A mobile agent based approach for optimizing real-time geographically distributed control systems using swarm intelligence

Many geographically distributed control systems have an optimization requirement that is computationally complex and therefore cannot be computed within a deterministic schedule. A real-time distributed control system can have a partial system failure, and during the failure the control system must continue to function in some degraded fashion. To solve these distributed problems, most control systems use either a centralized global algorithm that can be affected by partial failures, or a local greedy algorithm that is robust but non-optimal. Mobile agent algorithms are another means of implementing a distributed approximation. Since mobile agents respond well to dynamic environments and tend to recover quickly from unexpected conditions, they appear well suited to distributed control systems.;In this research, we define an approach that employs a Mobile Agent algorithm for optimization real-time systems. We also create an Architecture Description Language to make mobile agents easier to use in distributed control systems. The research results provide a compelling case that mobile agent-based systems have significant merit for optimizing globally distributed real-time systems.