Joint Resource Allocation and Load Management for Cooling-Aware Mobile-Edge Computing

Xiaojing Chen; Zhouyu Lu; Wei Ni; Xin Wang; Shunqing Zhang; Shugong Xu

doi:10.1109/ICC40277.2020.9148795

Joint Resource Allocation and Load Management for Cooling-Aware Mobile-Edge Computing

Xiaojing Chen
, Zhouyu Lu
, Wei Ni
, Xin Wang
, Shunqing Zhang
, Shugong Xu

Shanghai University
Fudan University

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

2 Citations (Scopus)

Abstract

In this paper, we jointly design resource allocation and load management in a mobile-edge computing (MEC) system with wireless power transfer (WPT), to minimize the total energy consumption of the BS, while meeting computation latency requirements. For the first time, the cooling energy, which is non-negligible, is considered to minimize the energy consumption of the MEC system. By orchestrating the alternative optimization technique, Lagrange duality method and subgradient method, we decompose the original optimization problem and obtain the optimal solution in a semi-closed form. Extensive numerical tests corroborate the merits of the proposed algorithm over existing benchmarks in terms of energy saving.

Original language	English
Title of host publication	2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728150895
DOIs	https://doi.org/10.1109/ICC40277.2020.9148795
Publication status	Published - Jun 2020
Externally published	Yes
Event	2020 IEEE International Conference on Communications, ICC 2020 - Dublin, Ireland Duration: 7 Jun 2020 → 11 Jun 2020

Publication series

Name	IEEE International Conference on Communications
Volume	2020-June
ISSN (Print)	1550-3607

Conference

Conference	2020 IEEE International Conference on Communications, ICC 2020
Country/Territory	Ireland
City	Dublin
Period	7/06/20 → 11/06/20

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

computation offloading
cooling energy
Mobile edge computing (MEC)
wireless power transfer (WPT)

Access to Document

10.1109/ICC40277.2020.9148795

Cite this

Chen, X., Lu, Z., Ni, W., Wang, X., Zhang, S., & Xu, S. (2020). Joint Resource Allocation and Load Management for Cooling-Aware Mobile-Edge Computing. In 2020 IEEE International Conference on Communications, ICC 2020 - Proceedings Article 9148795 (IEEE International Conference on Communications; Vol. 2020-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC40277.2020.9148795

@inproceedings{35e26e9d0aff41e4a22d2333808f5904,

title = "Joint Resource Allocation and Load Management for Cooling-Aware Mobile-Edge Computing",

abstract = "In this paper, we jointly design resource allocation and load management in a mobile-edge computing (MEC) system with wireless power transfer (WPT), to minimize the total energy consumption of the BS, while meeting computation latency requirements. For the first time, the cooling energy, which is non-negligible, is considered to minimize the energy consumption of the MEC system. By orchestrating the alternative optimization technique, Lagrange duality method and subgradient method, we decompose the original optimization problem and obtain the optimal solution in a semi-closed form. Extensive numerical tests corroborate the merits of the proposed algorithm over existing benchmarks in terms of energy saving.",

keywords = "computation offloading, cooling energy, Mobile edge computing (MEC), wireless power transfer (WPT)",

author = "Xiaojing Chen and Zhouyu Lu and Wei Ni and Xin Wang and Shunqing Zhang and Shugong Xu",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Conference on Communications, ICC 2020 ; Conference date: 07-06-2020 Through 11-06-2020",

year = "2020",

month = jun,

doi = "10.1109/ICC40277.2020.9148795",

language = "English",

series = "IEEE International Conference on Communications",

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

booktitle = "2020 IEEE International Conference on Communications, ICC 2020 - Proceedings",

}

Chen, X, Lu, Z, Ni, W, Wang, X, Zhang, S & Xu, S 2020, Joint Resource Allocation and Load Management for Cooling-Aware Mobile-Edge Computing. in 2020 IEEE International Conference on Communications, ICC 2020 - Proceedings., 9148795, IEEE International Conference on Communications, vol. 2020-June, Institute of Electrical and Electronics Engineers Inc., 2020 IEEE International Conference on Communications, ICC 2020, Dublin, Ireland, 7/06/20. https://doi.org/10.1109/ICC40277.2020.9148795

Joint Resource Allocation and Load Management for Cooling-Aware Mobile-Edge Computing. / Chen, Xiaojing; Lu, Zhouyu; Ni, Wei et al.
2020 IEEE International Conference on Communications, ICC 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 9148795 (IEEE International Conference on Communications; Vol. 2020-June).

Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

TY - GEN

T1 - Joint Resource Allocation and Load Management for Cooling-Aware Mobile-Edge Computing

AU - Chen, Xiaojing

AU - Lu, Zhouyu

AU - Ni, Wei

AU - Wang, Xin

AU - Zhang, Shunqing

AU - Xu, Shugong

PY - 2020/6

Y1 - 2020/6

N2 - In this paper, we jointly design resource allocation and load management in a mobile-edge computing (MEC) system with wireless power transfer (WPT), to minimize the total energy consumption of the BS, while meeting computation latency requirements. For the first time, the cooling energy, which is non-negligible, is considered to minimize the energy consumption of the MEC system. By orchestrating the alternative optimization technique, Lagrange duality method and subgradient method, we decompose the original optimization problem and obtain the optimal solution in a semi-closed form. Extensive numerical tests corroborate the merits of the proposed algorithm over existing benchmarks in terms of energy saving.

AB - In this paper, we jointly design resource allocation and load management in a mobile-edge computing (MEC) system with wireless power transfer (WPT), to minimize the total energy consumption of the BS, while meeting computation latency requirements. For the first time, the cooling energy, which is non-negligible, is considered to minimize the energy consumption of the MEC system. By orchestrating the alternative optimization technique, Lagrange duality method and subgradient method, we decompose the original optimization problem and obtain the optimal solution in a semi-closed form. Extensive numerical tests corroborate the merits of the proposed algorithm over existing benchmarks in terms of energy saving.

KW - computation offloading

KW - cooling energy

KW - Mobile edge computing (MEC)

KW - wireless power transfer (WPT)

UR - https://www.scopus.com/pages/publications/85089421573

U2 - 10.1109/ICC40277.2020.9148795

DO - 10.1109/ICC40277.2020.9148795

M3 - Conference Proceeding

AN - SCOPUS:85089421573

T3 - IEEE International Conference on Communications

BT - 2020 IEEE International Conference on Communications, ICC 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Conference on Communications, ICC 2020

Y2 - 7 June 2020 through 11 June 2020

ER -

Joint Resource Allocation and Load Management for Cooling-Aware Mobile-Edge Computing

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this