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Power Optimization of Large Scale Mobile Cloud System Using Cooperative Cloudlets

机译:基于协作小云的大规模移动云系统功耗优化

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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)系统及其满足服务水平协议(SLA)的能力所面临的最有趣的问题。这样的系统利用基于Cloudlet的基础结构来支持将用户的一些计算繁重的任务卸载到Cloudlet。但是,cloudlet系统的有限功能(就满足不同请求类型的能力和为大型地理区域的用户提供服务的能力而言)对实现这些目标提出了严峻挑战。为了满足用户对不同类型的服务以及在广阔的地理区域中的需求,小云通过将用户请求从一个小云传递到另一个小云来相互协作。通过适应这种合作,每个请求的总功耗将增加,从而包括用户与本地小云之间的功耗以及将请求传递到远程小云的功耗。在本文中,我们考虑两种类型的小云:局部小云和全局小云。全局小云是一种特殊的本地小云,但功能更高。用户只能连接到本地cloudlet并将其所有流量发送给它。如果本地小云无法满足所需的请求,则将请求移至其他本地小云。如果没有本地cloudlet可以满足请求,则将其移到可以为所有服务类型提供服务的全局cloudlet。我们优化了大型协作小云的功耗,并在两种现实情况下评估了所提出的模型。结果证明,该模型可用于优化大型MCC系统的功耗。

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