An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches

Energy utilization and inadequacy of sensor nodes are considered major drawbacks in wireless sensor networks (WSNs). This is because the sensor nodes use the battery for recharging energy. To overcome this issue WSN utilized a clustering-routing algorithm. This protocol divides the adjacent sensor n...

Full description

Autores:
Abraham, Robin
Vadivel, M.
Tipo de recurso:
Article of journal
Fecha de publicación:
2024
Institución:
Universidad Tecnológica de Bolívar
Repositorio:
Repositorio Institucional UTB
Idioma:
eng
OAI Identifier:
oai:repositorio.utb.edu.co:20.500.12585/13524
Acceso en línea:
https://hdl.handle.net/20.500.12585/13524
https://doi.org/10.32397/tesea.vol5.n1.548
Palabra clave:
Energy utilization
Routing
DSO
Cluster head
Elephant herding optimization
Network
Rights
openAccess
License
Robin Abraham, M. Vadivel - 2024
id UTB2_f5178aed4a9fd111f6919090a4bbed15
oai_identifier_str oai:repositorio.utb.edu.co:20.500.12585/13524
network_acronym_str UTB2
network_name_str Repositorio Institucional UTB
repository_id_str
dc.title.spa.fl_str_mv An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
dc.title.translated.spa.fl_str_mv An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
title An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
spellingShingle An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
Energy utilization
Routing
DSO
Cluster head
Elephant herding optimization
Network
title_short An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
title_full An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
title_fullStr An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
title_full_unstemmed An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
title_sort An Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization Approaches
dc.creator.fl_str_mv Abraham, Robin
Vadivel, M.
dc.contributor.author.eng.fl_str_mv Abraham, Robin
Vadivel, M.
dc.subject.eng.fl_str_mv Energy utilization
Routing
DSO
Cluster head
Elephant herding optimization
Network
topic Energy utilization
Routing
DSO
Cluster head
Elephant herding optimization
Network
description Energy utilization and inadequacy of sensor nodes are considered major drawbacks in wireless sensor networks (WSNs). This is because the sensor nodes use the battery for recharging energy. To overcome this issue WSN utilized a clustering-routing algorithm. This protocol divides the adjacent sensor nodes into separate clusters to choose a cluster head. Thus, the cluster head gathers information from all clusters and transmits it to the base station. In this article, the proposed method used cluster-based routing protocols to enhance energy efficiency and network lifetime. Moreover, this paper follows three stages to maximize energy efficiency. Initially, the clustering process is performed using dolphin swarm optimization (DSO), where a group of clusters is formed. Then the second stage is composed of cluster head selection among the group of clusters by elephant herding optimization (EHO) strategy. Finally, the collected data are necessary to forward to the base station for transferring the information. A specified path (routing) is selected by chicken swarm optimization (CSO). By using these algorithms, the network nodes support the balance of energy utilization. Experimental analysis proves when evaluated with existing methods the proposed technique has improved energy efficiency with an increase in network lifetime.
