Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks
Wireless sensor network is a hot research topic with massive applications in different domains. Generally, wireless sensor network comprises hundreds to thousands of sensor nodes, which communicate with one another by the use of radio signals. Some of the challenges exist in the design of wireless s...
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1177/1550147720949133 |
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doaj-eb8a95a69f7e4b5fa1000251091313bb2020-11-25T02:46:18ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772020-09-011610.1177/1550147720949133Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networksMohamed Elhoseny0R Sundar Rajan1Mohammad Hammoudeh2K Shankar3Omar Aldabbas4Faculty of Computers & Information, Mansoura University, Mansoura, EgyptDepartment of Information Technology, Kalasalingam Academy of Research and Education, Krishnankoil, IndiaDepartment of Computing & Mathematics, Manchester Metropolitan University, Manchester, UKDepartment of Computer Applications, Alagappa University, Karaikudi, IndiaFaculty of Engineering Technology, Al-Balqa’ Applied University, Amman, JordanWireless sensor network is a hot research topic with massive applications in different domains. Generally, wireless sensor network comprises hundreds to thousands of sensor nodes, which communicate with one another by the use of radio signals. Some of the challenges exist in the design of wireless sensor network are restricted computation power, storage, battery and transmission bandwidth. To resolve these issues, clustering and routing processes have been presented. Clustering and routing processes are considered as an optimization problem in wireless sensor network which can be resolved by the use of swarm intelligence–based approaches. This article presents a novel swarm intelligence–based clustering and multihop routing protocol for wireless sensor network. Initially, improved particle swarm optimization technique is applied for choosing the cluster heads and organizes the clusters proficiently. Then, the grey wolf optimization algorithm–based routing process takes place to select the optimal paths in the network. The presented improved particle swarm optimization–grey wolf optimization approach incorporates the benefits of both the clustering and routing processes which leads to maximum energy efficiency and network lifetime. The proposed model is simulated under an extension set of experimentation, and the results are validated under several measures. The obtained experimental outcome demonstrated the superior characteristics of the improved particle swarm optimization–grey wolf optimization technique under all the test cases.https://doi.org/10.1177/1550147720949133 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mohamed Elhoseny R Sundar Rajan Mohammad Hammoudeh K Shankar Omar Aldabbas |
spellingShingle |
Mohamed Elhoseny R Sundar Rajan Mohammad Hammoudeh K Shankar Omar Aldabbas Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks International Journal of Distributed Sensor Networks |
author_facet |
Mohamed Elhoseny R Sundar Rajan Mohammad Hammoudeh K Shankar Omar Aldabbas |
author_sort |
Mohamed Elhoseny |
title |
Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks |
title_short |
Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks |
title_full |
Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks |
title_fullStr |
Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks |
title_full_unstemmed |
Swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks |
title_sort |
swarm intelligence–based energy efficient clustering with multihop routing protocol for sustainable wireless sensor networks |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2020-09-01 |
description |
Wireless sensor network is a hot research topic with massive applications in different domains. Generally, wireless sensor network comprises hundreds to thousands of sensor nodes, which communicate with one another by the use of radio signals. Some of the challenges exist in the design of wireless sensor network are restricted computation power, storage, battery and transmission bandwidth. To resolve these issues, clustering and routing processes have been presented. Clustering and routing processes are considered as an optimization problem in wireless sensor network which can be resolved by the use of swarm intelligence–based approaches. This article presents a novel swarm intelligence–based clustering and multihop routing protocol for wireless sensor network. Initially, improved particle swarm optimization technique is applied for choosing the cluster heads and organizes the clusters proficiently. Then, the grey wolf optimization algorithm–based routing process takes place to select the optimal paths in the network. The presented improved particle swarm optimization–grey wolf optimization approach incorporates the benefits of both the clustering and routing processes which leads to maximum energy efficiency and network lifetime. The proposed model is simulated under an extension set of experimentation, and the results are validated under several measures. The obtained experimental outcome demonstrated the superior characteristics of the improved particle swarm optimization–grey wolf optimization technique under all the test cases. |
url |
https://doi.org/10.1177/1550147720949133 |
work_keys_str_mv |
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