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Efficient resource allocation for relay-assisted computation offloading in mobile edge computing

Efficient resource allocation for relay-assisted computation offloading in mobile edge computing
Efficient resource allocation for relay-assisted computation offloading in mobile edge computing
In this article, relay-assisted computation offloading (RACO) is investigated, where user $A$ wishes to share the results of computational tasks with another user $B$ with the assistance of a mobile-edge relay server (MERS). To enable this computation offloading, we propose a hybrid relaying (HR) approach employing a pair of orthogonal frequency bands, which are, respectively, used for the amplify–forward relaying of computational results and the decode–forward relaying of the unprocessed raw tasks. The motivation here is to adapt the allocation of computing and communication resources both to dynamic user requirements and to diverse computational tasks. Using this framework, we seek to minimize the weighted sum of the execution delays and the energy consumption in the RACO system by jointly optimizing the computation offloading ratio, the bandwidth allocation, the processor speeds, as well as the transmit power levels of both user $A$ and the MERS, under some practical constraints. By adopting a series of transformations, we first recast this problem into a form amenable to optimization and then develop an efficient iterative algorithm for its solution based on the concave–convex procedure (CCCP). By virtue of the particular problem structure in our case, we propose furthermore a simplified algorithm based on the inexact block coordinate descent (IBCD) method, which leads us to much lower computational complexity. Finally, our numerical results demonstrate the advantages of the proposed algorithms over the state-of-the-art benchmark schemes.
Concave-convex procedure (CCCP), computation offloading, hybrid relaying (HR), inexact block coordinate descent (IBCD), mobile-edge computing (MEC), resource allocation
2542-6605
2452 - 2468
Chen, Xihan
da76284b-0832-4ad9-9620-d84fa8896b6e
Cai, Yunlong
44a85b9f-185b-4078-aecd-02df90f5eab6
Shi, Qingjiang
b7a4b79b-d00c-444e-90c7-7569e9d83a28
Zhao, Min-Jian
df090273-a8c8-4013-9b5b-02214f31bcc4
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
Shi, Qingjiang
b7a4b79b-d00c-444e-90c7-7569e9d83a28
Zhao, Min-Jian
df090273-a8c8-4013-9b5b-02214f31bcc4
Champagne, Benoit
34637814-cef4-4177-b5fd-d748742be072
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Chen, Xihan, Cai, Yunlong, Shi, Qingjiang, Zhao, Min-Jian, Champagne, Benoit and Hanzo, Lajos (2020) Efficient resource allocation for relay-assisted computation offloading in mobile edge computing. Internet of Things, 7 (3), 2452 - 2468, [8924727]. (doi:10.1109/JIOT.2019.2957728).

Record type: Article

Abstract

In this article, relay-assisted computation offloading (RACO) is investigated, where user $A$ wishes to share the results of computational tasks with another user $B$ with the assistance of a mobile-edge relay server (MERS). To enable this computation offloading, we propose a hybrid relaying (HR) approach employing a pair of orthogonal frequency bands, which are, respectively, used for the amplify–forward relaying of computational results and the decode–forward relaying of the unprocessed raw tasks. The motivation here is to adapt the allocation of computing and communication resources both to dynamic user requirements and to diverse computational tasks. Using this framework, we seek to minimize the weighted sum of the execution delays and the energy consumption in the RACO system by jointly optimizing the computation offloading ratio, the bandwidth allocation, the processor speeds, as well as the transmit power levels of both user $A$ and the MERS, under some practical constraints. By adopting a series of transformations, we first recast this problem into a form amenable to optimization and then develop an efficient iterative algorithm for its solution based on the concave–convex procedure (CCCP). By virtue of the particular problem structure in our case, we propose furthermore a simplified algorithm based on the inexact block coordinate descent (IBCD) method, which leads us to much lower computational complexity. Finally, our numerical results demonstrate the advantages of the proposed algorithms over the state-of-the-art benchmark schemes.

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Accepted/In Press date: 30 November 2019
e-pub ahead of print date: 5 December 2019
Published date: 1 March 2020
Keywords: Concave-convex procedure (CCCP), computation offloading, hybrid relaying (HR), inexact block coordinate descent (IBCD), mobile-edge computing (MEC), resource allocation

Identifiers

Local EPrints ID: 436373
URI: http://eprints.soton.ac.uk/id/eprint/436373
ISSN: 2542-6605
PURE UUID: 880240eb-7487-4448-a72d-2ae521ecc76b
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 09 Dec 2019 17:30
Last modified: 28 Apr 2022 01:34

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Contributors

Author: Xihan Chen
Author: Yunlong Cai
Author: Qingjiang Shi
Author: Min-Jian Zhao
Author: Benoit Champagne
Author: Lajos Hanzo ORCID iD

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