The aim of this work is to present the problem of Capacity Allocation for multiple classes of Big Data applications running in the Cloud. The objective is the minimization of the renting out costs subject to the fulfillment of QoS requirements expressed in terms of application deadlines. We propose a preliminary version of a tool embedding a local- search-based algorithm exploiting also an integer nonlinear mathematical formulation and a queueing network simulation to solve the problem.
Ciavotta, M., Gianniti, E., Ardagna, D. (2017). Capacity allocation for big data applications in the cloud. In ICPE 2017 - Companion of the 2017 ACM/SPEC International Conference on Performance Engineering (pp.175-176). Association for Computing Machinery, Inc [10.1145/3053600.3053630].
Capacity allocation for big data applications in the cloud
Ciavotta, M;
2017
Abstract
The aim of this work is to present the problem of Capacity Allocation for multiple classes of Big Data applications running in the Cloud. The objective is the minimization of the renting out costs subject to the fulfillment of QoS requirements expressed in terms of application deadlines. We propose a preliminary version of a tool embedding a local- search-based algorithm exploiting also an integer nonlinear mathematical formulation and a queueing network simulation to solve the problem.
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