An energy aware cluster inspired routing protocol using multi strategy improved crayfish optimization algorithm for guaranteeing green communication in IoT

Internet of things (IoT) has a significant impact on environmental and economic factors for interconnecting billions or trillions of devices that utilize various types of sensors during communications using Internet. Energy is identified as the heart of smart IoT applications since it permits the se...

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Vydané v:	Scientific reports Ročník 15; číslo 1; s. 34815 - 24
Hlavní autori:	Chithra, R., Sarumathiy, C. K., Padma, E., Arulkumar, R.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 06.10.2025 Nature Publishing Group Nature Portfolio
Predmet:	639/705/117 639/705/258 Algorithms Alternative energy Cluster head (CH) selection Communication Decision making Economic factors Energy Energy consumption Energy management Environmental impact Green communication Humanities and Social Sciences Hybrid best worst method (BWM)-TOPSIS Internet of Things Internet of things (IoT) Multi-strategy improved crayfish optimization algorithm (MSICOA) multidisciplinary Multiple criteria decision making Multiple trusts Nodes Optimization algorithms Potential energy Science Science (multidisciplinary) Sensors Trust Trust management model Cluster head (CH) selection Hybrid best worst method (BWM)-TOPSIS Green communication Trust management model Internet of things (IoT) Multi-strategy improved crayfish optimization algorithm (MSICOA)
ISSN:	2045-2322, 2045-2322
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Abstract	Internet of things (IoT) has a significant impact on environmental and economic factors for interconnecting billions or trillions of devices that utilize various types of sensors during communications using Internet. Energy is identified as the heart of smart IoT applications since it permits the sensors to carry out their operations. Even though, sensors necessitate a small amount of energy for operations, rapid energy drain when billions and trillions of them interconnect is determined to crumble their performance by influencing energy stability. Clustering is the potential energy managing green communication mechanism which when implemented using metaheuristic techniques helps in achieving required quality of service by facilitating near-optimal solutions. In this paper, mult strategy-improved crayfish optimization algorithm-based intelligent clustering mechanism (MSCFOAICM) is proposed as a solution to the NP-hard problem of achieving green communication in IoT with maximized network lifetime. This MSCFOAICM scheme used a multi-objective fitness function that considered factors of delay, energy, distance, jitter and packet forwarding potential into account such that energy potent nodes are selected as cluster heads (CHs) during the clustering process. It uses multi-strategy-improved crayfish optimization algorithm for CH selection for establishing a better trade-off between exploration and exploitation. It then used a hybrid BWM-TOPSIS multicriteria decision making model for determining nodes’ trust using direct and indirect interaction to prevent selection of malicious nodes as CHs. This protocol also prevented low energy nodes to be selected as CHs depending on residual energy estimation during the trust computation process. The number of clusters built during the implementation is determined to be optimal as it aids in sustaining maximized energy and extending network lifetime. The results of MSCFOAICM scheme confirm better throughput of 18.14%, operating IoT nodes of 19.42% and reduced mean transmission delay of 18.42%, compared to the baseline schemes.
AbstractList	Internet of things (IoT) has a significant impact on environmental and economic factors for interconnecting billions or trillions of devices that utilize various types of sensors during communications using Internet. Energy is identified as the heart of smart IoT applications since it permits the sensors to carry out their operations. Even though, sensors necessitate a small amount of energy for operations, rapid energy drain when billions and trillions of them interconnect is determined to crumble their performance by influencing energy stability. Clustering is the potential energy managing green communication mechanism which when implemented using metaheuristic techniques helps in achieving required quality of service by facilitating near-optimal solutions. In this paper, mult strategy-improved crayfish optimization algorithm-based intelligent clustering mechanism (MSCFOAICM) is proposed as a solution to the NP-hard problem of achieving green communication in IoT with maximized network lifetime. This MSCFOAICM scheme used a multi-objective fitness function that considered factors of delay, energy, distance, jitter and packet forwarding potential into account such that energy potent nodes are selected as cluster heads (CHs) during the clustering process. It uses multi-strategy-improved crayfish optimization algorithm for CH selection for establishing a better trade-off between exploration and exploitation. It then used a hybrid BWM-TOPSIS multicriteria decision making model for determining nodes' trust using direct and indirect interaction to prevent selection of malicious nodes as CHs. This protocol also prevented low energy nodes to be selected as CHs depending on residual energy estimation during the trust computation process. The number of clusters built during the implementation is determined to be optimal as it aids in sustaining maximized energy and extending network lifetime. The results of MSCFOAICM scheme confirm better throughput of 18.14%, operating IoT nodes of 19.42% and reduced mean transmission delay of 18.42%, compared to the baseline schemes. Abstract Internet of things (IoT) has a significant impact on environmental and economic factors for interconnecting billions or trillions of devices that utilize various types of sensors during communications using Internet. Energy