Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks

Chen Wang; Daosen Zhai; Ruonan Zhang; Georges Kaddoum; Satinder Singh

doi:10.1109/ICC45041.2023.10279245

Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks

Chen Wang
, Daosen Zhai
, Ruonan Zhang
, Georges Kaddoum
, Satinder Singh

School of Electronics and Information

Northwestern Polytechnical University Xian
Southeast University, Nanjing
École de technologie supérieure
Ultra Communications

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

3 Scopus citations

Abstract

Unmanned aerial vehicles (UAVs) combining with mobile edge computing (MEC) networks have promoted the application of Internet of Things (IoT) devices, providing enhanced coverage with flexible computing services. But the energy consumption of data processing is still a shortage in the UAV-assisted MEC architecture. Motivated by that, we propose a dynamic UAV-assisted MEC network and formulate a problem and jointly optimize association strategies, UAV trajectory, data offloading, and resource distribution for minimizing total energy consumption. To deal with this tricky problem, we devise a dichotomy-based joint iterative optimization algorithm. Specifically, we divide the problem into three sub-problems, solving by the integer programming, successive convex optimization, and dichotomy method. Finally, the simulation consequences prove that the devised network and algorithm significantly reduce total energy consuming.

Original language	English
Title of host publication	ICC 2023 - IEEE International Conference on Communications
Subtitle of host publication	Sustainable Communications for Renaissance
Editors	Michele Zorzi, Meixia Tao, Walid Saad
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4671-4676
Number of pages	6
ISBN (Electronic)	9781538674628
DOIs	https://doi.org/10.1109/ICC45041.2023.10279245
State	Published - 2023
Event	2023 IEEE International Conference on Communications, ICC 2023 - Rome, Italy Duration: 28 May 2023 → 1 Jun 2023

Publication series

Name	IEEE International Conference on Communications
Volume	2023-May
ISSN (Print)	1550-3607

Conference

Conference	2023 IEEE International Conference on Communications, ICC 2023
Country/Territory	Italy
City	Rome
Period	28/05/23 → 1/06/23

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

association strategies
joint optimization
MEC
offloading
resource allocation
UAV trajectory

Access to Document

10.1109/ICC45041.2023.10279245

Cite this

Wang, C., Zhai, D., Zhang, R., Kaddoum, G., & Singh, S. (2023). Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks. In M. Zorzi, M. Tao, & W. Saad (Eds.), ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance (pp. 4671-4676). (IEEE International Conference on Communications; Vol. 2023-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC45041.2023.10279245

Wang, Chen ; Zhai, Daosen ; Zhang, Ruonan et al. / Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks. ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance. editor / Michele Zorzi ; Meixia Tao ; Walid Saad. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 4671-4676 (IEEE International Conference on Communications).

@inproceedings{0920ee732ea3415ba3415a48e317fa43,

title = "Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks",

abstract = "Unmanned aerial vehicles (UAVs) combining with mobile edge computing (MEC) networks have promoted the application of Internet of Things (IoT) devices, providing enhanced coverage with flexible computing services. But the energy consumption of data processing is still a shortage in the UAV-assisted MEC architecture. Motivated by that, we propose a dynamic UAV-assisted MEC network and formulate a problem and jointly optimize association strategies, UAV trajectory, data offloading, and resource distribution for minimizing total energy consumption. To deal with this tricky problem, we devise a dichotomy-based joint iterative optimization algorithm. Specifically, we divide the problem into three sub-problems, solving by the integer programming, successive convex optimization, and dichotomy method. Finally, the simulation consequences prove that the devised network and algorithm significantly reduce total energy consuming.",

keywords = "association strategies, joint optimization, MEC, offloading, resource allocation, UAV trajectory",

author = "Chen Wang and Daosen Zhai and Ruonan Zhang and Georges Kaddoum and Satinder Singh",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Communications, ICC 2023 ; Conference date: 28-05-2023 Through 01-06-2023",

year = "2023",

doi = "10.1109/ICC45041.2023.10279245",

language = "英语",

series = "IEEE International Conference on Communications",

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

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editor = "Michele Zorzi and Meixia Tao and Walid Saad",

