论文标题
混合边缘云计算系统中的在线资源采购和分配
Online Resource Procurement and Allocation in a Hybrid Edge-Cloud Computing System
论文作者
论文摘要
通过在网络边缘获得类似云的能力，Edge Computing有望显着改善用户体验。在本文中，我们制定了一个混合边缘云计算系统，其中有限的本地资源的边缘设备可以从云节点租用更多并执行资源分配以服务于用户。资源采购和分配决策不仅取决于云的多个租赁选项，还取决于Edge的本地处理成本和容量。我们首先提出了一种离线算法，其决定是通过未来需求的全部信息做出的。然后，提出了一种在线算法，边缘节点在每个时段中都无需以后的需求信息做出不可撤销的决策。我们表明，这两种算法都具有从离线最佳的恒定性能界限。使用Google群集 - 使用轨迹获得的数值结果表明，通过使用建议的算法可以大大降低边缘节点的成本，与基线算法相比，最高$ 80 \％$。我们还观察到云的定价结构和边缘的本地成本如何影响采购决策。
By acquiring cloud-like capacities at the edge of a network, edge computing is expected to significantly improve user experience. In this paper, we formulate a hybrid edge-cloud computing system where an edge device with limited local resources can rent more from a cloud node and perform resource allocation to serve its users. The resource procurement and allocation decisions depend not only on the cloud's multiple rental options but also on the edge's local processing cost and capacity. We first propose an offline algorithm whose decisions are made with full information of future demand. Then, an online algorithm is proposed where the edge node makes irrevocable decisions in each timeslot without future information of demand. We show that both algorithms have constant performance bounds from the offline optimum. Numerical results acquired with Google cluster-usage traces indicate that the cost of the edge node can be substantially reduced by using the proposed algorithms, up to $80\%$ in comparison with baseline algorithms. We also observe how the cloud's pricing structure and edge's local cost influence the procurement decisions.
