Cooperative vehicles-assisted task offloading in vehicular networks
Cooperative vehicles-assisted task offloading in vehicular networks
复制标题
车辆网络中的协作车辆辅助任务卸载
DOI：
10.1002/ett.4472
复制
发表时间：
2022-02-22
影响因子：
3.6
通讯作者：
Wang, Ruyan
中科院分区：
文献类型：
--
作者：
Cui, Yaping;Du, Lijuan;Wang, Ruyan
协同任务卸载是对计算能力敏感的移动的应用的一个很好的范例，而车载网络的动态和实时特性使得保证车载计算卸载的低延迟要求具有挑战性。现有的研究由于基础设施建设的稀疏部署和边缘服务器计算资源的有限性而不能满足实时计算的要求。受此启发，我们考虑了分布式车辆到车辆任务卸载的思想，它使车辆作为协作节点来执行任务。在本文中，我们利用并行计算的多车辆合作，提供低延迟的计算服务，而不超过能源约束。在此基础上，提出了一种基于双深度Q网络的协作车辆辅助任务卸载策略，在选择协作车辆后获得最优的任务卸载率。仿真结果表明，该策略可以有效地降低系统总时延。例如，与本地执行策略相比，所提出的策略的总系统延迟平均可以减少69.4%。
Cooperative task offloading emerges a well-received paradigm for mobile applications that are sensitive to computational power, while dynamic and real-time characteristics of vehicular networks makes it challenging to guarantee the low delay requirements of vehicular computation offloading. Existing researches cannot satisfy the real-time computation requests due to the sparse deployment of infrastructure constructions and constrained computing resources of edge servers. Motivated by these, we consider the idea of distributed vehicle-to-vehicle task offloading, which makes vehicles act as cooperative nodes to execute tasks. In this paper, we utilize parallel computing of multi-vehicle cooperation, to provide low-delay computation services without exceeding the energy constraint. Furthermore, a cooperative vehicles assisted task offloading strategy based on double deep Q-network is proposed to obtain the optimal task offloading ratio after selecting cooperative vehicles. Simulation results indicate that our proposed strategy can effectively decrease the total system delay. For example, compared with the local execution strategy, the total system delay of the proposed strategy can be reduced by 69.4% on average.