Smooth Scaling Ahead: Progressive MAS Simulation from Single PCs to Grids

  • Les Gasser
  • Kelvin Kakugawa
  • Brant Chee
  • Marc Esteva
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3415)


The emerging “Computational Grid” infrastructure poses many new opportunities for the developing science of large scale multi-agent simulation. The ability to migrate agent experiments seamlessly from simple, local single-processor development tools to large-scale distributed simulation environments provides valuable new models for experimentation and software engineering: first develop local, flexible prototypes, then as they become more stable progressively deploy and experiment with them at larger scales. Currently this kind of progressive scalability is hard for both practical and theoretical reasons: Practically, most agent platforms are designed for just one environment of operation. Smooth scalability is more than a matter of increasing agent numbers. Smooth scaling requires clear integration and consistent alignment between a variety of MAS system and simulation architectures and differing underlying infrastructures. This paper reports on recent progress with our experimental platform MACE3J, which now simulates MAS models seamlessly across a variety of scales and architecture types, from single PCs, to Single System Image (SSI) multicomputers, to heterogeneous distributed Grid environments.


Grid Service Agent Simulation Globus Toolkit Smooth Scalability Execution Resource 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Les Gasser
    • 1
  • Kelvin Kakugawa
    • 1
  • Brant Chee
    • 1
  • Marc Esteva
    • 1
  1. 1.Graduate School of Library and Information ScienceUniversity of Illinois at Urbana-Champaign 

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