Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf Optimizer
Energy efficiency is one of the main challenges in developing Wireless Sensor Networks (WSNs). Since communication has the largest share in energy consumption, efficient routing is an effective solution to this problem. Hierarchical clustering algorithms are a common approach to routing. This techni...
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8913518/ |
| _version_ | 1818557602782511104 |
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| author | S. M. Mahdi H. Daneshvar Pardis Alikhah Ahari Mohajer Sayyed Majid Mazinani |
| author_facet | S. M. Mahdi H. Daneshvar Pardis Alikhah Ahari Mohajer Sayyed Majid Mazinani |
| author_sort | S. M. Mahdi H. Daneshvar |
| collection | DOAJ |
| description | Energy efficiency is one of the main challenges in developing Wireless Sensor Networks (WSNs). Since communication has the largest share in energy consumption, efficient routing is an effective solution to this problem. Hierarchical clustering algorithms are a common approach to routing. This technique splits nodes into groups in order to avoid long-range communication which is delegated to the cluster head (CH). In this paper, we present a new clustering algorithm that selects CHs using the grey wolf optimizer (GWO). GWO is a recent swarm intelligence algorithm based on the behavior of grey wolves that shows impressive characteristics and competitive results. To select CHs, the solutions are rated based on the predicted energy consumption and current residual energy of each node. In order to improve energy efficiency, the proposed protocol uses the same clustering in multiple consecutive rounds. This allows the protocol to save the energy that would be required to reform the clustering. We also present a new dual-hop routing algorithm for CHs that are far from the base station and prove that the presented method ensures minimum and most balanced energy consumption while remaining nodes use single-hop communication. The performance of the protocol is evaluated in several different scenarios and it is shown that the proposed protocol improves network lifetime in comparison to a number of recent similar protocols. |
| first_indexed | 2024-12-14T00:01:41Z |
| format | Article |
| id | doaj.art-66c7a2654e24411cb3b88c941626aa3e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T00:01:41Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-66c7a2654e24411cb3b88c941626aa3e2022-12-21T23:26:19ZengIEEEIEEE Access2169-35362019-01-01717001917003110.1109/ACCESS.2019.29559938913518Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf OptimizerS. M. Mahdi H. Daneshvar0https://orcid.org/0000-0002-9125-3550Pardis Alikhah Ahari Mohajer1https://orcid.org/0000-0002-9155-3465Sayyed Majid Mazinani2https://orcid.org/0000-0002-2178-0048Department of Computer and Electrical Engineering, Imam Reza International University, Mashhad, IranDepartment of Computer and Electrical Engineering, Imam Reza International University, Mashhad, IranDepartment of Computer and Electrical Engineering, Imam Reza International University, Mashhad, IranEnergy efficiency is one of the main challenges in developing Wireless Sensor Networks (WSNs). Since communication has the largest share in energy consumption, efficient routing is an effective solution to this problem. Hierarchical clustering algorithms are a common approach to routing. This technique splits nodes into groups in order to avoid long-range communication which is delegated to the cluster head (CH). In this paper, we present a new clustering algorithm that selects CHs using the grey wolf optimizer (GWO). GWO is a recent swarm intelligence algorithm based on the behavior of grey wolves that shows impressive characteristics and competitive results. To select CHs, the solutions are rated based on the predicted energy consumption and current residual energy of each node. In order to improve energy efficiency, the proposed protocol uses the same clustering in multiple consecutive rounds. This allows the protocol to save the energy that would be required to reform the clustering. We also present a new dual-hop routing algorithm for CHs that are far from the base station and prove that the presented method ensures minimum and most balanced energy consumption while remaining nodes use single-hop communication. The performance of the protocol is evaluated in several different scenarios and it is shown that the proposed protocol improves network lifetime in comparison to a number of recent similar protocols.https://ieeexplore.ieee.org/document/8913518/Clusteringgrey wolf optimizerroutingWSN |
| spellingShingle | S. M. Mahdi H. Daneshvar Pardis Alikhah Ahari Mohajer Sayyed Majid Mazinani Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf Optimizer IEEE Access Clustering grey wolf optimizer routing WSN |
| title | Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf Optimizer |
| title_full | Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf Optimizer |
| title_fullStr | Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf Optimizer |
| title_full_unstemmed | Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf Optimizer |
| title_short | Energy-Efficient Routing in WSN: A Centralized Cluster-Based Approach via Grey Wolf Optimizer |
| title_sort | energy efficient routing in wsn a centralized cluster based approach via grey wolf optimizer |
| topic | Clustering grey wolf optimizer routing WSN |
| url | https://ieeexplore.ieee.org/document/8913518/ |
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