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In many counterterrorism applications there is a need to protect Critical Key Infrastructures and Resources (CKIR) such as transportation systems, aviation, highway, maritime transportation, to name a few. In many of these applications, there is a need to secure hundreds of thousands to millions of miles of roadways and/or airways. To achieve the monitoring of such large CKIR systems there is a need to develop intelligent geographically and computationally distributed multi-agent based monitoring systems. The main focus of this paper is on issues related to agent scheduling in such a large multi-agent distributed system. We propose an architecture for the distributed dynamic agent communication based on the Message Passing Interface (MPI) and a dynamic scheduling algorithm. The goal of the proposed dynamic multi-agent multi-node data-aware scheduling algorithm is to minimize the system total execution time of the agents by dynamically balancing the computational load among different distributed nodes while scheduling the agents to run as much as possible on the computational nodes where data information, that the agents need to perform/finish their tasks, reside. The desired aim is to reduce data transfer overhead and latency, and therefore increase the overall system computational performance.