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-06-30 11:55:40
2025-05-21T19:15:48Z
dc.date.available.none.fl_str_mv 2024-06-30 11:55:40
dc.date.issued.none.fl_str_mv 2024-06-30
dc.type.spa.fl_str_mv Artículo de revista
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.driver.eng.fl_str_mv info:eu-repo/semantics/article
dc.type.coar.eng.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.local.eng.fl_str_mv Journal article
dc.type.content.eng.fl_str_mv Text
dc.type.version.eng.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.coarversion.eng.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
format http://purl.org/coar/resource_type/c_6501
status_str publishedVersion
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12585/13524
dc.identifier.url.none.fl_str_mv https://doi.org/10.32397/tesea.vol5.n1.548
dc.identifier.doi.none.fl_str_mv 10.32397/tesea.vol5.n1.548
dc.identifier.eissn.none.fl_str_mv 2745-0120
url https://hdl.handle.net/20.500.12585/13524
https://doi.org/10.32397/tesea.vol5.n1.548
identifier_str_mv 10.32397/tesea.vol5.n1.548
2745-0120
dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.references.eng.fl_str_mv M. Selvi, S. V. N. Santhosh Kumar, S. Ganapathy, A. Ayyanar, H. K. Nehemiah, and A. Kannan. An Energy Efficient Clustered Gravitational and Fuzzy Based Routing Algorithm in WSNs - Wireless Personal Communications. https://link.springer.com/article/10.1007/s11277-020-07705-4, aug 7 2020. [2] S. P. Singh and S. Sharma. A Survey on Cluster Based Routing Protocols in Wireless Sensor Networks. Procedia Computer Science, 45:687–695, 2015. [3] S. Khan, A. S. K. Pathan, and N. A. Alrajeh. Wireless Sensor Networks. apr 21 2016. [4] P. S. Mann and S. Singh. Energy-Efficient Hierarchical Routing for Wireless Sensor Networks: A Swarm Intelligence Approach. Wireless Personal Communications, 92(2):785–805, aug 8 2016. [5] S. M. Mahdi H. Daneshvar, Pardis Alikhah Ahari Mohajer, and Sayyed Majid Mazinani. Energy-efficient routing in wsn: A centralized cluster-based approach via grey wolf optimizer. IEEE Access, 7:170019–170031, 2019. [6] B. Jan, H. Farman, H. Javed, B. Montrucchio, M. Khan, and S. Ali. Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey. Wireless Communications and Mobile Computing, 2017:1–14, 2017. [7] A. K. Das, R. Chaki, and K. N. Dey. Cluster-based energy-aware routing scheme (CBEARS) for wireless sensor network. International Journal of Sensor Networks, 21(4):262, 2016. [8] H. Saidi, D. Gretete, and A. Adnane. Opportunistic routing in wireless sensors networks. Proceedings of the 2nd International Conference on Computing and Wireless Communication Systems, nov 14 2017. [9] D. Liu, M. Hou, Z. Cao, J. Wang, Y. He, and Y. Liu. Duplicate Detectable Opportunistic Forwarding in Duty-Cycled Wireless Sensor Networks. IEEE/ACM Transactions on Networking, 24(2):662–673, 4 2016. [10] Y. Liu, M. Dong, K. Ota, and A. Liu. Activetrust: Secure and Trustable Routing in Wireless Sensor Networks. IEEE Transactions on Information Forensics and Security, 11(9):2013–2027, 9 2016. [11] D. Sinha, R. Kumari, and S. Tripathi. Semisupervised Classification Based Clustering Approach in WSN for Forest Fire Detection. Wireless Personal Communications, 109(4):2561–2605, aug 23 2019. [12] P. A. Patil, R. S. Deshpande, and P. B. Mane. Trust and Opportunity Based Routing Framework in Wireless Sensor Network Using Hybrid Optimization Algorithm. Wireless Personal Communications, 115(1):415–437, jun 20 2020. [13] J. Bhola, S. Soni, and G. K. Cheema. Genetic algorithm based optimized leach protocol for energy efficient wireless sensor networks. Journal of Ambient Intelligence and Humanized Computing, 11(3):1281–1288, jul 18 2019. [14] Eyman Fathelrhman Ahmed Elsmany, Mohd Adib Omar, Tat-Chee Wan, and Altahir Abdalla Altahir. Eesra: Energy efficient scalable routing algorithm for wireless sensor networks. IEEE Access, 7:96974–96983, 