Multi-objective resource allocation for mobile edge computing systems

Xinyi Zhang; Yuyi Mao; Jun Zhang; Khaled B. Letaief

doi:10.1109/PIMRC.2017.8292379

Multi-objective resource allocation for mobile edge computing systems

Xinyi Zhang
, Yuyi Mao
, Jun Zhang
, Khaled B. Letaief

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

23 Citations (Scopus)

Abstract

To enhance the computation capability of mobile devices by offloading computation-demanding tasks to the nearby edge servers. In order to minimize the task latency and the device energy consumption, in this paper, we investigate the multi-objective resource allocation for multi-user MEC systems by adopting the system utility as the performance metric, which is a normalized weighted combination of the time and energy saving achieved by computation offloading. To provide an efficient solution, a low-complexity ranking-based algorithm is proposed based on the modified Newton method and the concept of computation offloading priority. Simulation results show that our proposed algorithm achieves a near-optimal performance and greatly outperforms a baseline algorithm with random spectrum allocation. In addition, it is demonstrated that jointly optimizing the spectrum and computational resource management policy is more critical when the number of MEC users is large.

Original language	English
Title of host publication	2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications
Subtitle of host publication	Engaged Citizens and their New Smart Worlds, PIMRC 2017 - Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781538635315
DOIs	https://doi.org/10.1109/PIMRC.2017.8292379
Publication status	Published - 14 Feb 2018
Externally published	Yes
Event	28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2017 - Montreal, Canada Duration: 8 Oct 2017 → 13 Oct 2017

Publication series

Name	IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Volume	2017-October

Conference

Conference	28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2017
Country/Territory	Canada
City	Montreal
Period	8/10/17 → 13/10/17

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Computation offloading
Mobile edge computing
Modified Newton method
Multi-objective optimization

ASJC Scopus subject areas

Electrical and Electronic Engineering

More information

10.1109/PIMRC.2017.8292379

Cite this

Zhang, X., Mao, Y., Zhang, J., & Letaief, K. B. (2018). Multi-objective resource allocation for mobile edge computing systems. In 2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications: Engaged Citizens and their New Smart Worlds, PIMRC 2017 - Conference Proceedings (pp. 1-5). (IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC; Vol. 2017-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PIMRC.2017.8292379

Zhang, Xinyi ; Mao, Yuyi ; Zhang, Jun et al. / Multi-objective resource allocation for mobile edge computing systems. 2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications: Engaged Citizens and their New Smart Worlds, PIMRC 2017 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-5 (IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC).

@inproceedings{59d43eb0729f4346968cd9aeb01f50ef,

title = "Multi-objective resource allocation for mobile edge computing systems",

abstract = "To enhance the computation capability of mobile devices by offloading computation-demanding tasks to the nearby edge servers. In order to minimize the task latency and the device energy consumption, in this paper, we investigate the multi-objective resource allocation for multi-user MEC systems by adopting the system utility as the performance metric, which is a normalized weighted combination of the time and energy saving achieved by computation offloading. To provide an efficient solution, a low-complexity ranking-based algorithm is proposed based on the modified Newton method and the concept of computation offloading priority. Simulation results show that our proposed algorithm achieves a near-optimal performance and greatly outperforms a baseline algorithm with random spectrum allocation. In addition, it is demonstrated that jointly optimizing the spectrum and computational resource management policy is more critical when the number of MEC users is large.",

keywords = "Computation offloading, Mobile edge computing, Modified Newton method, Multi-objective optimization",

author = "Xinyi Zhang and Yuyi Mao and Jun Zhang and Letaief, \{Khaled B.\}",

year = "2018",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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Zhang, X, Mao, Y, Zhang, J & Letaief, KB 2018, Multi-objective resource allocation for mobile edge computing systems. in 2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications: Engaged Citizens and their New Smart Worlds, PIMRC 2017 - Conference Proceedings. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, vol. 2017-October, Institute of Electrical and Electronics Engineers Inc., pp. 1-5, 28th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2017, Montreal, Canada, 8/10/17. https://doi.org/10.1109/PIMRC.2017.8292379

Multi-objective resource allocation for mobile edge computing systems. / Zhang, Xinyi; Mao, Yuyi; Zhang, Jun et al.
2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications: Engaged Citizens and their New Smart Worlds, PIMRC 2017 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-5 (IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC; Vol. 2017-October).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Mao, Yuyi

AU - Zhang, Jun

AU - Letaief, Khaled B.

PY - 2018/2/14

Y1 - 2018/2/14

N2 - To enhance the computation capability of mobile devices by offloading computation-demanding tasks to the nearby edge servers. In order to minimize the task latency and the device energy consumption, in this paper, we investigate the multi-objective resource allocation for multi-user MEC systems by adopting the system utility as the performance metric, which is a normalized weighted combination of the time and energy saving achieved by computation offloading. To provide an efficient solution, a low-complexity ranking-based algorithm is proposed based on the modified Newton method and the concept of computation offloading priority. Simulation results show that our proposed algorithm achieves a near-optimal performance and greatly outperforms a baseline algorithm with random spectrum allocation. In addition, it is demonstrated that jointly optimizing the spectrum and computational resource management policy is more critical when the number of MEC users is large.

AB - To enhance the computation capability of mobile devices by offloading computation-demanding tasks to the nearby edge servers. In order to minimize the task latency and the device energy consumption, in this paper, we investigate the multi-objective resource allocation for multi-user MEC systems by adopting the system utility as the performance metric, which is a normalized weighted combination of the time and energy saving achieved by computation offloading. To provide an efficient solution, a low-complexity ranking-based algorithm is proposed based on the modified Newton method and the concept of computation offloading priority. Simulation results show that our proposed algorithm achieves a near-optimal performance and greatly outperforms a baseline algorithm with random spectrum allocation. In addition, it is demonstrated that jointly optimizing the spectrum and computational resource management policy is more critical when the number of MEC users is large.

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Zhang X, Mao Y, Zhang J, Letaief KB. Multi-objective resource allocation for mobile edge computing systems. In 2017 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications: Engaged Citizens and their New Smart Worlds, PIMRC 2017 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-5. (IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC). doi: 10.1109/PIMRC.2017.8292379

Multi-objective resource allocation for mobile edge computing systems

Abstract

Publication series

Conference

UN SDGs

Keywords

ASJC Scopus subject areas

More information

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