车载边缘计算中任务卸载和服务缓存的联合智能优化

doi:10.11959/j.issn.1000-436x.2021017

Abstract

Abstract:

Given the contradiction between limited network resources and massive user demands in Internet of vehicles, an intelligent vehicular edge computing network architecture was proposed to achieve the comprehensive cooperation and intelligent management of network resources.Based on this architecture, a joint optimization scheme of task offloading and service caching was furtherly devised, which formulated an optimization problem about how to offload tasks and allocate computation and cache resources.In view of the dynamics, randomness and time variation of vehicular networks, an asynchronous distributed reinforcement learning algorithm was employed to obtain the optimal task offloading and resource management policy.Simulation results demonstrate that the proposed algorithm achieves significant performance improvement in comparison with the other schemes.

Key words: Internet of vehicles, edge computing, computation offloading, service caching, intelligent optimization

CLC Number:

TN92

Lei LIU, Chen CHEN, Jie FENG, Qingqi PEI, Ci HE, Zhibin DOU. Joint intelligent optimization of task offloading and service caching for vehicular edge computing[J]. Journal on Communications, 2021, 42(1): 18-26.

Figures/Tables 7

References 24

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参数	分布
边缘服务器计算能力/（Gcycle·s^-1）	[2,6]
边缘服务器缓存能力/MB	200,1 000]
车辆数目/辆	25、35、45
车辆计算能力/（Mcycle·s^-1）	[100,500]
任务计算强度/（cycle·bit^-1）	297.62

Joint intelligent optimization of task offloading and service caching for vehicular edge computing

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