Congestion Control Method for Campus Opportunity Network based on Ant Colony Algorithm

Due to the limited storage resources of portable devices, congestion control has become a hot direction in opportunity networks. To address the issue of heavy loads on certain nodes, which can impact routing efficiency and overall network performance, this paper proposes a load-balancing algorithm based on ant colony optimization (ACO) in a campus environment. The congestion status is represented by the ratio of message drop receptions within a certain period and the occupancy of the cache. Path selection is based on the concentration of pheromones and the pheromones on the path are updated when a data transmission is completed. In the event of congestion, the algorithm prevents a large amount of data from entering the node and unloads the data to other nodes, even if they are not the optimal relay nodes. Experimental results demonstrate that the proposed algorithm effectively improves data transmission success rates, reduces network loads, and decreases the number of packet losses, especially under low latency conditions.