A Dual Cluster-Head Energy-Efficient Routing Algorithm Based on Canopy Optimization and K-Means for WSN
Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent...
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| Vydáno v: | Sensors (Basel, Switzerland) Ročník 22; číslo 24; s. 9731 |
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| Abstract | Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent battery replacement is not feasible. Therefore, it is important to reduce the energy consumption of sensors and extend the network lifetime. An effective way to achieve this is clustering. This paper proposes a dual cluster-head energy-efficient algorithm (DCK-LEACH), which is based on K-means and Canopy optimization. Considering that the K-means algorithm is sensitive to the location of the initial clustering centers, this paper uses both the dynamic Canopy algorithm and K-means algorithm for clustering. For cluster-head election, this algorithm uses a hierarchy to minimize the cluster-head burden and balance the network load. The primary cluster-head is selected by two objectives: the node’s residual energy and the distance from the node to the clustering center. The vice cluster-head is selected by the residual energy of the node, and the distance from the nodes to the base station. Simulator results show that DCK-LEACH significantly prolongs the energy-critical node lifetime and the network lifetime compared with existing protocols. |
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| AbstractList | Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent battery replacement is not feasible. Therefore, it is important to reduce the energy consumption of sensors and extend the network lifetime. An effective way to achieve this is clustering. This paper proposes a dual cluster-head energy-efficient algorithm (DCK-LEACH), which is based on K-means and Canopy optimization. Considering that the K-means algorithm is sensitive to the location of the initial clustering centers, this paper uses both the dynamic Canopy algorithm and K-means algorithm for clustering. For cluster-head election, this algorithm uses a hierarchy to minimize the cluster-head burden and balance the network load. The primary cluster-head is selected by two objectives: the node's residual energy and the distance from the node to the clustering center. The vice cluster-head is selected by the residual energy of the node, and the distance from the nodes to the base station. Simulator results show that DCK-LEACH significantly prolongs the energy-critical node lifetime and the network lifetime compared with existing protocols. Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent battery replacement is not feasible. Therefore, it is important to reduce the energy consumption of sensors and extend the network lifetime. An effective way to achieve this is clustering. This paper proposes a dual cluster-head energy-efficient algorithm (DCK-LEACH), which is based on K-means and Canopy optimization. Considering that the K-means algorithm is sensitive to the location of the initial clustering centers, this paper uses both the dynamic Canopy algorithm and K-means algorithm for clustering. For cluster-head election, this algorithm uses a hierarchy to minimize the cluster-head burden and balance the network load. The primary cluster-head is selected by two objectives: the node's residual energy and the distance from the node to the clustering center. The vice cluster-head is selected by the residual energy of the node, and the distance from the nodes to the base station. Simulator results show that DCK-LEACH significantly prolongs the energy-critical node lifetime and the network lifetime compared with existing protocols.Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent battery replacement is not feasible. Therefore, it is important to reduce the energy consumption of sensors and extend the network lifetime. An effective way to achieve this is clustering. This paper proposes a dual cluster-head energy-efficient algorithm (DCK-LEACH), which is based on K-means and Canopy optimization. Considering that the K-means algorithm is sensitive to the location of the initial clustering centers, this paper uses both the dynamic Canopy algorithm and K-means algorithm for clustering. For cluster-head election, this algorithm uses a hierarchy to minimize the cluster-head burden and balance the network load. The primary cluster-head is selected by two objectives: the node's residual energy and the distance from the node to the clustering center. The vice cluster-head is selected by the residual energy of the node, and the distance from the nodes to the base station. Simulator results show that DCK-LEACH significantly prolongs the energy-critical node lifetime and the network lifetime compared with existing protocols. |
