Performance Optimization for Multi-agent Based Simulation in Grid Environments

Multi-agent based simulation (MABS) is a discrete event simulation technique used to study complex systems with entities having social and autonomous behavior. MABS applications are characterized by unpredictable execution behavior and high communication-to-computation ratio. In this paper, we propose an adaptation strategy to support efficient execution of large-scale MABS applications on typical Grid infrastructures. To achieve this objective, the behavior of MABS applications and the execution environment is investigated, in order to constantly obtain performance prediction models. These models will then be used to realize dynamic load balancing and resource allocation schemes. We discuss our basic approach, initial experimental results, the planned future research and an application of our research in the transportation and logistics simulation domain.