In the Internet of Vehicles (IoV), with the increasing demand for intelligent technologies such as driverless driving, more and more in-vehicle applications have been put into autonomous driving. For the computationally intensive task, the vehicle self-organizing network uses other high-performance nodes in the vehicle driving environment to hand over tasks to these nodes for execution. In this way, the computational load of the cloud alleviated. However, due to the unreliability of the communication link and the dynamic changes of the vehicle environment, lengthy task completion time may lead to the increase of task failure rate. Although the flooding algorithm can improve the success rate of task completion, the offloading expend will be large. Aiming at this problem, we design the partial flooding algorithm, which is a comprehensive evaluation method based on system reliability in the vehicle computing environment without infrastructure. Using V2V link to select some nodes with better performance for partial flooding offloading to reduce the task complete time, improve system reliability and cut down the impact of vehicle mobility on offloading. The results show that the proposed offloading strategy can not only improve the utilization of computing resources, but also promote the offloading performance of the system.

中文翻译：

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基于可靠性和能力的车辆自组织云计算分流策略

在车联网（IoV）中，随着对无人驾驶等智能技术的需求不断增长，越来越多的车载应用已用于自动驾驶。对于计算密集型任务，车辆自组织网络使用车辆驾驶环境中的其他高性能节点将任务移交给这些节点以执行。这样，减轻了云计算的负担。然而，由于通信链路的不可靠性以及车辆环境的动态变化，漫长的任务完成时间可能导致任务失败率的增加。尽管泛洪算法可以提高任务完成的成功率，但分流开销却很大。针对这个问题，我们设计了部分泛洪算法，这是在没有基础设施的情况下基于车辆计算环境中系统可靠性的综合评估方法。使用V2V链接来选择一些性能更好的节点来进行部分洪流卸载，以减少任务完成时间，提高系统可靠性并减少车辆移动性对卸载的影响。结果表明，所提出的卸载策略不仅可以提高计算资源的利用率，而且可以提高系统的卸载性能。