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Power Optimization of Large Scale Mobile Cloud System Using Cooperative Cloudlets

机译:使用合作Cloudlets大规模移动云系统的功率优化

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Reducing the total power consumption and network delay are among the most interesting issues facing large scale Mobile Cloud Computing (MCC) systems and their ability to satisfy the Service Level Agreement (SLA). Such systems utilize cloudlet based infrastructure to support off-loading some of user's computationally heavy tasks to the cloudlets. However, the limited capabilities of the cloudlet system (in terms of the ability of serve different request type and the ability to serve users in large geographical regions) represent serious challenges to achieve those objectives. To cover the users demand for different types of services and in wide geographical regions, cloudlets cooperate among each others by passing user requests from one cloudlets to another. By adapting this cooperation, the total power consumption per request will be increased so that it includes the power consumption between the user and the local cloudlet and the power consumption of passing the request to a remote cloudlet. In this paper, we consider two types of cloudlets: local cloudlets and global cloudlets. The global cloudlets are a special kind of local cloudlets but with higher capabilities. The user can connect only to the local cloudlet and sends all its traffics to it. If the local cloudlet cannot serve the desired request, then the request is moved to other local cloudlet. If no local cloudlet can serve the request, then it is moved to a global cloudlet in which it can serve all service types. We optimize the power consumption for large scale cooperative cloudlets and evaluate the proposed model under two realistic scenarios. The result prove that the proposed model can be used to optimize power consumption in large scale MCC systems.
机译:降低总功耗和网络延迟是大规模移动云计算(MCC)系统的最有趣问题,以及他们满足服务级别协议(SLA)的能力。此类系统利用基于Cloudlet的基础架构来支持将一些用户的计算机计算繁忙的任务放在Cloudlets上。然而,Cloudlet系统的有限能力(就服务不同请求类型的能力而言,在大地理区域提供服务的能力方面)代表了实现这些目标的严重挑战。为了涵盖用户对不同类型的服务和广泛的地理区域的需求,Cloudlet通过将用户请求从一个Cloudlet传递给另一个Cloudlet来彼此之间配合。通过调整这种合作,将增加每个请求的总功耗,以便它包括用户和本地Cloudlet之间的功耗以及将请求传递给远程Cliblet的功耗。在本文中,我们考虑两种Cloudlets:本地Cloudlets和全局Cloudlets。全局Cloudlets是一种特殊的本地Cloudlet,但功能较高。用户只能连接到本地Cloudlet并将其所有流量发送到它。如果本地Cloudlet无法满足所需的请求,则请求将移动到其他本地Cloudlet。如果没有本地Cloudlet可以服务于请求,则它将移动到全局Cloudlet,其中它可以提供所有服务类型。我们优化大规模协作Cloudlet的功耗,并在两个现实场景下评估所提出的模型。结果证明了所提出的模型可用于优化大规模MCC系统中的功耗。

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