| Audience | Academic |
| Author | Lu, Tao Li, Zhengliang Min, Qiusha Wu, Mei Chen, Jing |
| AuthorAffiliation | 3 School of Educational Information Technology, Central China Normal University, Wuhan 430079, China 1 School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China 2 School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan 430205, China |
| AuthorAffiliation_xml | – name: 2 School of Mathematics and Physics, Wuhan Institute of Technology, Wuhan 430205, China – name: 1 School of Computer Science and Engineering, Wuhan Institute of Technology, Wuhan 430205, China – name: 3 School of Educational Information Technology, Central China Normal University, Wuhan 430079, China |
| Author_xml | – sequence: 1 givenname: Mei orcidid: 0000-0001-8676-9432 surname: Wu fullname: Wu, Mei – sequence: 2 givenname: Zhengliang orcidid: 0000-0003-1471-8462 surname: Li fullname: Li, Zhengliang – sequence: 3 givenname: Jing orcidid: 0000-0001-9929-5846 surname: Chen fullname: Chen, Jing – sequence: 4 givenname: Qiusha surname: Min fullname: Min, Qiusha – sequence: 5 givenname: Tao orcidid: 0000-0001-8117-2012 surname: Lu fullname: Lu, Tao |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36560099$$D View this record in MEDLINE/PubMed |
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| Cites_doi | 10.1109/ICDS47004.2019.8942253 10.1007/s11277-021-09028-4 10.1108/SR-06-2016-0104 10.1016/j.cogsys.2018.10.021 10.1109/ACCESS.2022.3142082 10.1109/ACCESS.2019.2956068 10.1016/j.adhoc.2021.102692 10.1142/S0218126621500638 10.1007/s00521-019-04441-0 10.1109/EDiS49545.2020.9296444 10.1109/ACCESS.2019.2911190 10.1109/JIOT.2022.3195677 10.1504/IJES.2020.105935 10.3390/electronics11060869 10.1109/TCYB.2016.2526683 10.1109/ICCICT.2012.6398214 10.1109/INCET51464.2021.9456313 10.1109/ACCESS.2022.3163254 10.1109/ICE348803.2020.9122962 10.1109/CYBER.2015.7288132 10.1002/dac.4354 10.1002/dac.3407 10.3390/s19204579 10.1109/ACCESS.2020.2985495 10.1109/FCST.2015.61 10.3390/s22166085 10.1109/ICSESS.2017.8343043 10.1109/ICNSC.2016.7478994 10.1109/JSYST.2020.3010868 10.1109/LISAT.2016.7494136 10.1109/SAI.2015.7237270 10.1007/s00500-020-04955-z 10.1109/ICAA53760.2021.00090 10.1109/IEMCON.2015.7344478 10.1109/CENTCON52345.2021.9688050 10.3390/s20205865 |
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| References | Panchal (ref_25) 2021; 30 Qin (ref_32) 2017; 47 Gul (ref_27) 2022; 9 ref_14 ref_36 Lin (ref_40) 2019; 7 ref_35 Kuo (ref_38) 2015; 46 ref_12 ref_34 Lin (ref_3) 2021; 15 ref_33 Thangaramya (ref_39) 2020; 24 ref_10 Park (ref_9) 2021; 67 ref_31 He (ref_11) 2019; 7 ref_19 ref_18 ref_17 ref_16 ref_15 ref_37 Pattnaik (ref_41) 2020; 33 Gamal (ref_29) 2022; 10 Sathyamoorthy (ref_24) 2022; 122 Baz (ref_4) 2018; 31 Gherbi (ref_1) 2017; 37 Pitchaimanickam (ref_13) 2020; 32 Wu (ref_5) 2020; 14 ref_21 Panchal (ref_26) 2021; 123 ref_28 Arya (ref_30) 2022; 10 Mei (ref_20) 2020; 12 Lata (ref_2) 2020; 8 ref_8 Jesudurai (ref_22) 2019; 57 Bakaraniya (ref_23) 2013; 4 ref_7 ref_6 |
| References_xml | – ident: ref_8 doi: 10.1109/ICDS47004.2019.8942253 – volume: 122 start-page: 2745 year: 2022 ident: ref_24 article-title: Improved K-Means based Q Learning algorithm for optimal clustering and node balancing in WSN publication-title: Wireless Pers. Commun. doi: 10.1007/s11277-021-09028-4 – volume: 37 start-page: 12 year: 2017 ident: ref_1 article-title: A survey on clustering routing protocols in wireless sensor networks publication-title: Sens. Rev. doi: 10.1108/SR-06-2016-0104 – volume: 4 start-page: 1521 year: 2013 ident: ref_23 article-title: K-LEACH: An improved LEACH protocol for lifetime improvement in WSN publication-title: Int. J. Eng. Trends Technol. – volume: 14 start-page: 514 year: 2020 ident: ref_5 article-title: A many-objective optimization WSN energy balance model publication-title: KSII Trans. Internet Inf. Syst. – volume: 57 start-page: 101 year: 2019 ident: ref_22 article-title: An improved energy efficient cluster-head selection protocol using the double cluster-heads and data fusion methods for IoT applications publication-title: Cogn. Syst. Res. doi: 10.1016/j.cogsys.2018.10.021 – volume: 10 start-page: 9340 year: 2022 ident: ref_30 article-title: Performance analysis of deep learning-based routing protocol for an efficient data transmission in 5G WSN Communication publication-title: IEEE Access doi: 10.1109/ACCESS.2022.3142082 – volume: 7 start-page: 172505 year: 2019 ident: ref_11 article-title: Energy saving algorithm and simulation of wireless sensor networks based on clustering routing protocol publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2956068 – volume: 123 start-page: 1 year: 2021 ident: ref_26 article-title: EEHCHR: Energy efficient hybrid clustering and hierarchical routing for wireless sensor networks