is identified as the heart of smart IoT applications since it permits the sensors to carry out their operations. Even though, sensors necessitate a small amount of energy for operations, rapid energy drain when billions and trillions of them interconnect is determined to crumble their performance by influencing energy stability. Clustering is the potential energy managing green communication mechanism which when implemented using metaheuristic techniques helps in achieving required quality of service by facilitating near-optimal solutions. In this paper, mult strategy-improved crayfish optimization algorithm-based intelligent clustering mechanism (MSCFOAICM) is proposed as a solution to the NP-hard problem of achieving green communication in IoT with maximized network lifetime. This MSCFOAICM scheme used a multi-objective fitness function that considered factors of delay, energy, distance, jitter and packet forwarding potential into account such that energy potent nodes are selected as cluster heads (CHs) during the clustering process. It uses multi-strategy-improved crayfish optimization algorithm for CH selection for establishing a better trade-off between exploration and exploitation. It then used a hybrid BWM-TOPSIS multicriteria decision making model for determining nodes’ trust using direct and indirect interaction to prevent selection of malicious nodes as CHs. This protocol also prevented low energy nodes to be selected as CHs depending on residual energy estimation during the trust computation process. The number of clusters built during the implementation is determined to be optimal as it aids in sustaining maximized energy and extending network lifetime. The results of MSCFOAICM scheme confirm better throughput of 18.14%, operating IoT nodes of 19.42% and reduced mean transmission delay of 18.42%, compared to the baseline schemes. Internet of things (IoT) has a significant impact on environmental and economic factors for interconnecting billions or trillions of devices that utilize various types of sensors during communications using Internet. Energy is identified as the heart of smart IoT applications since it permits the sensors to carry out their operations. Even though, sensors necessitate a small amount of energy for operations, rapid energy drain when billions and trillions of them interconnect is determined to crumble their performance by influencing energy stability. Clustering is the potential energy managing green communication mechanism which when implemented using metaheuristic techniques helps in achieving required quality of service by facilitating near-optimal solutions. In this paper, mult strategy-improved crayfish optimization algorithm-based intelligent clustering mechanism (MSCFOAICM) is proposed as a solution to the NP-hard problem of achieving green communication in IoT with maximized network lifetime. This MSCFOAICM scheme used a multi-objective fitness function that considered factors of delay, energy, distance, jitter and packet forwarding potential into account such that energy potent nodes are selected as cluster heads (CHs) during the clustering process. It uses multi-strategy-improved crayfish optimization algorithm for CH selection for establishing a better trade-off between exploration and exploitation. It then used a hybrid BWM-TOPSIS multicriteria decision making model for determining nodes' trust using direct and indirect interaction to prevent selection of malicious nodes as CHs. This protocol also prevented low energy nodes to be selected as CHs depending on residual energy estimation during the trust computation process. The number of clusters built during the implementation is determined to be optimal as it aids in sustaining maximized energy and extending network lifetime. The results of MSCFOAICM scheme confirm better throughput of 18.14%, operating IoT nodes of 19.42% and reduced mean transmission delay of 18.42%, compared to the baseline schemes.Internet of things (IoT) has a significant impact on environmental and economic factors for interconnecting billions or trillions of devices that utilize various types of sensors during communications using Internet. Energy is identified as the heart of smart IoT applications since it permits the sensors to carry out their operations. Even though, sensors necessitate a small amount of energy for operations, rapid energy drain when billions and trillions of them interconnect is determined to crumble their performance by influencing energy stability. Clustering is the potential energy managing green communication mechanism which when implemented using metaheuristic techniques helps in achieving required quality of service by facilitating near-optimal solutions. In this paper, mult strategy-improved crayfish optimization algorithm-based intelligent clustering mechanism (MSCFOAICM) is proposed as a solution to the NP-hard problem of achieving green communication in IoT with maximized network lifetime. This MSCFOAICM scheme used a multi-objective fitness function that considered factors of delay, energy, distance, jitter and packet forwarding potential into account such that energy potent nodes are selected as cluster heads (CHs) during the clustering process. It uses multi-strategy-improved crayfish optimization algorithm for CH selection for establishing a better trade-off between exploration and exploitation. It then used a hybrid BWM-TOPSIS multicriteria decision making model for determining nodes' trust using direct and indirect interaction to prevent selection of malicious nodes as CHs. This protocol also prevented low energy nodes to be selected as CHs depending on residual energy estimation during the trust computation process. The number of clusters built during the implementation is determined to be optimal as it aids in sustaining maximized energy and extending network lifetime. The results of MSCFOAICM scheme confirm better throughput of 18.14%, operating IoT nodes of 19.42% and reduced mean transmission delay of 18.42%, compared to the baseline schemes.
