Game-Based Resource Allocation and Task Offloading Scheme in Collaborative Cloud-Edge Computing System

Authors

Xuewen Wu, School of Computer and Information, Hohai University, Nanjing 211100, China;Follow
Jingxian Liao, School of Computer and Information, Hohai University, Nanjing 211100, China;

Abstract

Abstract: Considering the delay, energy consumption and computing resource cost, the utility maximization problem in collaborative cloud-edge system is constructed, and divided into three subproblems: computing resource allocation, uplink power allocation and task offloading strategy. A game-based resource allocation and task offloading(GRATO) scheme is proposed to solve those subproblems. The optimal solution of computing resource allocation is obtained by using convex optimization conditions; a low complexity uplink power allocation method is designed to reduce wireless interfere; a game-based distributed task offloading algorithm (GDTOA) is proposed to optimize the task offloading strategy. Simulation results show that the performance of GRATO is better than other schemes on delay and energy consumption, and it can sense the priority of users, resulting in higher utility and lower latency for emergency users..

Recommended Citation

Wu, Xuewen and Liao, Jingxian (2022) "Game-Based Resource Allocation and Task Offloading Scheme in Collaborative Cloud-Edge Computing System," Journal of System Simulation: Vol. 34: Iss. 7, Article 9.
DOI: 10.16182/j.issn1004731x.joss.21-0077
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss7/9

First Page

1468

Revised Date

2021-04-30

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-0077

Last Page

1481

CLC

TP301.6

Recommended Citation

Xuewen Wu, Jingxian Liao. Game-Based Resource Allocation and Task Offloading Scheme in Collaborative Cloud-Edge Computing System[J]. Journal of System Simulation, 2022, 34(7): 1468-1481.

DOI

10.16182/j.issn1004731x.joss.21-0077