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Load-Balancing for Large Scale Situated Agent-based Simulations

Omar Rihawi 1, 2 Yann Secq 1, 2 Philippe Mathieu 1, 2
1 SMAC - Systèmes Multi-Agents et Comportements
CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
Abstract : In large scale agent-based simulations, memory and computational power requirements can increase dramatically because of high numbers of agents and interactions. To be able to simulate millions of agents, distributing the simulator on a computer network is promising, but raises some issues like: agents allocation and load-balancing between machines. In this paper, we study the best ways to automatically balance the loads between machines in large scale situations. We study the performance of two different applications with two different distribution approaches, and we show in our experimental results that some applications can automatically adapt the loads between machines and get alone a high performance in large scale simulations with one distribution approach than the other.
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Submitted on : Monday, December 28, 2015 - 6:34:32 PM
Last modification on : Friday, December 11, 2020 - 6:44:03 PM

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Omar Rihawi, Yann Secq, Philippe Mathieu. Load-Balancing for Large Scale Situated Agent-based Simulations. International Conference On Computational Science, ICCS 2015 — Computational Science at the Gates of Nature, Slawomir Koziel, Leifur Leifsson, Michael Lees, Valeria V. Krzhizhanovskaya, Jack Dongarra and Peter M.A. Sloot, Jun 2015, Reykjavik, Iceland. pp.90-99, ⟨10.1016/j.procs.2015.05.204⟩. ⟨hal-01248794⟩



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