Efficient Task Scheduling With Stochastic Delay Cost in Mobile Edge Computing

Wenyu Zhang, Zhenjiang Zhang, Sherali Zeadally, Han Chieh Chao

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


We propose a new efficient and effective task scheduling approach with stochastic time cost for computation offloading in mobile edge computing. We developed an optimization model that minimizes the maximum tolerable delay (MTD) by considering both the average delay and delay jitter. We also proposed an efficient conservative heterogeneous earliest-finish-time algorithm to solve the MTD-minimization problem. Numerical results obtained with our proposed approach demonstrate its effectiveness over previously proposed techniques.

Original languageEnglish
Article number8523681
Pages (from-to)4-7
Number of pages4
JournalIEEE Communications Letters
Issue number1
StatePublished - Jan 2019

Bibliographical note

Funding Information:
Manuscript received October 11, 2018; revised October 25, 2018; accepted October 29, 2018. Date of publication November 5, 2018; date of current version January 8, 2019. This work is supported by National Natural Science Foundation of China under grant 61772064, and Academic Discipline, Post-Graduate Education Project of the Beijing Municipal Commission of Education, and Fundamental Research Funds for the Central Universities under grant 2017YJS026. The associate editor coordinating the review of this paper and approving it for publication was J. Ben Othman. (Corresponding author: Zhenjiang Zhang.) W. Zhang and Z. Zhang are with the Key Laboratory of Communication and Information Systems, Beijing Municipal Commission of Education, School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China (e-mail: zhangzhenjiang@bjtu.edu.cn).

Publisher Copyright:
© 2018 IEEE.

Copyright 2019 Elsevier B.V., All rights reserved.


  • Call graph
  • delay jitter
  • mobile edge computing
  • scheduling
  • stochastic delay

ASJC Scopus subject areas

  • Modeling and Simulation
  • Computer Science Applications
  • Electrical and Electronic Engineering


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