Uneven clustering routing algorithm based on glowworm swarm optimization
An uneven clustering routing algorithm based on glowworm swarm optimization for wireless sensor networks (UCRA-GSO) is proposed to solve the Wireless sensor network (WSN) energy balance problem. We introduce factors such as cluster head density, cluster head proximity distance, cluster head energy,...
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| Veröffentlicht in: | Ad hoc networks Jg. 93; S. 101923 |
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Elsevier B.V
01.10.2019
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| Abstract | An uneven clustering routing algorithm based on glowworm swarm optimization for wireless sensor networks (UCRA-GSO) is proposed to solve the Wireless sensor network (WSN) energy balance problem. We introduce factors such as cluster head density, cluster head proximity distance, cluster head energy, and compactness of the cluster into a glowworm swarm optimization (GSO) method to find the optimal clustering method. The test case involves a forwarding-tree of two level gradients (single and multi-hop transmission) such that the distance between the sensor and the base station is determined by a cost function. The simulation results show that UCRA-GSO effectively extends the network's life cycle while balancing the network's energy dissipation. |
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| AbstractList | An uneven clustering routing algorithm based on glowworm swarm optimization for wireless sensor networks (UCRA-GSO) is proposed to solve the Wireless sensor network (WSN) energy balance problem. We introduce factors such as cluster head density, cluster head proximity distance, cluster head energy, and compactness of the cluster into a glowworm swarm optimization (GSO) method to find the optimal clustering method. The test case involves a forwarding-tree of two level gradients (single and multi-hop transmission) such that the distance between the sensor and the base station is determined by a cost function. The simulation results show that UCRA-GSO effectively extends the network's life cycle while balancing the network's energy dissipation. |
| ArticleNumber | 101923 |
| Author | Qin, Liu Xiuwu, Yu Mufang, Hu Ke, Zhang Yong, Liu Renrong, Xiao |
| Author_xml | – sequence: 1 givenname: Yu surname: Xiuwu fullname: Xiuwu, Yu organization: University of South China, Hunan 421001, China – sequence: 2 givenname: Liu surname: Qin fullname: Qin, Liu email: lqing8008@163.com organization: University of South China, Hunan 421001, China – sequence: 3 givenname: Liu surname: Yong fullname: Yong, Liu organization: University of South China, Hunan 421001, China – sequence: 4 givenname: Hu surname: Mufang fullname: Mufang, Hu organization: University of South China, Hunan 421001, China – sequence: 5 givenname: Zhang surname: Ke fullname: Ke, Zhang organization: University of South China, Hunan 421001, China – sequence: 6 givenname: Xiao surname: Renrong fullname: Renrong, Xiao organization: University of South China, Hunan 421001, China |
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| Cites_doi | 10.1109/JSEN.2015.2411598 10.1145/1456650.1456651 10.1155/2017/8946576 10.1109/ACCESS.2017.2666082 10.1016/j.eswa.2011.03.053 10.1109/JSEN.2016.2523061 10.1109/TWC.2015.2496596 10.1016/j.procs.2015.08.331 |
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| Keywords | Wireless sensor networks Routing algorithm Uneven clustering Glowworm swarm optimization |
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| SubjectTerms | Glowworm swarm optimization Routing algorithm Uneven clustering Wireless sensor networks |
| Title | Uneven clustering routing algorithm based on glowworm swarm optimization |
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