ArticleNumber	34815
Author	Chithra, R. Arulkumar, R. Padma, E. Sarumathiy, C. K.
Author_xml	– sequence: 1 givenname: R. surname: Chithra fullname: Chithra, R. email: chithra@ksrct.ac.in organization: Department of Information Technology, K. S. Rangasamy College of Technology – sequence: 2 givenname: C. K. surname: Sarumathiy fullname: Sarumathiy, C. K. organization: Department of Computer Science and Engineering, Nitte Meenakshi Institute of Technology(NMIT), Nitte (Deemed to be University) – sequence: 3 givenname: E. surname: Padma fullname: Padma, E. organization: Department of Computer Science and Engineering, Vels Institute of Science, Technology and Advanced Studies (VISTAS) Pallavaram – sequence: 4 givenname: R. surname: Arulkumar fullname: Arulkumar, R. organization: Department of Information Technology, Jeppiaar Institute of Technology
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Cites_doi	10.1109/TGCN.2022.3143991 10.1016/j.adhoc.2020.102215 10.1002/dac.5976 10.1016/j.micpro.2023.104892 10.1016/j.adhoc.2019.102053 10.23919/JCC.ja.2022-0665 10.1007/s12083-021-01099-1 10.3390/s22103910 10.1016/j.compeleceng.2024.109946 10.3390/app14041615 10.1038/s41598-024-82311-z 10.1007/s12083-022-01388-3 10.1016/j.adhoc.2024.103752 10.1038/s41598-025-07404-9 10.3390/su16031160 10.1016/j.egyr.2024.05.021 10.1186/s44147-024-00464-0 10.1002/dac.70050 10.1007/s41870-024-02399-4 10.1002/dac.4806 10.1504/IJMC.2025.144194 10.1002/ett.4595 10.1186/s44147-025-00603-1 10.1002/dac.v38.1310.1002/dac.70171 10.1155/2023/3507600 10.1038/s41598-025-15345-6 10.1142/S0219622023500220 10.1002/dac.70037 10.1002/itl2.646 10.1016/j.adhoc.2025.103830 10.1007/s44227-024-00041-0 10.1038/s41598-025-94550-9 10.1007/s10462-024-10738-x 10.1002/spy2.70004 10.1007/s10922-025-09899-z 10.1016/j.iot.2023.101013
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Keywords	Cluster head (CH) selection Hybrid best worst method (BWM)-TOPSIS Green communication Trust management model Internet of things (IoT) Multi-strategy improved crayfish optimization algorithm (MSICOA)
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SubjectTerms	639/705/117 639/705/258 Algorithms Alternative energy Cluster head (CH) selection Communication Decision making Economic factors Energy Energy consumption Energy management Environmental impact Green communication Humanities and Social Sciences Hybrid best worst method (BWM)-TOPSIS Internet of Things Internet of things (IoT) Multi-strategy improved crayfish optimization algorithm (MSICOA) multidisciplinary Multiple criteria decision making Multiple trusts Nodes Optimization algorithms Potential energy Science Science (multidisciplinary) Sensors Trust Trust management model
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Title	An energy aware cluster inspired routing protocol using multi strategy improved crayfish optimization algorithm for guaranteeing green communication in IoT
URI	https://link.springer.com/article/10.1038/s41598-025-18774-5 https://www.ncbi.nlm.nih.gov/pubmed/41053345 https://www.proquest.com/docview/3257730260 https://www.proquest.com/docview/3258101117 https://doaj.org/article/3a9279b79397412db4db7d91743f4496
Volume	15
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