Revisiting computation partitioning in future 5G-based edge computing environments

Jin Cao, Lei Yang, Jiannong Cao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

9 Citations (Scopus)

Abstract

Edge computing recently attracts the industry and academic attentions due to its advantage of providing low latency services in a much closer place to the end users. This paper studies the problem of computation partitioning in future 5G-based edge computing environments. Although the problem has been studied a lot in (mobile) cloud computing, the problem in this paper is different with previous works. Traditional partitioning approaches in cloud computing aim to achieve an optimal tradeoff between the network transmission cost and the local computation cost, because the data transmission to cloud is very costly. However, in future 5G-based edge computing, the high bandwidth and low latency will overcome the data transmission challenge. Instead the constrained computation capability of the edge will greatly affect the performance of an partitioned execution of the application. As the challenge changes, we propose a new partitioning model, which parallelizes the computations and fully utilizes the computational resources on the edge and end devices. We develop an off-line solution for partitioning and scheduling the computation to the resources. We prove in theory that our off-line solution achieves the optimal performance. Based on the off-line solution, we further develop a set of online algorithms, and conduct extensive simulations to show that our proposed online algorithms significantly outperform the benchmark algorithms.

Original languageEnglish
Article number8462758
Pages (from-to)2427-2438
Number of pages12
JournalIEEE Internet of Things Journal
Volume6
Issue number2
DOIs
Publication statusPublished - Apr 2019

Keywords

  • Computation partitioning
  • edge computing
  • task dispatching
  • task scheduling

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems
  • Hardware and Architecture
  • Computer Science Applications
  • Computer Networks and Communications

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