计算机科学
车载自组网
云计算
供应
聚类分析
分布式计算
专用短程通信
智能交通系统
可靠性(半导体)
计算机网络
实时计算
无线自组网
无线
人工智能
工程类
操作系统
物理
土木工程
功率(物理)
电信
量子力学
作者
Penghan Yan,Glaucio H. S. Carvalho,Robson E. De Grande
标识
DOI:10.1145/3551660.3560915
摘要
Intelligent and networked vehicles cooperate to create a mobile Cloud through vehicular Fog computing (VFC). Such Clouds rely heavily on the underlying vehicular networks, so estimating communication resilience allows to address the problems caused by intermittent vehicle connectivity for data transfers. Individually estimating the communication stability of vehicles, nevertheless, undergoes incorrect predictions due to their particular mobility patterns. Therefore, we provide a region-oriented Fog management model based on the connectivity through vehicular heterogeneous network environment via V2X and C-V2X. A Fog management strategy dynamically monitors nearby vehicles to determine distinct regions in urban centres. The model enables a software-defined vehicular network (SDVN) controller to coordinate data flows. From the stochasticity of the environment, our model is based on Markov Decision Process (MDP), tracking the status of vehicle clusters and their potential for provisioning services. The model for vehicular clustering is supported by 5G and DSRC heterogeneous networks. Simulated analyses have shown the capability of our proposed model to estimate cluster reliability in real-time urban scenarios and support effective vehicular Fog management.
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