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首页> 外文期刊>Journal of Cloud Computing: Advances, Systems and Applications >Efficient resource allocation and dimensioning of media edge clouds infrastructure
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Efficient resource allocation and dimensioning of media edge clouds infrastructure

机译:媒体边缘云基础架构的高效资源分配和规模确定

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Media Edge Cloud Data Centers (MEC-DCs) that are interconnected by a Metro Network were selected as infrastructure to enhance the Quality of Experience (QoE) for end users of multimedia applications. Unlike the traditional Data Centers, MEC-DCs, which are kept closer to the user, have limited availability of resources at a given Data Center. Therefore, it is of paramount importance for Infrastructure service providers to efficiently dimension and use the media resources in an environment where the applications have high resource demand and the infrastructure has limited availability. To perform this task dynamically, we first propose a resource allocation strategy that considers the physical characteristics of the networking layer while minimizing the costs of deploying media applications. Second, we analyze the different configurations of the networking layer in order to enhance the use of MEC-DCs resources and the QoE for the end-users. Simulation results show a clear advantage of this proposed optimization-based approach over the benchmarks in terms of provisioning costs, blocking ratio and resource use.
机译:通过城域网互连的媒体边缘云数据中心(MEC-DC)被选为基础设施,以提高多媒体应用最终用户的体验质量(QoE)。与传统的数据中心不同,MEC-DC与用户之间的距离更近,它们在给定数据中心的资源可用性有限。因此,对于基础结构服务提供商而言,在应用程序具有高资源需求且基础结构可用性有限的环境中,有效地确定尺寸并使用媒体资源至关重要。为了动态地执行此任务,我们首先提出一种资源分配策略,该策略应考虑网络层的物理特性,同时将部署媒体应用程序的成本降至最低。其次,我们分析网络层的不同配置,以增强最终用户对MEC-DCs资源和QoE的使用。仿真结果表明,在配置成本,阻塞率和资源使用方面,这种基于优化的建议方法比基准具有明显优势。

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