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SMDP Based Cross-Area Resource Management for Vehicular Cloud Networks

机译:基于SMDP的车辆云网络跨区域资源管理

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Recent years have witnessed the emerging concept of Vehicular Cloud Networks (VCN) with the development of Internet of Vehicles and cloud computing. There is a common phenomenon that the loads and resources of local clouds (LCs) in different regions are seriously unbalanced in dynamic VCN as LCs are confronted with the shortage of resources and vehicles are featured by high mobility. As a consequence, we propose a cross-area resource management scheme (CRMS) based on semi-Markov decision process (SMDP) to alleviate this problem. In this scheme, a service migration mechanism plays an imperative role, which the local cloud needs to take the service requests from both local and neighboring cloud into account when allocating computing resources that we focus on in this paper. Considering the impact of different types of service requests on system revenue, we obtain the optimal policy of resource allocation adaptively through SMDP to maximize the long-term expected reward. Numerical results show the performance of the proposed CRMS has been significantly improved.
机译:近年来,随着车辆互联网和云计算的发展,目睹了车辆云网络(VCN)的新兴概念。存在常见的现象,即在动态VCN中,当地云(LCS)的载荷和资源在动态VCN中严重不平衡,因为LCS面对资源短缺,并且车辆具有高移动性。因此,我们提出了基于半马尔可夫决策过程(SMDP)的跨地资源管理方案(CRM)来缓解此问题。在该方案中,服务迁移机制扮演命令的作用,该作用是当地云在分配我们专注于本文的计算资源时,本地云需要从本地和邻近云中的服务请求。考虑到不同类型的服务请求对系统收入的影响,我们通过SMDP获得资源分配的最佳政策,以最大限度地提高长期预期奖励。数值结果表明,所提出的CRM的性能得到了显着改善。

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