Hierarchical Offloading for Delay-Constrained Applications in Fog RAN

Kun Guo, Min Sheng, Jianhua Tang, Tony Q.S. Quek, Zhiliang Qiu

Research output: Contribution to journalArticlepeer-review

Abstract

By computation offloading, fog radio access network (RAN) can support delay-constrained applications, since such a hierarchical network architecture enables parallel computing at local computing layer (LCL), edge computing layer (ECL), and cloud computing layer (CCL). Comparing to processing applications exclusively at the LCL, the assistance of processing at the ECL and the CCL can reduce computation latency, while introduce extra communication latency. These two latency are not only influenced by the hierarchical offloading decision but also by the available communication and computational resources at multiple computing layers. In this regard, this paper aims to jointly provision communication and computational resources for a powerful hierarchical offloading mechanism in fog RAN to complete delay-constrained applications with high-efficiency resource utilization. Specifically, we formulate a deadline-constrained energy minimization problem, which is followed by feasibility analysis, effective solution, and application extension. Through theoretical analyses and simulation results, we provide some insights on hierarchical offloading conditions and demonstrate advantages of our proposed algorithms in terms of the minimum affordable latency, total energy consumption, and scalability.

Original languageEnglish
Article number8988183
Pages (from-to)4257-4270
Number of pages14
JournalIEEE Transactions on Vehicular Technology
Volume69
Issue number4
DOIs
Publication statusPublished - 2020 Apr

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Applied Mathematics

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