Online resource procurement and allocation in a hybrid edge-cloud computing system

Thinh Quang Dinh, Ben Liang, Tony Q.S. Quek, Hyundong Shin

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Article number8950272
Pages (from-to)2137-2149
Number of pages13
JournalIEEE Transactions on Wireless Communications
Volume19
Issue number3
DOIs
Publication statusPublished - 2020 Mar

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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