Simulation Research on Optimal Location of Congested Nodes in Mobile Network Based on Improved ant Colony Algorithm

With the rapid development of, the problem of network congestion has become more and more prominent. How to effectively manage bandwidth, make full use of network resources and avoid network congestion has become an urgent problem to be solved. The optimal location of congested nodes in the mobile network of the Internet of Things can effectively improve the safety factor of node devices in the mobile network. For the location of network congested nodes, it is necessary to construct a node distance function and perform nonlinear transformation on the location data of congested nodes. The traditional method takes the historical position of the node as the position of the anchor node, and the velocity value as the communication radius to assist the location of the congested node, but ignores the nonlinear transformation of the node location data, resulting in low positioning accuracy. This paper transforms the node location problem into a function optimization problem, applies the ant colony algorithm (ACO) to the node location problem, and proposes the node location algorithm based on the ant colony algorithm (ACOL). Due to the limitations of the ant colony algorithm, it is easy to lead to premature or slow convergence. The experimental results show that ACOL algorithm and AACOL algorithm have higher positioning accuracy than DV-Hop algorithm, and AACOL algorithm has more stable results and faster convergence speed than ACOL algorithm.