With the explosion in the number of connected devices and Internet of Things (IoT) services in smart city, the challenges to meet the demands from both data traffic delivery and information processing are increasingly prominent. Meanwhile, the connected vehicle networks have become an essential part in smart city, bringing massive data traffic as well as significant networking, caching and computing resources. In this paper, we propose a novel vehicle network architecture, mitigating the network congestion with the joint optimization of networking, caching and computing. Cloud computing at the data centers as well as mobile edge computing (MEC) at the evolved node Bs (eNodeBs) and on-board units (OBUs) are taken as the paradigms to provide caching and computing resources. The programmable control principle originated from software-defined networking (SDN) paradigm has been introduced to facilitate the system architecture and resource integration. With the careful modeling of the services, the vehicle mobility and the system state, a joint resource management scheme is proposed and formulated as a partially observable Markov decision process (POMDP) to minimize system cost, which consists of both network overhead and execution time of computing tasks. Extensive simulation results with different system parameters reveal that the proposed scheme could significantly improve the system performance compared to the existing schemes.

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2018 IEEE International Conference on Communications, ICC 2018
School of Information Technology

Li, M. (Meng), Yu, F.R, Si, P. (Pengbo), Yao, H. (Haipeng), & Zhang, Y. (Yanhua). (2018). Software-Defined Vehicular Networks with Caching and Computing for Delay-Tolerant Data Traffic. In IEEE International Conference on Communications. doi:10.1109/ICC.2018.8422823