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Edge computing resource procurement: An online optimization approach

机译:边缘计算资源采购:一种在线优化方法

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Edge computing (EC) has emerged as a key technology in future communication networks to enhance user experience and enable various Internet of Things (IoT) applications. In this paper, we propose an online framework for edge computing resource procurement in which a marketplace (platform) is established between sellers (i.e., resource contributors) and buyers (i.e., resource purchasers). Each buyer has a certain budget for his procurement campaign. The sellers arrive to the platform in an online fashion and offer their computing capacities along with prices that they want to be compensated for their services. Upon the arrival of every new offer, the platform has to make an irrevocable decision, without knowing future information, to accept the offer or not and to allocate the accepted resource to which buyer. We present an efficient online optimization method that helps the platform maximize the total system utility with guaranteed performance. Indeed, the developed model can be applied to other interesting settings such as edge caching and content delivery with slight modifications. Finally, numerical studies are conducted to illustrate the effectiveness of the proposed solution approach.
机译:边缘计算(EC)已成为未来通信网络中的关键技术,以增强用户体验并启用各种物联网(IoT)应用程序。在本文中,我们提出了一种用于边缘计算资源采购的在线框架,其中在卖方(即资源贡献者)和买方(即资源购买者)之间建立了一个市场(平台)。每个购买者都有自己的采购活动预算。卖家以在线方式到达平台,并提供他们的计算能力以及他们希望通过服务获得补偿的价格。在收到每个新要约后,平台必须做出不撤消的决定,不知道未来的信息,是否接受要约,并将接受的资源分配给买方。我们提出了一种有效的在线优化方法,该方法可帮助平台在保证性能的情况下最大化系统的整体效用。确实,可以将开发的模型应用于其他有趣的设置,例如边缘缓存和内容传递(稍加修改)。最后,进行数值研究以说明所提出的解决方案方法的有效性。

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