2019. [15] C. Wang, X. Liu, H. Hu, Y. Han, and M. Yao. Energy-Efficient and Load-Balanced Clustering Routing Protocol for Wireless Sensor Networks Using a Chaotic Genetic Algorithm. IEEE Access, 8:158082–158096, 2020. [16] Gia Nhu Nguyen, Nin Ho Le Viet, A. Francis Saviour Devaraj, R. Gobi, and K. Shankar. Blockchain enabled energy efficient red deer algorithm based clustering protocol for pervasive wireless sensor networks. Sustainable Computing: Informatics and Systems, 28:100464, 2020. [17] Lakshmanarao Battula and P Vamsikrishna Raja. Power efficient gathering in sensor information systems protocol using k-means clustering algorithm. International Journal of Science, Engineering and Computer Technology, 6(4):133, 2016. [18] D. Sharma and G. Singh Tomar. Enhance PEGASIS Algorithm for Increasing the Life Time of Wireless Sensor Network. Materials Today: Proceedings, 29:372–380, 2020. [19] Amirhossein Barzin, Ahmad Sadegheih, Hassan Khademi Zare, and Mahbooeh Honarvar. A hybrid swarm intelligence algorithm for clustering-based routing in wireless sensor networks. Journal of Circuits, Systems and Computers, 29(10):2050163, 2020. [20] T. Bhowmik and I. Banerjee. An Improved PSOGSA for Clustering and Routing in WSNs. Wireless Personal Communications, 117(2):431–459, nov 23 2020. [21] A. N. Shahbaz, H. Barati, and A. Barati. Multipath routing through the firefly algorithm and fuzzy logic in wireless sensor networks. Peer-to-Peer Networking and Applications, 14(2):541–558, oct 9 2020. [22] S. Kaur and V. Grewal. A novel approach for particle swarm optimizationbased clustering with dual sink mobility in wireless sensor network. International Journal of Communication Systems, 33(16), aug 23 2020. [23] S. Sharma, S. Verma, and K. Jyoti. A New Bat Algorithm with Distance Computation Capability and Its Applicability in Routing for WSN. Advances in Intelligent Systems and Computing, pages 163–171, 2019. [24] T. Q. Wu, M. Yao, and J. H. Yang. Dolphin swarm algorithm. Frontiers of Information Technology & Electronic Engineering, 17(8):717–729, 8 2016. [25] G. G. Wang, S. Deb, and L. D. S. Coelho. Elephant Herding Optimization. 2015 3rd International Symposium on Computational and Business Intelligence (ISCBI), 12 2015. [26] Xianbing Meng, Yu Liu, Xiaozhi Gao, and Hengzhen Zhang. A new bio-inspired algorithm: Chicken swarm optimization. In Ying Tan, Yuhui Shi, and Carlos A. Coello Coello, editors, Advances in Swarm Intelligence, pages 86–94, Cham, 2014. Springer International Publishing. [27] N. Mazumdar and H. Om. Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks. International Journal of Communication Systems, 31(12), may 28 2018. [28] S. Prahadeeshwaran and G. Maria Priscilla. A hybrid elephant optimization algorithm-based cluster head selection to extend network lifetime in wireless sensor networks (wsns). EAI Endorsed Transactions on Energy Web, 8(31), 7 2020.
dc.relation.ispartofjournal.eng.fl_str_mv Transactions on Energy Systems and Engineering Applications
dc.relation.citationvolume.eng.fl_str_mv 5
dc.relation.citationstartpage.none.fl_str_mv 1
dc.relation.citationendpage.none.fl_str_mv 24
dc.relation.bitstream.none.fl_str_mv https://revistas.utb.edu.co/tesea/article/download/548/391
dc.relation.citationedition.eng.fl_str_mv Núm. 1 , Año 2024 : Transactions on Energy Systems and Engineering Applications
dc.relation.citationissue.eng.fl_str_mv 1
dc.rights.eng.fl_str_mv Robin Abraham, M. Vadivel - 2024
dc.rights.uri.eng.fl_str_mv https://creativecommons.org/licenses/by/4.0
dc.rights.accessrights.eng.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.creativecommons.eng.fl_str_mv This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.coar.eng.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Robin Abraham, M. Vadivel - 2024
https://creativecommons.org/licenses/by/4.0
This work is licensed under a Creative Commons Attribution 4.0 International License.
