Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network
Energy-efficient optimization algorithm in wireless sensor network (WSN) is often based on solely cluster routing or multi-hop routing. The cluster optimization algorithm will form a cluster network by dividing the sensor nodes into few clusters where each cluster has a cluster head (CH) for data co...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
IEEE
2020
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| Subjects: | |
| Online Access: | https://eprints.ums.edu.my/id/eprint/26784/1/Metaheuristic%20Multi-Hop%20Clustering%20Optimization%20for%20Energy-Efficient%20Wireless%20Sensor%20Network.pdf https://eprints.ums.edu.my/id/eprint/26784/ |
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| Summary: | Energy-efficient optimization algorithm in wireless sensor network (WSN) is often based on solely cluster routing or multi-hop routing. The cluster optimization algorithm will form a cluster network by dividing the sensor nodes into few clusters where each cluster has a cluster head (CH) for data collection. On the other hand, multi-hop optimization algorithm will form a multi-hop network by transmitting data to base station (BS) through data multi-hopping between sensor nodes. However, cluster optimization algorithm suffers from the overburdens of CH nodes, while multi-hop optimization algorithm suffers from the overburdens of nodes which are near to the BS. Therefore, Genetic Algorithm-Cuckoo Search (GACS) is proposed and developed based on the multi-hop clustering model in this paper. GACS optimizes both intra-cluster and inter-cluster communications to enhance energy efficiency in WSN, extending the network lifetime. Based on the performance evaluation, GACS outperforms both Genetic Algorithm (GA)-based cluster optimization algorithm and Cuckoo Search (CS)-based multi-hop optimization algorithm. |
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