such as energy consumption, distance, and end-to-end latency, in order to achieve superior energy efficiency and an extended network lifetime. To validate the efficacy of the AWDO-EACS model, extensive experiments with varying node counts were carried out. In terms of network stability, energy efficiency, end-to-end latency, packet delivery ratio, throughput, packet loss rate, and network lifetime, the results demonstrate that the AWDO-EACS outperforms contemporary clustering strategies. Specifically, the AWDO-EACS obtained a significant increase in energy efficiency, with a 27.35 percent improvement over existing clustering techniques for 20 nodes and an 83.41 percent improvement for 100 nodes. In addition, the end-to-end latency was considerably reduced, with a 96-round lifetime for 20 nodes and a 74-round lifetime for 100 nodes, compared to 37 and 20 rounds, respectively, for GA-LEACH and MW-LEACH. In addition, the AWDO-EACS demonstrated superior packet delivery performance, with a 99.32% delivery ratio for 100 nodes, eclipsing the 76.90% and 82.65% of GA-LEACH and MW-LEACH, respectively. Moreover, the AWDO-EACS model demonstrated a remarkably low packet loss rate of 0.68 percent for 100 nodes, compared to 23.10 percent for GA-LEACH and 17.35 percent for MW-LEACH. The effectiveness of the proposed AWDO-EACS model in enhancing the overall performance of WSNs is demonstrated.
first_indexed 2024-04-24T09:03:02Z
format Article
id doaj.art-8840c67dad9a487ca6bd613b57d09055
institution Directory Open Access Journal
issn 1330-3651
1848-6339
language English
last_indexed 2024-04-24T09:03:02Z
publishDate 2024-01-01
publisher Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
record_format Article
series Tehnički Vjesnik
spelling doaj.art-8840c67dad9a487ca6bd613b57d090552024-04-15T19:25:07ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392024-01-0131246647310.17559/TV-20230610000715Adaptive Wind Driven Optimization based Energy Aware Clustering Scheme for Wireless Sensor NetworksK. Muthulakshmi0Sundar Prakash Balaji1S. Stephe2J. Vijayalakshmi3Department of Electronics and Communication Engineering, Sri Krishna College of Technology, CoimbatoreDepartment of Electronics and Communication Engineering, Mookambigai College of Engineering, Keeranur, PudukkottaiDepartment of Electronics and Communication Engineering, K.Ramakrishnan College of Engineering, TiruchirapalliDepartment of Electronics and Communication Engineering, Kongu Engineering College, Perundurai, 638060, IndiaWireless Sensor Networks (WSNs) are utilised in a variety of applications due to their capacity to capture and transmit environmental data. Clustering has emerged as an efficient method for improving energy efficiency in WSNs. To resolve these issues, we propose an Adaptive Wind Driven Optimisation based Energy Aware Clustering Scheme (AWDO-EACS) for WSNs. The AWDO-EACS model presents an extended form of the Wind Driven Optimisation (WDO) algorithm, designated AWDO, with optimised inherent term values. The proposed model takes into account multiple objectives, such as energy consumption, distance, and end-to-end latency, in order to achieve superior energy efficiency and an extended network lifetime. To validate the efficacy of the AWDO-EACS model, extensive experiments with varying node counts were carried out. In terms of network stability, energy efficiency, end-to-end latency, packet delivery ratio, throughput, packet loss rate, and network lifetime, the results demonstrate that the AWDO-EACS outperforms contemporary clustering strategies. Specifically, the AWDO-EACS obtained a significant increase in energy efficiency, with a 27.35 percent improvement over existing clustering techniques for 20 nodes and an 83.41 percent improvement for 100 nodes. In addition, the end-to-end latency was considerably reduced, with a 96-round lifetime for 20 nodes and a 74-round lifetime for 100 nodes, compared to 37 and 20 rounds, respectively, for GA-LEACH and MW-LEACH. In addition, the AWDO-EACS demonstrated superior packet delivery performance, with a 99.32% delivery ratio for 100 nodes, eclipsing the 76.90% and 82.65% of GA-LEACH and MW-LEACH, respectively. Moreover, the AWDO-EACS model demonstrated a remarkably low packet loss rate of 0.68 percent for 100 nodes, compared to 23.10 percent for GA-LEACH and 17.35 percent for MW-LEACH. The effectiveness of the proposed AWDO-EACS model in enhancing the overall performance of WSNs is demonstrated.https://hrcak.srce.hr/file/454990clusteringenergy efficiencymetaheuristicsnetwork stabilityobjective functionWSN
spellingShingle K. Muthulakshmi
Sundar Prakash Balaji
S. Stephe
J. Vijayalakshmi
Adaptive Wind Driven Optimization based Energy Aware Clustering Scheme for Wireless Sensor Networks
Tehnički Vjesnik
clustering
energy efficiency
metaheuristics
network stability
objective function
WSN
title Adaptive Wind Driven Optimization based Energy Aware Clustering Scheme for Wireless Sensor Networks
title_full Adaptive Wind Driven Optimization based Energy Aware Clustering Scheme for Wireless Sensor Networks
title_fullStr Adaptive Wind Driven Optimization based Energy Aware Clustering Scheme for Wireless Sensor Networks
title_full_unstemmed Adaptive Wind Driven Optimization based Energy Aware Clustering Scheme for Wireless Sensor Networks
title_short Adaptive Wind Driven Optimization based Energy Aware Clustering Scheme for Wireless Sensor Networks
title_sort adaptive wind driven optimization based energy aware clustering scheme for wireless sensor networks
topic clustering
energy efficiency
metaheuristics
network stability
objective function
WSN
url https://hrcak.srce.hr/file/454990
work_keys_str_mv AT kmuthulakshmi adaptivewinddrivenoptimizationbasedenergyawareclusteringschemeforwirelesssensornetworks
AT sundarprakashbalaji adaptivewinddrivenoptimizationbasedenergyawareclusteringschemeforwirelesssensornetworks
AT sstephe adaptivewinddrivenoptimizationbasedenergyawareclusteringschemeforwirelesssensornetworks
AT jvijayalakshmi adaptivewinddrivenoptimizationbasedenergyawareclusteringschemeforwirelesssensornetworks