Performance improvements of interactive crowds simulations

Resumen

This thesis proposes different improvements of crowd systems in order to significantly enhance the performance of these systems. First, a distributed system architecture is proposed for simulating large crowds. This system is based on a networked-server interconnection scheme. Results demonstrate that this scheme can provide a good flexibility and scalability by distributing the elements of the system across different machines. In addition, different improvements are proposed for exploiting computational capabilities of multi-core and many-core platforms. Results show that the use of these platforms allows to increase the throughput of the simulation system. Performing crowd simulations in a distributed fashion requires some technique for efficiently managing the dynamic workload generated. For that reason, this thesis also studies different partitioning methods for distributing the crowd across the different computational resources available in the system. A fitness function is defined in order to compare the performance of the different methods and choose the method that best suits the crowd partitioning problem. Finally, this thesis proposes a visualization system for displaying images of the simulations. In order to provide the scalability required by the visualization system, it is designed in a distributed fashion. In this way, different cameras hosted by different machines can render different viewpoints of the same scene. Results show that the proposed design of the visualization system can provide the scalability and interactivity required by crowd simulations.