In recent years, the fast development of mobile communications and cloud systems has substantially promoted edge computing. By pushing server resources to the edge, mobile service providers can deliver their content and services with enhanced performance, and mobile-network carriers can alleviate congestion in the core networks. Although edge computing has been attracting much interest, most current research is application-specific, and analysis is lacking from a business perspective of edge cloud providers (ECPs) that provide general-purpose edge cloud services to mobile service providers and users. In this article, we present a vision of general-purpose edge computing realized by multiple interconnected edge clouds, analyzing the business model from the viewpoint of ECPs and identifying the main issues to address to maximize benefits for ECPs. Specifically, we formalize the long-term revenue of ECPs as a function of server-resource allocation and public data-placement decisions subject to the amount of physical resources and inter-cloud data-transportation cost constraints. To optimize the long-term objective, we propose an online framework that integrates the drift-plus-penalty and primal-dual methods. With theoretical analysis and simulations, we show that the proposed method approximates the optimal solution in a challenging environment without having future knowledge of the system.
翻译:近年来,移动通信和云系统的快速发展极大地促进了边际计算。通过将服务器资源推向边际,移动服务供应商可以提供其内容和服务,提高性能,移动网络承运人可以缓解核心网络的拥挤。尽管边缘计算吸引了很大的兴趣,但目前大多数研究都是针对应用的,而且缺乏向移动服务供应商和用户提供一般用途边缘云服务的边缘云供应商和用户的商业视角分析。在本篇文章中,我们提出了一个通过多个相互关联的边际云实现的普通用途边际计算愿景,从 ECP的角度分析商业模式,并找出要解决的主要问题,以最大限度地为ECP带来好处。具体地说,我们正式确定ECP的长期收入是服务器资源分配和公共数据配置决定的一种功能,取决于实际资源的数量和相互交错的数据传输成本限制。为了优化长期目标,我们提议了一个将漂浮和原始方法结合起来的在线框架。通过理论分析和模拟,我们表明,拟议的方法在不具有挑战性环境方面最具挑战性的方法。我们表明,在不具有理论分析和模拟的情况下,我们提出了一种最具挑战性的方法。