海报:车辆网络中基于多排架构的动态任务调度

Tingting Xiao, Chen Chen, Qingqi Pei, Shaohua Wan
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引用次数: 0

摘要

自动驾驶车辆排有潜力应对资源受限车辆对处理能力的需求以及MEC-BS的分散部署所带来的压力。在这张海报中,我们关注任务调度的多排场景。我们的目标是最小化受长期延迟约束的总体能耗。为了刻画随机特性和处理变量间的耦合,提出了一种基于李雅普诺夫优化(Lyapunov optimization, LDTS)的动态任务调度算法。我们从理论上和经验上评估了所提出算法的性能,结果表明,在执行延迟和能耗方面,该算法明显优于最先进的和其他基准方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Poster: A Dynamic Task Scheduling using Multi-Platoon Architecture in Vehicular Networks
The autonomous vehicle platoon has the potential to cope with the stress caused by the resource-constrained vehicles‘ demand for processing power and the spread-out deployment of MEC-BS. In this poster, we focus on a multi-platoons scenario for task scheduling. Our objective is to minimize the overall energy consumption subject to the long-term latency constraint. To characterize stochastic properties and deal with coupling between variables, we propose a dynamic task scheduling algorithm based on Lyapunov optimization (LDTS). We theoretically and empirically evaluate the performance of the proposed algorithm, which is illustrated to be significantly better than state-of-the-art and other benchmark approaches in terms of execution latency and energy consumption.
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