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A Novel Clustering Strategy-Based Sink Path Optimization for Wireless Sensor Network
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DOI：10.1109/JSEN.2022.3199605.png)
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Abstract
En 中文
To optimize the path of mobile sinks in the wireless sensor network (WSN) and use of 5G signals to transmit information, a new clustering strategy is proposed, which not only balances the number of cluster nodes but also shortens the path of mobile sinks. By moving rendezvous points (RPs) to change the cluster position, we first propose a metaheuristics clustering algorithm named the dynamic clustering-based rectangular evolutionary algorithm (DCREA). The algorithm adjusts the clustering structure of the network by limiting the cluster movement range; then, it is optimized in combination with the greedy algorithm. Extensive experimental results show that this method can significantly shorten the path of the mobile sink, increase the efficiency of the mobile sink, and improve the quality of signal transmission while maintaining the balance of the cluster structure. The experimental results show that the DCREA is the most effective and indicate the effectiveness of the algorithm by comparing it with related recent algorithms.
Keywords:
Sensors
Clustering algorithms
Wireless sensor networks
Periodic structures
Metaheuristics
Heuristic algorithms
Energy consumption
Clustering
metaheuristics
mobile sink
path optimization
wireless sensor network (WSN)