Efficient Task Scheduling With Stochastic Delay Cost in Mobile Edge Computing

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

doi:10.1109/LCOMM.2018.2879317

Efficient Task Scheduling With Stochastic Delay Cost in Mobile Edge Computing

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

School of Information Science

Research output: Contribution to journal › Article › peer-review

32 Scopus citations

Abstract

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 language	English
Article number	8523681
Pages (from-to)	4-7
Number of pages	4
Journal	IEEE Communications Letters
Volume	23
Issue number	1
DOIs	https://doi.org/10.1109/LCOMM.2018.2879317
State	Published - Jan 2019

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

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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10.1109/LCOMM.2018.2879317

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abstract = "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.",

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AB - 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.

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KW - scheduling

KW - stochastic delay

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Efficient Task Scheduling With Stochastic Delay Cost in Mobile Edge Computing

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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