publication-title: Ad Hoc Netw. doi: 10.1016/j.adhoc.2021.102692 – volume: 30 start-page: 2150063 year: 2021 ident: ref_25 article-title: EADCR: Energy aware distance based cluster-head selection and routing protocol for wireless sensor networks publication-title: J. Circuits Syst. Comput. (World Sci.) doi: 10.1142/S0218126621500638 – volume: 32 start-page: 7709 year: 2020 ident: ref_13 article-title: A hybrid firefly algorithm with particle swarm optimization for energy efficient optimal cluster-head selection in wireless sensor networks publication-title: Neural Comput. Appl. doi: 10.1007/s00521-019-04441-0 – ident: ref_35 doi: 10.1109/EDiS49545.2020.9296444 – volume: 7 start-page: 49894 year: 2019 ident: ref_40 article-title: An energy-efficient clustering algorithm combined game theory and dual-cluster-head mechanism for WSNs publication-title: IEEE Access doi: 10.1109/ACCESS.2019.2911190 – volume: 9 start-page: 25150 year: 2022 ident: ref_27 article-title: UAV-Driven sustainable and Quality-Aware data collection in robotic wireless sensor networks publication-title: IEEE Internet Things J. doi: 10.1109/JIOT.2022.3195677 – volume: 12 start-page: 177 year: 2020 ident: ref_20 article-title: A hybrid optimisation algorithm based on GA algorithm and ACO algorithm improvements for routing selection in heterogeneous sensor networks publication-title: Int. J. Embed. Syst. doi: 10.1504/IJES.2020.105935 – ident: ref_18 doi: 10.3390/electronics11060869 – volume: 47 start-page: 772 year: 2017 ident: ref_32 article-title: Distributed K-Means algorithm and fuzzy C-Means algorithm for sensor networks based on multiagent consensus theory publication-title: IEEE Trans. Cybern. doi: 10.1109/TCYB.2016.2526683 – ident: ref_6 – ident: ref_19 doi: 10.1109/ICCICT.2012.6398214 – ident: ref_7 doi: 10.1109/INCET51464.2021.9456313 – volume: 10 start-page: 36935 year: 2022 ident: ref_29 article-title: Enhancing the lifetime of wireless sensor networks using fuzzy logic LEACH technique-based particle swarm optimization publication-title: IEEE Access doi: 10.1109/ACCESS.2022.3163254 – ident: ref_16 doi: 10.1109/ICE348803.2020.9122962 – ident: ref_34 doi: 10.1109/CYBER.2015.7288132 – volume: 33 start-page: e4354 year: 2020 ident: ref_41 article-title: Assimilation of fuzzy clustering approach and EHO-Greedy algorithm for efficient routing in WSN publication-title: Int. J. Commun. Syst. doi: 10.1002/dac.4354 – volume: 31 start-page: e3407 year: 2018 ident: ref_4 article-title: A new algorithm for cluster-head selection in LEACH protocol for wireless sensor networks publication-title: Int. J. Commun. Syst. doi: 10.1002/dac.3407 – ident: ref_33 doi: 10.3390/s19204579 – volume: 8 start-page: 66013 year: 2020 ident: ref_2 article-title: Fuzzy clustering algorithm for enhancing reliability and network lifetime of wireless sensor networks publication-title: IEEE Access doi: 10.1109/ACCESS.2020.2985495 – ident: ref_10 doi: 10.1109/FCST.2015.61 – ident: ref_31 doi: 10.3390/s22166085 – ident: ref_21 doi: 10.1109/ICSESS.2017.8343043 – ident: ref_37 doi: 10.1109/ICNSC.2016.7478994 – volume: 15 start-page: 4492 year: 2021 ident: ref_3 article-title: A social welfare theory-based energy-efficient cluster-head election scheme for WSNs publication-title: IEEE Syst. J. doi: 10.1109/JSYST.2020.3010868 – volume: 67 start-page: 4019 year: 2021 ident: ref_9 article-title: Enhanced KOCED routing protocol with k-means algorithm publication-title: Comput. Mater. Contin. – volume: 46 start-page: 1014 year: 2015 ident: ref_38 article-title: A CSMA-based MAC protocol for WLANs with automatic synchronization capability to provide hard quality of service guarantees publication-title: Comput. Netw. – ident: ref_15 doi: 10.1109/LISAT.2016.7494136 – ident: ref_36 doi: 10.1109/SAI.2015.7237270 – volume: 24 start-page: 16483 year: 2020 ident: ref_39 article-title: Intelligent fuzzy rule-based approach with outlier detection for secured routing in WSN publication-title: Soft Comput. doi: 10.1007/s00500-020-04955-z – ident: ref_12 doi: 10.1109/ICAA53760.2021.00090 – ident: ref_14 doi: 10.1109/IEMCON.2015.7344478 – ident: ref_17 doi: 10.1109/CENTCON52345.2021.9688050 – ident: ref_28 doi: 10.3390/s20205865 |
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| SubjectTerms | Algorithms canopy algorithm Clustering Communication Computer Communication Networks Energy consumption Energy management systems Energy use energy-efficient Environmental Monitoring K-means algorithm network lifetime Optimization Physical Phenomena Sensors Wireless sensor networks Wireless Technology Workloads |
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| Title | A Dual Cluster-Head Energy-Efficient Routing Algorithm Based on Canopy Optimization and K-Means for WSN |
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