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arXiv 1902.09055cs.NI
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Edge Federation:走向综合业务提供模型

Edge Federation: Towards an Integrated Service Provisioning Model

Xiaofeng Cao, Guoming Tang, Deke Guo, Yan Li, Weiming Zhang

摘要:

边缘计算是将云服务推向网络边缘的一种有前途的计算范例。为此,边缘基础设施提供商(EIP)需要将计算和存储资源带到网络边缘,并允许边缘服务提供商(ESP)为用户提供延迟关键型服务。目前,EIP更倾向于建立一系列私有边缘计算环境来满足用户的特定需求。这种资源配置机制严重限制了边缘计算的发展和传播,以满足不同的用户需求。为此,我们提出了一个集成的资源供应模型,命名为边缘联邦,无缝地实现跨独立的边缘计算提供商和云的资源合作和服务提供。为了有效地调度和利用跨多个EIP的资源,我们系统地将供应过程描述为一个大规模线性规划(LP)问题,并将其转化为一个容易解决的形式。因此,我们设计了一个动态的算法来处理不同的服务需求的用户。我们在多伦多市的基站网络进行了广泛的实验。与现有的固定契约模型和多宿主模型相比,边缘联盟可以分别降低EIP的总体成本23.3%至24.5%和15.5%至16.3%。

英文摘要:

Edge computing is a promising computing paradigm for pushing the cloud service to the network edge. To this end, edge infrastructure providers (EIPs) need to bring computation and storage resources to the network edge and allow edge service providers (ESPs) to provision latency-critical services to users. Currently, EIPs prefer to establish a series of private edge-computing environments to serve specific requirements of users. This kind of resource provisioning mechanism severely limits the development and spread of edge computing for serving diverse user requirements. To this end, we propose an integrated resource provisioning model, named edge federation, to seamlessly realize the resource cooperation and service provisioning across standalone edge computing providers and clouds. To efficiently schedule and utilize the resources across multiple EIPs, we systematically characterize the provisioning process as a large-scale linear programming (LP) problem and transform it into an easily solved form. Accordingly, we design a dynamic algorithm to tackle the varying service demands from users. We conduct extensive experiments over the base station networks in Toronto city. Compared with the existing fixed contract model and multihoming model, edge federation can reduce the overall cost of EIPs by 23.3% to 24.5%, and 15.5% to 16.3%, respectively.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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