Power-delay tradeoff in multi-user mobile-edge computing systems

Yuyi Mao, Jun Zhang, S. H. Song, Khaled Letaief

Research output: Chapter in Book/Report/Conference proceedingConference contribution

81 Citations (Scopus)

Abstract

Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we investigate the tradeoff between two critical but conflicting objectives in multi-user MEC systems, namely, the power consumption of mobile devices and the execution delay of computation tasks. A power consumption minimization problem with task buffer stability constraints is formulated to investigate the tradeoff, and an online algorithm that decides the local execution and computation offloading policy is developed based on Lyapunov optimization. Specifically, at each time slot, the optimal frequencies of the local CPUs are obtained in closed forms, while the optimal transmit power and bandwidth allocation for computation offloading are determined with the Gauss-Seidel method. Performance analysis is conducted for the proposed algorithm, which indicates that the power consumption and execution delay obeys an [O(1/V),O(V)] tradeoff with V as a control parameter. Simulation results are provided to validate the theoretical analysis and demonstrate the impacts of various parameters to the system performance.

Original languageEnglish
Title of host publication2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509013289
DOIs
Publication statusPublished - 2 Feb 2017
Externally publishedYes
Event59th IEEE Global Communications Conference, GLOBECOM 2016 - Washington, United States
Duration: 4 Dec 20168 Dec 2016

Other

Other59th IEEE Global Communications Conference, GLOBECOM 2016
CountryUnited States
CityWashington
Period4/12/168/12/16

Fingerprint

Electric power utilization
Mobile devices
Frequency allocation
Program processors

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality

Cite this

Mao, Y., Zhang, J., Song, S. H., & Letaief, K. (2017). Power-delay tradeoff in multi-user mobile-edge computing systems. In 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings [7842160] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GLOCOM.2016.7842160

Power-delay tradeoff in multi-user mobile-edge computing systems. / Mao, Yuyi; Zhang, Jun; Song, S. H.; Letaief, Khaled.

2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. 7842160.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Mao, Y, Zhang, J, Song, SH & Letaief, K 2017, Power-delay tradeoff in multi-user mobile-edge computing systems. in 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings., 7842160, Institute of Electrical and Electronics Engineers Inc., 59th IEEE Global Communications Conference, GLOBECOM 2016, Washington, United States, 4/12/16. https://doi.org/10.1109/GLOCOM.2016.7842160
Mao Y, Zhang J, Song SH, Letaief K. Power-delay tradeoff in multi-user mobile-edge computing systems. In 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2017. 7842160 https://doi.org/10.1109/GLOCOM.2016.7842160
Mao, Yuyi ; Zhang, Jun ; Song, S. H. ; Letaief, Khaled. / Power-delay tradeoff in multi-user mobile-edge computing systems. 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017.
@inproceedings{830e1c7a704f48b789456bac6316c0cb,
title = "Power-delay tradeoff in multi-user mobile-edge computing systems",
abstract = "Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we investigate the tradeoff between two critical but conflicting objectives in multi-user MEC systems, namely, the power consumption of mobile devices and the execution delay of computation tasks. A power consumption minimization problem with task buffer stability constraints is formulated to investigate the tradeoff, and an online algorithm that decides the local execution and computation offloading policy is developed based on Lyapunov optimization. Specifically, at each time slot, the optimal frequencies of the local CPUs are obtained in closed forms, while the optimal transmit power and bandwidth allocation for computation offloading are determined with the Gauss-Seidel method. Performance analysis is conducted for the proposed algorithm, which indicates that the power consumption and execution delay obeys an [O(1/V),O(V)] tradeoff with V as a control parameter. Simulation results are provided to validate the theoretical analysis and demonstrate the impacts of various parameters to the system performance.",
author = "Yuyi Mao and Jun Zhang and Song, {S. H.} and Khaled Letaief",
year = "2017",
month = "2",
day = "2",
doi = "10.1109/GLOCOM.2016.7842160",
language = "English",
booktitle = "2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Power-delay tradeoff in multi-user mobile-edge computing systems

AU - Mao, Yuyi

AU - Zhang, Jun

AU - Song, S. H.

AU - Letaief, Khaled

PY - 2017/2/2

Y1 - 2017/2/2

N2 - Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we investigate the tradeoff between two critical but conflicting objectives in multi-user MEC systems, namely, the power consumption of mobile devices and the execution delay of computation tasks. A power consumption minimization problem with task buffer stability constraints is formulated to investigate the tradeoff, and an online algorithm that decides the local execution and computation offloading policy is developed based on Lyapunov optimization. Specifically, at each time slot, the optimal frequencies of the local CPUs are obtained in closed forms, while the optimal transmit power and bandwidth allocation for computation offloading are determined with the Gauss-Seidel method. Performance analysis is conducted for the proposed algorithm, which indicates that the power consumption and execution delay obeys an [O(1/V),O(V)] tradeoff with V as a control parameter. Simulation results are provided to validate the theoretical analysis and demonstrate the impacts of various parameters to the system performance.

AB - Mobile-edge computing (MEC) has recently emerged as a promising paradigm to liberate mobile devices from increasingly intensive computation workloads, as well as to improve the quality of computation experience. In this paper, we investigate the tradeoff between two critical but conflicting objectives in multi-user MEC systems, namely, the power consumption of mobile devices and the execution delay of computation tasks. A power consumption minimization problem with task buffer stability constraints is formulated to investigate the tradeoff, and an online algorithm that decides the local execution and computation offloading policy is developed based on Lyapunov optimization. Specifically, at each time slot, the optimal frequencies of the local CPUs are obtained in closed forms, while the optimal transmit power and bandwidth allocation for computation offloading are determined with the Gauss-Seidel method. Performance analysis is conducted for the proposed algorithm, which indicates that the power consumption and execution delay obeys an [O(1/V),O(V)] tradeoff with V as a control parameter. Simulation results are provided to validate the theoretical analysis and demonstrate the impacts of various parameters to the system performance.

UR - http://www.scopus.com/inward/record.url?scp=85015451847&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85015451847&partnerID=8YFLogxK

U2 - 10.1109/GLOCOM.2016.7842160

DO - 10.1109/GLOCOM.2016.7842160

M3 - Conference contribution

AN - SCOPUS:85015451847

BT - 2016 IEEE Global Communications Conference, GLOBECOM 2016 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -