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Hierarchical evolutionary game based dynamic cloudlet selection and bandwidth allocation for mobile cloud computing environment

机译:基于分层进化游戏的移动云计算环境动态小云选择和带宽分配

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摘要

To bridge the gap between the resource-constrained mobile devices and the resource-demanding applications, mobile cloud computing (MCC) emerges for offloading complex tasks to a cloud server. Based on this concept, cloudlets, which move available resource to the vicinity of the mobile network, enhance further the system accessibility and performance. Moreover, to strengthen the network capacity in traffic intensive area, dense small cell network (DSCN) is proposed as one of the promising solutions. In this study, the operation of cloudlets and DSCN is collaboratively studied in order to further improve the system performance. On the one hand, users can select a cloudlet and dynamically adapt the connection according to the performance and the cost, which is referred to as a user-essential dynamic cloudlet selection problem. On the other hand, a cloudlet needs to set the optimal selling price and the size of resource for the users, which is considered as a cloudlet resource allocation problem. To jointly address the problems of dynamic cloudlet selection and resource allocation, the authors propose a hierarchical evolutionary game to maximise the utilities. Simulation studies are carried out to demonstrate the effectiveness of the proposed algorithms, which, indeed, improve the entire system performance significantly.
机译:为了弥合资源受限的移动设备和资源需求的应用程序之间的鸿沟,出现了移动云计算(MCC),用于将复杂的任务卸载到云服务器。基于此概念,将可用资源移动到移动网络附近的小云进一步增强了系统的可访问性和性能。此外,为了增强交通密集区域的网络容量,提出了密集小小区网络(DSCN)作为有前途的解决方案之一。在这项研究中,协同研究了cloudlets和DSCN的操作,以进一步提高系统性能。一方面,用户可以选择一个cloudlet,并根据性能和成本动态调整连接,这被称为用户必需的动态cloudlet选择问题。另一方面,小云需要为用户设置最佳售价和资源大小,这被认为是小云资源分配问题。为了共同解决动态小云选择和资源分配的问题,作者提出了一种分级进化博弈,以最大化实用性。仿真研究证明了所提出算法的有效性,实际上,该算法显着提高了整个系统的性能。

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