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Budget constrained selection of cloud storage services for advanced processing in datacenters

机译:预算约束在数据中心中的高级处理中选择云存储服务的选择

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Large scale, cyber-infrastructure systems include a large base of heterogeneous data sources, geographically distributed. Cloud storage services can be an ideal candidate for storing all these data. However, it is difficult to find the optimal solution in order to select a set of storage providers, with respect to different multiple objectives of this type of systems, such as cost optimization, budget constraints, Quality of Service (QoS), load balancing etc. In this paper, we study the multi-objective optimization problem for storage service selection with budget constraints. We start from a real world case scenario and build our mathematical model for the optimization problem. Then we propose a linear programming technique to find a near optimal solution for the service selection problem.
机译:大规模,网络 - 基础设施系统包括大底座的异构数据源,地理分布。云存储服务可以是存储所有这些数据的理想候选者。但是,很难找到最佳解决方案,以便在这种类型的系统的不同多个目标方面选择一组存储提供商,例如成本优化,预算约束,服务质量(QoS),负载平衡等。在本文中,我们研究了使用预算约束的存储服务选择的多目标优化问题。我们从一个真实的世界案例场景开始,并建立我们的数学模型进行优化问题。然后我们提出了一种线性编程技术,可以找到服务选择问题的近最佳解决方案。

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