Epidemic Random Network Simulations in a Distributed Computing Environment

We discuss a computational system following the paradigm of distributed computing, which will allow us to simulate the epidemic propagation in random networks with large number of nodes up to one million. This paradigm consists of a server that delivers tasks to be carried out by client computers. When the task is finished, the client sends the obtained results to the server to be stored until all tasks are finished and then ready to be analysed. Finally, we show that this technique allows us to disclose the emergence of seasonal patterns in the respiratory syncytial virus transmission dynamics which do not appear neither in smaller systems nor in continuous systems.This paper has been supported by the Grant from the Universitat Politecnica de Valencia PAID-06-11 ref: 2087 and the Grant FIS PI-10/01433. The authors would like to thank the staff of the Facultad de Administracion de Empresas of the Universidad Politecnica de Valencia, in particular Mara Angeles Herrera, Teresa Solaz, and Jose Luis Real, and the staff of the CES Felipe II of Aranjuez for their help and for letting them use free computer rooms to carry out the Sisifo computations described in this paper. They would also like to acknowledge the BOINC community for its support and the many anonymous volunteers who joined thier project and helped them obtain the results so fast.Villanueva-Oller, J.; Acedo Rodríguez, L.; Moraño Fernández, JA.; Sánchez Sánchez, A. (2013). Epidemic Random Network Simulations in a Distributed Computing Environment. Abstract and Applied Analysis. 2013:1-10. https://doi.org/10.1155/2013/4628011102013PROULX, S., PROMISLOW, D., & PHILLIPS, P. (2005). Network thinking in ecology and evolution. Trends in Ecology & Evolution, 20(6), 345-353. doi:10.1016/j.tree.2005.04.004Traud, A. L., Mucha, P. 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