Managing Agent Sampling Probabilities in Irregular Networks

Abstract

Agent-based security can provide a good distributed solution to issues surrounding large real-world networks. Such networks are often modeled by small-world, scale-free, minimum-distance, or random (SFMR) graphs. If agents randomly wander nodes, then the irregularity found in these types of graphs gives rise to some nodes being visited more often than others. Assuming the system requires agents to uniformly visit and perform some set of tasks at nodes, then the cost of executing these tasks at every visited node can negatively impact the peformance of the system.