A Semifixed Clustering Routing Protocol Based on Improved ACO Algorithm for WSNs

• Published in: IEEE sensors journal Vol. 24; no. 21; pp. 34664 - 34675
• Main Authors: Zhou, Jiaqi, Zhang, Zhaohui, Zhong, Qin, Li, Jing
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptive algorithms; Algorithms; Ant colony optimization; cluster head (CH) rotation; Clustering; Clustering algorithms; Data communication; Data transmission; Energy consumption; Game theory; Head movement; Heuristic algorithms; load balancing; Monitoring; Network latency; Nodes; Routing; Routing (telecommunications); Routing protocols; Search algorithms; semifixed clustering (SFC); Wireless sensor networks; wireless sensor networks (WSNs)
• ISSN: 1530-437X; 1558-1748
• DOI: 10.1109/JSEN.2024.3416961

Wireless sensor networks (WSNs) are a kind of self-organizing network by deploying a large number of wireless sensor nodes in the monitoring area. To satisfy various restricted monitoring requirements of actual applications, WSNs are always used to collect the precise information. However, the batteries cannot be recharged once the nodes are deployed, which limits the network lifetime of WSNs. In order to prolong the lifetime of WSNs in this study, we propose a multihop routing algorithm based on semifixed clustering and improved ant colony optimization (SFC-IACO) algorithm. First, in the initial phase of the network, the network is divided into several fixed areas, and then, we make adjustments to each cluster and achieve the load balancing by evenly adjusting the number of nodes in the cluster. Next in the data transmission phase, we design an adjacency matrix related to the energy and distance. Aiming at avoiding the local optimal when searching for the optimal routing, we improve the ant colony algorithm (ACO) and present a multihop routing selection algorithm based on the IACO. Finally, in order to achieve energy balancing of the network when the network runs a certain number of rounds, a dynamic cluster head rotation mechanism and an energy consumption balance mechanism between clusters are adopted in this study, which balances the energy consumption of nodes in each cluster. Simulations demonstrate the strong performance of the proposed algorithm in terms of network lifetime compared with the existing algorithms. The simulation results show that compared with centralized energy-efficient clustering (CEEC), multi-hop routing protocol based on game theory and coverage optimization (MRP-GTCO), and low power and low latency (LPLL)-low-energy adaptive clustering hierarchy (LEACH) algorithms, SFC-IACO can effectively extend the network's lifetime by 41%, 80%, and 221%, respectively.