Abstract
The article focuses on the problem of computing resource management in systems offering data processing methods in service-based model. It proposes a new model for service requests processing based on a concept of dynamic service selection in such a way, which meets client’s requirements, while minimizing the service delivery cost for the service provider. The key innovation of the described approach is the utilization of machine learning methods for effective estimation of non-functional parameters and resource allocation decision-making.
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Falas, Ł., Juszczyszyn, K. (2017). Towards Effective Allocation of Resources in Service-Oriented Systems. In: Grzech, A., Świątek, J., Wilimowska, Z., Borzemski, L. (eds) Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part II. Advances in Intelligent Systems and Computing, vol 522. Springer, Cham. https://doi.org/10.1007/978-3-319-46586-9_12
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DOI: https://doi.org/10.1007/978-3-319-46586-9_12
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