pp. 1835-1847
S&M3292 Research Paper of Special Issue https://doi.org/10.18494/SAM4310 Published: June 15, 2023 Research on Energy-saving Strategy of Wireless Sensor Network Based on Improved Ant Colony Algorithm [PDF] Zhensong Ni, Shuri Cai, and Cairong Ni (Received January 7, 2023; Accepted May 10, 2023) Keywords: wireless sensor network, ant colony algorithm, bridge inspection, pheromone, balance of energy
On the basis of the ant colony routing algorithm, we propose an improved energy-efficient routing algorithm based on power-saving ant colony optimization (PSACO). Taking into account the residual energy of wireless sensors as a parameter, the proposed algorithm ensures the route between the source and destination nodes to be optimal more efficiently and quickly, and finds an optimal solution that prolongs the network’s lifetime as long as possible. In improving the previous ant colony routing algorithm, an advanced bionic intelligent algorithm is integrated as it is known for its excellent distribution and the on-demand energy-saving mechanism. The proposed algorithm selects the best path to balance the network load and achieve positive feedback using distributed computing. The test of the proposed algorithm for measuring the vibration characteristics of a bridge validates that the improved ant colony routing algorithm is energy-efficient and robust, and shows excellent network load balancing with positive feedback. Therefore, the improved ant colony routing algorithm proves its superiority in wireless sensor network routing.
Corresponding author: Shuri CaiThis work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Zhensong Ni, Shuri Cai, and Cairong Ni, Research on Energy-saving Strategy of Wireless Sensor Network Based on Improved Ant Colony Algorithm, Sens. Mater., Vol. 35, No. 6, 2023, p. 1835-1847. |