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Distributed QoS-aware scheduling optimization for resource-intensive mobile application in hybrid cloud

机译:在混合云中的资源密集型移动应用程序分布式QoS感知调度优化

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摘要

In the paper, the distributed scheduling optimization model for resource-intensive mobile application is proposed. Lagrangian method is applied to achieve distributed scheduling optimization in hybrid cloud. By decomposing the Kuhn-Tucker conditions into different roles of mobile user, public cloud supplier and local cloud supplier, the scheduling optimization problem in hybrid cloud is converted into a distributed problem. The system design and example of distributed scheduling optimization for resource intensive mobile application is also given. The local or public cloud provider uses service-level agreement (SLA) in determining the share of resources to be allocated to the mobile user. The distributed scheduling optimization algorithm for resource intensive mobile application is proposed, which includes three parts: local cloud agent scheduling optimization, public cloud service scheduling and mobile application QoS optimization. The experiments study how data size, request arrival rate, number of mobile users and mobility have effect on the proposed algorithm and other related works.
机译:本文提出了用于资源密集型移动应用程序的分布式调度优化模型。拉格朗日方法应用于在混合云中实现分布式调度优化。通过将Kuhn-Tucker条件分解成不同的移动用户,公共云供应商和本地云供应商的角色,混合云中的调度优化问题被转换为分布式问题。还给出了资源密集型移动应用程序的分布式调度优化的系统设计和示例。本地或公共云提供商使用服务级协议(SLA)确定要分配给移动用户的资源的份额。提出了用于资源密集型移动应用程序的分布式调度优化算法,包括三个部分:本地云代理调度优化,公共云服务调度和移动应用QoS优化。实验研究了数据大小,请求到达率,移动用户和移动性的数量如何对所提出的算法和其他相关工程产生影响。

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