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.eng.fl_str_mv application/pdf
dc.publisher.eng.fl_str_mv Universidad Tecnológica de Bolívar
dc.source.eng.fl_str_mv https://revistas.utb.edu.co/tesea/article/view/548
institution Universidad Tecnológica de Bolívar
repository.name.fl_str_mv Repositorio Digital Universidad Tecnológica de Bolívar
repository.mail.fl_str_mv bdigital@metabiblioteca.com
_version_ 1858228398249213952
spelling Abraham, RobinVadivel, M.2024-06-30 11:55:402025-05-21T19:15:48Z2024-06-30 11:55:402024-06-30https://hdl.handle.net/20.500.12585/13524https://doi.org/10.32397/tesea.vol5.n1.54810.32397/tesea.vol5.n1.5482745-0120Energy utilization and inadequacy of sensor nodes are considered major drawbacks in wireless sensor networks (WSNs). This is because the sensor nodes use the battery for recharging energy. To overcome this issue WSN utilized a clustering-routing algorithm. This protocol divides the adjacent sensor nodes into separate clusters to choose a cluster head. Thus, the cluster head gathers information from all clusters and transmits it to the base station. In this article, the proposed method used cluster-based routing protocols to enhance energy efficiency and network lifetime. Moreover, this paper follows three stages to maximize energy efficiency. Initially, the clustering process is performed using dolphin swarm optimization (DSO), where a group of clusters is formed. Then the second stage is composed of cluster head selection among the group of clusters by elephant herding optimization (EHO) strategy. Finally, the collected data are necessary to forward to the base station for transferring the information. A specified path (routing) is selected by chicken swarm optimization (CSO). By using these algorithms, the network nodes support the balance of energy utilization. Experimental analysis proves when evaluated with existing methods the proposed technique has improved energy efficiency with an increase in network lifetime.application/pdfengUniversidad Tecnológica de BolívarRobin Abraham, M. Vadivel - 2024https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.utb.edu.co/tesea/article/view/548Energy utilizationRoutingDSOCluster headElephant herding optimizationNetworkAn Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization ApproachesAn Enhanced Energy Efficiency Routing for WSN based on Elephant Herding and Swarm Optimization ApproachesArtículo de revistainfo:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Journal articleTextinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85M. Selvi, S. V. N. Santhosh Kumar, S. Ganapathy, A. Ayyanar, H. K. Nehemiah, and A. Kannan. An Energy Efficient Clustered Gravitational and Fuzzy Based Routing Algorithm in WSNs - Wireless Personal Communications. https://link.springer.com/article/10.1007/s11277-020-07705-4, aug 7 2020. [2] S. P. Singh and S. Sharma. A Survey on Cluster Based Routing Protocols in Wireless Sensor Networks. Procedia Computer Science, 45:687–695, 2015. [3] S. Khan, A. S. K. Pathan, and N. A. Alrajeh. Wireless Sensor Networks. apr 21 2016. [4] P. S. Mann and S. Singh. Energy-Efficient Hierarchical Routing for Wireless Sensor Networks: A Swarm Intelligence Approach. Wireless Personal Communications, 92(2):785–805, aug 8 2016. [5] S. M. Mahdi H. Daneshvar, Pardis Alikhah Ahari Mohajer, and Sayyed Majid Mazinani. Energy-efficient routing in wsn: A centralized cluster-based approach via grey wolf optimizer. IEEE Access, 7:170019–170031, 2019. [6] B. Jan, H. Farman, H. Javed, B. Montrucchio, M. Khan, and S. Ali. Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey. Wireless Communications and Mobile Computing, 2017:1–14, 2017. [7] A. K. Das, R. Chaki, and K. N. Dey. Cluster-based energy-aware routing scheme (CBEARS) for wireless sensor network. International Journal of Sensor Networks, 21(4):262, 2016. [8] H. Saidi, D. Gretete, and A. Adnane. Opportunistic routing in wireless sensors networks. Proceedings of the 2nd International Conference on Computing and Wireless Communication Systems, nov 14 2017. [9] D. Liu, M. Hou, Z. Cao, J. Wang, Y. He, and Y. Liu. Duplicate Detectable Opportunistic Forwarding in Duty-Cycled Wireless Sensor Networks. IEEE/ACM Transactions on Networking, 24(2):662–673, 4 2016. [10] Y. Liu, M. Dong, K. Ota, and A. Liu. Activetrust: Secure and Trustable Routing in Wireless