Task scheduling in deadline-aware mobile edge computing systems

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

143 Scopus Citations
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Author(s)

  • Tongxin Zhu
  • Tuo Shi
  • Jianzhong Li
  • Zhipeng Cai
  • Xun Zhou

Detail(s)

Original languageEnglish
Pages (from-to)4854-4866
Number of pages13
Journal / PublicationIEEE Internet of Things Journal
Volume6
Issue number3
Online published9 Oct 2018
Publication statusPublished - Jun 2019
Externally publishedYes

Abstract

Mobile edge computing (MEC) is a new computing approach in which computation tasks carried by mobile devices (MDs) can be offloaded to MEC servers or computed locally. Since the MDs are always battery limited and computation tasks have strict deadlines, how to schedule the execution of each task energy effectively is important. Comparing with existing works, we consider a much more complexed scenario, in which multiple moving MDs sharing multiple heterogeneous MEC servers, and a problem named as minimum energy consumption problem in deadline-aware MEC system is formulated. Such problem is proved to be NP-hard, and two approximation algorithms are proposed focusing on single and multiple MD scenarios, respectively. The performances of these algorithms are varied by theoretical analysis and simulations. © 2018 IEEE.

Research Area(s)

  • Edge computing, schedules

Citation Format(s)

Task scheduling in deadline-aware mobile edge computing systems. / Zhu, Tongxin; Shi, Tuo; Li, Jianzhong et al.
In: IEEE Internet of Things Journal, Vol. 6, No. 3, 06.2019, p. 4854-4866.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review