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Workload balancing in distributed crowd simulations: the partitioning method

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Abstract

The simulation of large crowds of autonomous agents with a realistic behavior is still a challenge for several computer research communities. Distributed architectures can provide scalability to crowd simulations, but they require the use of efficient partitioning methods. Although convex hulls have been shown as very efficient structures for crowd partitioning, providing efficient workload balancing to large scale simulations is still an open issue. In this paper, we propose the integration of a workload balancing technique for crowd simulations within a partitioning method based on convex hulls. The region-based balancing technique reassigns agents to servers using a criterion of distance. The performance evaluation results show that this technique ensures the saturation avoidance of the servers in an homogeneous distributed system. This feature can increase the scalability of crowd simulations.

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Author information

Author notes

  1. Juan M. Orduña

    Present address: , Avda. Vicent Andrés Estellés, s/n. 46007, Burjassot (Valencia), Spain

Authors and Affiliations

  1. Departmento de Informática, Universidad de Valencia, Valencia, Spain

    Guillermo Vigueras, Miguel Lozano & Juan M. Orduña

Authors
  1. Guillermo Vigueras
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  2. Miguel Lozano
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  3. Juan M. Orduña
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Corresponding author

Correspondence to Juan M. Orduña.

Additional information

This work has been jointly supported by the Spanish MICINN, the European Commission FEDER funds, and the University of Valencia under grants Consolider-Ingenio 2010 CSD2006-00046, TIN2009-14475-C04-04, and V_SEGLES_PIE.

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Vigueras, G., Lozano, M. & Orduña, J.M. Workload balancing in distributed crowd simulations: the partitioning method. J Supercomput 58, 261–269 (2011). https://doi.org/10.1007/s11227-009-0375-5

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  • DOI: https://doi.org/10.1007/s11227-009-0375-5

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