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Wang, C, Zhai, D , Zhang, R, Kaddoum, G & Singh, S 2023, Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks. in M Zorzi, M Tao & W Saad (eds), ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance. IEEE International Conference on Communications, vol. 2023-May, Institute of Electrical and Electronics Engineers Inc., pp. 4671-4676, 2023 IEEE International Conference on Communications, ICC 2023, Rome, Italy, 28/05/23. https://doi.org/10.1109/ICC45041.2023.10279245

Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks. / Wang, Chen; Zhai, Daosen ; Zhang, Ruonan et al.
ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance. ed. / Michele Zorzi; Meixia Tao; Walid Saad. Institute of Electrical and Electronics Engineers Inc., 2023. p. 4671-4676 (IEEE International Conference on Communications; Vol. 2023-May).

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

TY - GEN

T1 - Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks

AU - Wang, Chen

AU - Zhai, Daosen

AU - Zhang, Ruonan

AU - Kaddoum, Georges

AU - Singh, Satinder

PY - 2023

Y1 - 2023

N2 - Unmanned aerial vehicles (UAVs) combining with mobile edge computing (MEC) networks have promoted the application of Internet of Things (IoT) devices, providing enhanced coverage with flexible computing services. But the energy consumption of data processing is still a shortage in the UAV-assisted MEC architecture. Motivated by that, we propose a dynamic UAV-assisted MEC network and formulate a problem and jointly optimize association strategies, UAV trajectory, data offloading, and resource distribution for minimizing total energy consumption. To deal with this tricky problem, we devise a dichotomy-based joint iterative optimization algorithm. Specifically, we divide the problem into three sub-problems, solving by the integer programming, successive convex optimization, and dichotomy method. Finally, the simulation consequences prove that the devised network and algorithm significantly reduce total energy consuming.

AB - Unmanned aerial vehicles (UAVs) combining with mobile edge computing (MEC) networks have promoted the application of Internet of Things (IoT) devices, providing enhanced coverage with flexible computing services. But the energy consumption of data processing is still a shortage in the UAV-assisted MEC architecture. Motivated by that, we propose a dynamic UAV-assisted MEC network and formulate a problem and jointly optimize association strategies, UAV trajectory, data offloading, and resource distribution for minimizing total energy consumption. To deal with this tricky problem, we devise a dichotomy-based joint iterative optimization algorithm. Specifically, we divide the problem into three sub-problems, solving by the integer programming, successive convex optimization, and dichotomy method. Finally, the simulation consequences prove that the devised network and algorithm significantly reduce total energy consuming.

KW - association strategies

KW - joint optimization

KW - MEC

KW - offloading

KW - resource allocation

KW - UAV trajectory

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U2 - 10.1109/ICC45041.2023.10279245

DO - 10.1109/ICC45041.2023.10279245

M3 - 会议稿件

AN - SCOPUS:85178256424

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SP - 4671

EP - 4676

BT - ICC 2023 - IEEE International Conference on Communications

A2 - Zorzi, Michele

A2 - Tao, Meixia

A2 - Saad, Walid

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE International Conference on Communications, ICC 2023

Y2 - 28 May 2023 through 1 June 2023

ER -

Wang C, Zhai D , Zhang R, Kaddoum G, Singh S. Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks. In Zorzi M, Tao M, Saad W, editors, ICC 2023 - IEEE International Conference on Communications: Sustainable Communications for Renaissance. Institute of Electrical and Electronics Engineers Inc. 2023. p. 4671-4676. (IEEE International Conference on Communications). doi: 10.1109/ICC45041.2023.10279245

Energy Consumption Minimization in Dynamic UAV-assisted Mobile Edge Computing Networks

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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