An Experimental Analysis of a Robust Pheromone-Based Algorithm for the Patrolling Problem

Recently, the necessity to resolve the patrolling problem has become pressing. This problem is modeled using an undirected graph structure in which one or more agents patrol the graph and regularly visit each node with the shortest time interval possible. Some central controlled algorithms have been proposed to solve this problem. However, the reliability of these algorithms, which depends on the central controller and communication between the controller and each agent, is considered insufficient. Thus, algorithms with a central controller are not applicable to critical environments. As an alternative approach, some autonomous and distributed algorithms have been proposed to achieve higher reliability and robustness. In a previous paper, we proposed an autonomous and distributed algorithm, called pheromone- and inverse-degree-based Probabilistic Vertex-Ant-Walk (pidPVAW). pidPVAW uses a pheromone model corresponding to fixed points for agent communication and cooperative patrolling as an extension of pheromone-based PVAW (pPVAW). In this paper, we introduce a new parameter k to control the effect of the degree of the neighbor nodes on the agent decision to move. When $$k = 0$$, pidPVAW behaves like pPVAW; therefore, pidPVAW includes pPVAW. The parameter k controls how easily nodes with lower connectivity can be visited. We ran some computer simulations for the parameter k on square grid graphs and scale-free graphs, and showed its effect on the system.