车辆边缘云的轨迹感知边缘节点聚类

Jaewook Lee, Haneul Ko, Sangheon Pack
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引用次数: 5

摘要

在车辆边缘云中,来自车辆的任务在附近的边缘节点(ENs)处理,从而可以提供低延迟的服务。然而,在车辆高度移动的情况下,两个网络之间的业务迁移频繁,切换延迟增加。在本文中,我们引入了一种轨迹感知边缘节点聚类(TENC)方案,其中多个边缘节点根据目标车辆的轨迹组成一个簇。为了获得最优的性能,我们利用约束马尔可夫决策过程(CMDP)构造了一个优化问题。评估结果表明,所得到的最优策略能显著地降低服务延迟。
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Trajectory-Aware Edge Node Clustering in Vehicular Edge Clouds
In vehicular edge clouds, tasks from vehicles are processed nearby edge nodes (ENs) and thus low latency services can be provided. However, under high vehicular mobility, frequent service migration between two ENs and increased handover latency can be observed. In this paper, we introduce a trajectory-aware edge node clustering (TENC) scheme in which multiple ENs form a cluster depending on the trajectory of a target vehicle. To attain the optimal performance, we formulate an optimization problem by means of a constrained Markov decision process (CMDP). Evaluation results demonstrate that the obtained optimal policy can minimize service delay significantly.
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