Computation offloading and resource allocation for mobile edge computing with multiple access points

Li，Qiuping1,2; Zhao，Junhui1,3; Gong，Yi2

2019-10-29

10.1049/iet-com.2019.0446

IET Communications   影响因子和分区

1751-8628

1751-8636

Mobile edge computing (MEC) is an innovative computing paradigm to enhance the computing capacity of mobile devices (MDs) by offloading computation-intensive tasks to MEC servers. With the widespread deployment of wireless local area networks, each MD can offload computation task to server via multiple wireless access points (WAPs). However, computation offloading can bring a higher system cost if all users select the same access points to offload their tasks. This study proposes a computation offloading strategy and resource allocation optimisation scheme in a multiple wireless access points network with MEC, which aims to minimise the system cost by providing the optimal computation offloading strategy, transmission power allocation, bandwidth assignment, and computation resource scheduling. The proposed scheme decouples the optimisation problem into subproblems of offloading strategy and resource allocation since the problem is NP-hard. The offloading strategy involves the optimal access point selection, which is analysed by the potential game. The resource allocation is obtained using Lagrange multiplier. The authors' analysis and simulation results verify the convergence performance of the proposed scheme, and the proposed scheme outperforms the simple resource allocation scheme and the offloading strategy optimisation scheme in terms of the system cost.

mobile computing wireless LAN resource allocation optimisation computational complexity distributed processing optimal access point selection simple resource allocation scheme offloading strategy optimisation scheme mobile edge computing multiple access points innovative computing paradigm mobile devices computation-intensive tasks MEC servers wireless local area networks resource allocation optimisation scheme multiple wireless access points network optimal computation offloading strategy transmission power allocation computation resource scheduling bandwidth assignment NP-hard problem Lagrange multiplier

SCI ; EI

英语

其他

Shenzhen Technology Development Program[JCYJ20170817110410346] ; 5511 Science and Technology Innovation Talent Project of Jiangxi Province[20172BCB22016] ; Natural Science Foundation of Beijing Municipality[L182018] ; Fundamental Research Funds for the Central Universities[2018YJS008] ; Jiangxi Provincial Department of Science and Technology[2016D0037] ; National Major Science and Technology Projects of China[2016ZX03001014-006] ; Southeast University[2017D14] ; National Natural Science Foundation of China[61661021]

Engineering

Engineering, Electrical & Electronic

WOS:000498019000005

Institution of Engineering and Technology

20194307577984

Edge computing ; Lagrange multipliers ; Optimization ; Resource allocation

Management:912.2 ; Optimization Techniques:921.5

2-s2.0-85073719633

Scopus

1.School of Electronic and Information EngineeringBeijing Jiaotong University,Beijing,100044,China
2.Shenzhen Engineering Laboratory of Intelligent Information Processing for IoTSouthern University of Science and Technology,Shenzhen,518055,China
3.School of Information EngineeringEast China Jiaotong University,Nanchang,330013,China

Li，Qiuping,Zhao，Junhui,Gong，Yi. Computation offloading and resource allocation for mobile edge computing with multiple access points[J]. IET Communications,2019,13(17):2668-2677.

Li，Qiuping,Zhao，Junhui,&Gong，Yi.(2019).Computation offloading and resource allocation for mobile edge computing with multiple access points.IET Communications,13(17),2668-2677.

Li，Qiuping,et al."Computation offloading and resource allocation for mobile edge computing with multiple access points".IET Communications 13.17(2019):2668-2677.