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Dan Chen, Roland Ewald, Georgios K Theodoropoulos, and Tonworio Oguara (2006)

Data Management in Distributed Simulation of Complex Systems

University of Birmingham, School of Computer Science.

Distributed simulation has emerged as an important instrument for studying large-scale complex systems. Such systems inherently consist of a large number of components, which operate in a large shared state space interacting with it in highly dynamic and unpredictable ways. Optimising access to the enormous shared data is crucial for achieving efficient simulation executions. This effort involves two major issues, data distribution and data accessing. In this paper, we discuss the issues of modelling shared data. We have developed a framework for distributed simulation of MAS, which uses a hierarchical infrastructure to manage the shared data and facilitate interoperation amongst agent simulation models. Our framework aims to reduce the cost of accessing shared data by dynamically redistributing shared data in the infrastructure according to the access pattern of the agent simulation models. Data accesses may take two forms: locating data according to a set of attribute value ranges (Range query) locating a particular state variable from the given identifier (ID query and update). This paper proposes two alternative routing approaches, namely the address-based approach, which locates data according to their address information, and the range-based approach, whose operation is based on looking up attribute value range information along the paths to the destinations. The two algorithms are discussed an analysed in the context of PDES-MAS, a framework for the distributed simulation of multi-agent systems, which uses a hierarchical infrastructure to manage the shared state space. The paper introduces a generic meta-simulation framework which is used to perform a quantitative comparative analysis of the proposed algorithms under various circumstances.