Abstract
Volunteer computing systems provide a middleware for interaction between project owners and great number volunteers. In this chapter, a genetic programming paradigm has been proposed to a multi-objective scheduler design for efficient using some resources of volunteer computers via the web. In a studied problem, genetic scheduler can optimize both a workload of a bottleneck computer and cost of system. Genetic programming has been applied for finding the Pareto solutions by applying an immunological procedure. Finally, some numerical experiment outcomes have been discussed.
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Balicki, J., Korłub, W., Krawczyk, H., Paluszak, J. (2014). Genetic Programming for Interaction Efficient Supporting in Volunteer Computing Systems. In: S. Hippe, Z., L. Kulikowski, J., Mroczek, T., Wtorek, J. (eds) Issues and Challenges in Artificial Intelligence. Studies in Computational Intelligence, vol 559. Springer, Cham. https://doi.org/10.1007/978-3-319-06883-1_11
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DOI: https://doi.org/10.1007/978-3-319-06883-1_11
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