An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks
Abstract Energy efficiency plays a major role in sustaining lifespan and stability of the network, being one of most critical factors in wireless sensor networks (WSNs). To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vul...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-12-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-83005-2 |
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| author | Mohit Kumar Ashwani Kumar Sunil Kumar Piyush Chauhan Shitharth Selvarajan |
| author_facet | Mohit Kumar Ashwani Kumar Sunil Kumar Piyush Chauhan Shitharth Selvarajan |
| author_sort | Mohit Kumar |
| collection | DOAJ |
| description | Abstract Energy efficiency plays a major role in sustaining lifespan and stability of the network, being one of most critical factors in wireless sensor networks (WSNs). To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. The proposed AVOACS method improves clustering by including four critical terms: communication mode decider, distance of sink and nodes, residual energy and intra-cluster distance. Through mimicking the natural scavenging behavior of African vultures, AVOACS continuously balances energy consumption on nodes resulting in an increase in network stability and lifetime. For CH selection, we use AVOACS, which considers the following parameters: communication mode decider, the distance between sink and node, residual energy, and intra-cluster distance. In comparison to the OE2-LB protocol, simulation findings demonstrate that AVOACS enhances stability, network lifetime, and throughput by 21.5%, 31.4%, and 16.9%, respectively. The results show that AVOACS is an effective clustering algorithm for energy-efficient operation in heterogeneous WSN environments as it contributes to a large increase of network lifetime and significant enhancement of performance. |
| format | Article |
| id | doaj-art-32a5dd7931d247a8a53091e61d63f023 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-32a5dd7931d247a8a53091e61d63f0232024-12-29T12:17:36ZengNature PortfolioScientific Reports2045-23222024-12-0114111810.1038/s41598-024-83005-2An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networksMohit Kumar0Ashwani Kumar1Sunil Kumar2Piyush Chauhan3Shitharth Selvarajan4Department of Information Technology, School of Computing, MIT Art, Design and Technology UniversitySchool of Computer Science Engineering & Technology, Bennett UniversityDepartment of CSE, Galgotias College of Engineering & TechnologySymbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University)Department of Computer Science and Engineering, Chennai Institute of TechnologyAbstract Energy efficiency plays a major role in sustaining lifespan and stability of the network, being one of most critical factors in wireless sensor networks (WSNs). To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. The proposed AVOACS method improves clustering by including four critical terms: communication mode decider, distance of sink and nodes, residual energy and intra-cluster distance. Through mimicking the natural scavenging behavior of African vultures, AVOACS continuously balances energy consumption on nodes resulting in an increase in network stability and lifetime. For CH selection, we use AVOACS, which considers the following parameters: communication mode decider, the distance between sink and node, residual energy, and intra-cluster distance. In comparison to the OE2-LB protocol, simulation findings demonstrate that AVOACS enhances stability, network lifetime, and throughput by 21.5%, 31.4%, and 16.9%, respectively. The results show that AVOACS is an effective clustering algorithm for energy-efficient operation in heterogeneous WSN environments as it contributes to a large increase of network lifetime and significant enhancement of performance.https://doi.org/10.1038/s41598-024-83005-2AVOAWSNsCluster HeadSensor NetworksCMD |
| spellingShingle | Mohit Kumar Ashwani Kumar Sunil Kumar Piyush Chauhan Shitharth Selvarajan An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks Scientific Reports AVOA WSNs Cluster Head Sensor Networks CMD |
| title | An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks |
| title_full | An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks |
| title_fullStr | An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks |
| title_full_unstemmed | An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks |
| title_short | An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks |
| title_sort | african vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks |
| topic | AVOA WSNs Cluster Head Sensor Networks CMD |
| url | https://doi.org/10.1038/s41598-024-83005-2 |
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