Improved Particle Swarm Optimization Based Distributed Energy-Efficient Opportunistic Algorithm for Clustering and Routing in WSNs
Wireless Sensor Networks (WSNs) have been employed in various real-time applications and addressed fundamental issues, such as limited power resources and network life. Several sensor nodes in a WSN monitor the actual world and relay discovered data to base stations. The biggest issue with WSN is th...
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| Format: | Article |
| Language: | English |
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University of Tehran
2023-03-01
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| Series: | Journal of Information Technology Management |
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| Online Access: | https://jitm.ut.ac.ir/article_91560_288bc624c0deb290552ef681a12e6247.pdf |
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| author | M. S. Sivagamasundari T. Thamaraimanalan S. Ramalingam K. Balachander |
| author_facet | M. S. Sivagamasundari T. Thamaraimanalan S. Ramalingam K. Balachander |
| author_sort | M. S. Sivagamasundari |
| collection | DOAJ |
| description | Wireless Sensor Networks (WSNs) have been employed in various real-time applications and addressed fundamental issues, such as limited power resources and network life. Several sensor nodes in a WSN monitor the actual world and relay discovered data to base stations. The biggest issue with WSN is that the sensors have a limited lifetime and use much electricity to relay data to the base station. This paper proposes an improved PSO-based Enhanced Distributed Energy Efficient Clustering (EDEEC) algorithm to extend the network's life and reduce power consumption. Clustering is the process of forming groups of sensor nodes. The cluster aims to improve the network's scalability, energy efficiency, and other characteristics. The particle swarm optimization algorithm is modified to obtain energy-efficient WSNs. The assessment is based on the essential WSN characteristics, including network lifetime and energy efficiency (power consumption). Compared to LEACH, HEED, and DEEC, our proposed IPSO-EDEEC uses less energy. |
| format | Article |
| id | doaj-art-ffbb0038388044679e0ead3cc19ee9a3 |
| institution | DOAJ |
| issn | 2008-5893 2423-5059 |
| language | English |
| publishDate | 2023-03-01 |
| publisher | University of Tehran |
| record_format | Article |
| series | Journal of Information Technology Management |
| spelling | doaj-art-ffbb0038388044679e0ead3cc19ee9a32025-08-20T03:06:13ZengUniversity of TehranJournal of Information Technology Management2008-58932423-50592023-03-0115Special Issue: Digital Twin Enabled Neural Networks Architecture Management for Sustainable Computing52010.22059/jitm.2023.9156091560Improved Particle Swarm Optimization Based Distributed Energy-Efficient Opportunistic Algorithm for Clustering and Routing in WSNsM. S. Sivagamasundari0T. Thamaraimanalan1S. Ramalingam2K. Balachander3Department of Electrical and Electronics Engineering, Amrita College of Engineering and Technology, Tamilnadu, India.Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, India.Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, Tamilnadu, India.Department of Electrical and Electronics Engineering, Karpagam Academy of Higher Education, Coimbatore, Tamilnadu, India.Wireless Sensor Networks (WSNs) have been employed in various real-time applications and addressed fundamental issues, such as limited power resources and network life. Several sensor nodes in a WSN monitor the actual world and relay discovered data to base stations. The biggest issue with WSN is that the sensors have a limited lifetime and use much electricity to relay data to the base station. This paper proposes an improved PSO-based Enhanced Distributed Energy Efficient Clustering (EDEEC) algorithm to extend the network's life and reduce power consumption. Clustering is the process of forming groups of sensor nodes. The cluster aims to improve the network's scalability, energy efficiency, and other characteristics. The particle swarm optimization algorithm is modified to obtain energy-efficient WSNs. The assessment is based on the essential WSN characteristics, including network lifetime and energy efficiency (power consumption). Compared to LEACH, HEED, and DEEC, our proposed IPSO-EDEEC uses less energy.https://jitm.ut.ac.ir/article_91560_288bc624c0deb290552ef681a12e6247.pdfsensor nodes (sn)wireless sensor network (wsn)network lifetimeenergy consumptionclusteringrouting |
| spellingShingle | M. S. Sivagamasundari T. Thamaraimanalan S. Ramalingam K. Balachander Improved Particle Swarm Optimization Based Distributed Energy-Efficient Opportunistic Algorithm for Clustering and Routing in WSNs Journal of Information Technology Management sensor nodes (sn) wireless sensor network (wsn) network lifetime energy consumption clustering routing |
| title | Improved Particle Swarm Optimization Based Distributed Energy-Efficient Opportunistic Algorithm for Clustering and Routing in WSNs |
| title_full | Improved Particle Swarm Optimization Based Distributed Energy-Efficient Opportunistic Algorithm for Clustering and Routing in WSNs |
| title_fullStr | Improved Particle Swarm Optimization Based Distributed Energy-Efficient Opportunistic Algorithm for Clustering and Routing in WSNs |
| title_full_unstemmed | Improved Particle Swarm Optimization Based Distributed Energy-Efficient Opportunistic Algorithm for Clustering and Routing in WSNs |
| title_short | Improved Particle Swarm Optimization Based Distributed Energy-Efficient Opportunistic Algorithm for Clustering and Routing in WSNs |
| title_sort | improved particle swarm optimization based distributed energy efficient opportunistic algorithm for clustering and routing in wsns |
| topic | sensor nodes (sn) wireless sensor network (wsn) network lifetime energy consumption clustering routing |
| url | https://jitm.ut.ac.ir/article_91560_288bc624c0deb290552ef681a12e6247.pdf |
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