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Energy-efficient resource allocation for latency-sensitive mobile edge computing

Energy-efficient resource allocation for latency-sensitive mobile edge computing
Energy-efficient resource allocation for latency-sensitive mobile edge computing
Resource allocation algorithms are conceived for minimizing the energy consumption of multiuser mobile edge computing (MEC) systems operating in the face of interference channels, and where mobile users can offload their latency-sensitive tasks to the mobile edge server via a base station (BS). Latency-sensitive applications that benefit from MEC services can be divided into two major classes: 1) applications requiring uninterrupted execution and that cannot be fragmented and therefore require full offloading (FO); 2) applications which can benefit from fractional or partial offloading (PO). For each class of applications, we first formulate a joint optimization problem where the aim is to minimize the overall energy consumption across the sub-network subject to latency, transmission quality, computational budget and transmit power constraints. The proposed optimization problems are nonconvex, tightly coupled, and consequently challenging to solve. By exploiting binary relaxation, smooth approximation and auxiliary variables, we convert these problems into more tractable forms and subsequently develop novel algorithms based on the concave-convex procedure (CCCP) to solve them. Furthermore, by incorporating a measure of user priority, a reduced-complexity solution is proposed for the FO scheme. The benefits of our energy-efficient resource allocation algorithms for latency-sensitive MEC are demonstrated through simulations.
CCCP, Mobile edge computing, full offloading scheme, partial offloading scheme, resource allocation
0018-9545
2246-2262
Chen, Xihan
da76284b-0832-4ad9-9620-d84fa8896b6e
Cai, Yunlong
44a85b9f-185b-4078-aecd-02df90f5eab6
Li, Liyan
b4539af6-41df-446a-b0f0-8e1739901c4d
Zhao, Minjian
d552c3c1-57fd-4643-b914-4572ef291edf
Champagne, Benoit
34637814-cef4-4177-b5fd-d748742be072
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Chen, Xihan
da76284b-0832-4ad9-9620-d84fa8896b6e
Cai, Yunlong
44a85b9f-185b-4078-aecd-02df90f5eab6
Li, Liyan
b4539af6-41df-446a-b0f0-8e1739901c4d
Zhao, Minjian
d552c3c1-57fd-4643-b914-4572ef291edf
Champagne, Benoit
34637814-cef4-4177-b5fd-d748742be072
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Chen, Xihan, Cai, Yunlong, Li, Liyan, Zhao, Minjian, Champagne, Benoit and Hanzo, Lajos (2020) Energy-efficient resource allocation for latency-sensitive mobile edge computing. IEEE Transactions on Vehicular Technology, 69 (2), 2246-2262, [8944163]. (doi:10.1109/TVT.2019.2962542).

Record type: Article

Abstract

Resource allocation algorithms are conceived for minimizing the energy consumption of multiuser mobile edge computing (MEC) systems operating in the face of interference channels, and where mobile users can offload their latency-sensitive tasks to the mobile edge server via a base station (BS). Latency-sensitive applications that benefit from MEC services can be divided into two major classes: 1) applications requiring uninterrupted execution and that cannot be fragmented and therefore require full offloading (FO); 2) applications which can benefit from fractional or partial offloading (PO). For each class of applications, we first formulate a joint optimization problem where the aim is to minimize the overall energy consumption across the sub-network subject to latency, transmission quality, computational budget and transmit power constraints. The proposed optimization problems are nonconvex, tightly coupled, and consequently challenging to solve. By exploiting binary relaxation, smooth approximation and auxiliary variables, we convert these problems into more tractable forms and subsequently develop novel algorithms based on the concave-convex procedure (CCCP) to solve them. Furthermore, by incorporating a measure of user priority, a reduced-complexity solution is proposed for the FO scheme. The benefits of our energy-efficient resource allocation algorithms for latency-sensitive MEC are demonstrated through simulations.

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More information

Accepted/In Press date: 23 December 2019
e-pub ahead of print date: 27 December 2019
Published date: February 2020
Keywords: CCCP, Mobile edge computing, full offloading scheme, partial offloading scheme, resource allocation

Identifiers

Local EPrints ID: 436820
URI: http://eprints.soton.ac.uk/id/eprint/436820
ISSN: 0018-9545
PURE UUID: afa91250-ef02-4258-a126-c813cca47452
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

Catalogue record

Date deposited: 10 Jan 2020 17:31
Last modified: 28 Apr 2022 01:34

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Contributors

Author: Xihan Chen
Author: Yunlong Cai
Author: Liyan Li
Author: Minjian Zhao
Author: Benoit Champagne
Author: Lajos Hanzo ORCID iD

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