Sensor Networks. IEEE Transactions on Information Forensics and Security, 11(9):2013–2027, 9 2016. [11] D. Sinha, R. Kumari, and S. Tripathi. Semisupervised Classification Based Clustering Approach in WSN for Forest Fire Detection. Wireless Personal Communications, 109(4):2561–2605, aug 23 2019. [12] P. A. Patil, R. S. Deshpande, and P. B. Mane. Trust and Opportunity Based Routing Framework in Wireless Sensor Network Using Hybrid Optimization Algorithm. Wireless Personal Communications, 115(1):415–437, jun 20 2020. [13] J. Bhola, S. Soni, and G. K. Cheema. Genetic algorithm based optimized leach protocol for energy efficient wireless sensor networks. Journal of Ambient Intelligence and Humanized Computing, 11(3):1281–1288, jul 18 2019. [14] Eyman Fathelrhman Ahmed Elsmany, Mohd Adib Omar, Tat-Chee Wan, and Altahir Abdalla Altahir. Eesra: Energy efficient scalable routing algorithm for wireless sensor networks. IEEE Access, 7:96974–96983, 2019. [15] C. Wang, X. Liu, H. Hu, Y. Han, and M. Yao. Energy-Efficient and Load-Balanced Clustering Routing Protocol for Wireless Sensor Networks Using a Chaotic Genetic Algorithm. IEEE Access, 8:158082–158096, 2020. [16] Gia Nhu Nguyen, Nin Ho Le Viet, A. Francis Saviour Devaraj, R. Gobi, and K. Shankar. Blockchain enabled energy efficient red deer algorithm based clustering protocol for pervasive wireless sensor networks. Sustainable Computing: Informatics and Systems, 28:100464, 2020. [17] Lakshmanarao Battula and P Vamsikrishna Raja. Power efficient gathering in sensor information systems protocol using k-means clustering algorithm. International Journal of Science, Engineering and Computer Technology, 6(4):133, 2016. [18] D. Sharma and G. Singh Tomar. Enhance PEGASIS Algorithm for Increasing the Life Time of Wireless Sensor Network. Materials Today: Proceedings, 29:372–380, 2020. [19] Amirhossein Barzin, Ahmad Sadegheih, Hassan Khademi Zare, and Mahbooeh Honarvar. A hybrid swarm intelligence algorithm for clustering-based routing in wireless sensor networks. Journal of Circuits, Systems and Computers, 29(10):2050163, 2020. [20] T. Bhowmik and I. Banerjee. An Improved PSOGSA for Clustering and Routing in WSNs. Wireless Personal Communications, 117(2):431–459, nov 23 2020. [21] A. N. Shahbaz, H. Barati, and A. Barati. Multipath routing through the firefly algorithm and fuzzy logic in wireless sensor networks. Peer-to-Peer Networking and Applications, 14(2):541–558, oct 9 2020. [22] S. Kaur and V. Grewal. A novel approach for particle swarm optimizationbased clustering with dual sink mobility in wireless sensor network. International Journal of Communication Systems, 33(16), aug 23 2020. [23] S. Sharma, S. Verma, and K. Jyoti. A New Bat Algorithm with Distance Computation Capability and Its Applicability in Routing for WSN. Advances in Intelligent Systems and Computing, pages 163–171, 2019. [24] T. Q. Wu, M. Yao, and J. H. Yang. Dolphin swarm algorithm. Frontiers of Information Technology & Electronic Engineering, 17(8):717–729, 8 2016. [25] G. G. Wang, S. Deb, and L. D. S. Coelho. Elephant Herding Optimization. 2015 3rd International Symposium on Computational and Business Intelligence (ISCBI), 12 2015. [26] Xianbing Meng, Yu Liu, Xiaozhi Gao, and Hengzhen Zhang. A new bio-inspired algorithm: Chicken swarm optimization. In Ying Tan, Yuhui Shi, and Carlos A. Coello Coello, editors, Advances in Swarm Intelligence, pages 86–94, Cham, 2014. Springer International Publishing. [27] N. Mazumdar and H. Om. Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks. International Journal of Communication Systems, 31(12), may 28 2018. [28] S. Prahadeeshwaran and G. Maria Priscilla. A hybrid elephant optimization algorithm-based cluster head selection to extend network lifetime in wireless sensor networks (wsns). EAI Endorsed Transactions on Energy Web, 8(31), 7 2020.Transactions on Energy Systems and Engineering Applications5124https://revistas.utb.edu.co/tesea/article/download/548/391Núm. 1 , Año 2024 : Transactions on Energy Systems and Engineering Applications120.500.12585/13524oai:repositorio.utb.edu.co:20.500.12585/135242025-05-21 14:15:48.66https://creativecommons.org/licenses/by/4.0Robin Abraham, M. Vadivel - 2024metadata.onlyhttps://repositorio.utb.edu.coRepositorio Digital Universidad Tecnológica de Bolívarbdigital@metabiblioteca.com

Publicaciones similares