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Task scheduling in deadline-aware mobile edge computing systems

  • Tongxin Zhu
  • , Tuo Shi
  • , Jianzhong Li*
  • , Zhipeng Cai
  • , Xun Zhou
  • *Corresponding author for this work
  • Harbin Institute of Technology
  • Georgia State University
  • University of Iowa

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number8486629
Pages (from-to)4854-4866
Number of pages13
JournalIEEE Internet of Things Journal
Volume6
Issue number3
DOIs
StatePublished - Jun 2019
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Edge computing
  • Schedules

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