In this chapter, an MVNET architecture is proposed to support vehicular applications. Most AV applications are usually with stringent delays and intensive computing requirements, which can be regarded as typical emerging vehicular applications. Thus, in this chapter, designing the MVNET architecture is mainly motivated from the AVs’ perspectives yet can be easily extended to general vehicular networks. Improving navigation safety by enabling HD-map-assisted cooperative driving among AVs is of great importance to the market perspective of AVs but confronts technical challenges due to increased communication, computing, and caching tasks generated by AVs for supporting different applications. To address these challenges, an MEC-assisted ADVNET architecture is proposed in this chapter. Specifically, an MEC-assisted ADVNET architecture that incorporates both SDN and NFV technologies is proposed in Sect. 2.1, in which a joint multi-resource management scheme is presented and some future research issues are discussed. Then, we take the intelligent resource allocation in an aerial-assisted vehicular network as a case study in Sect. 2.3. In this section, AI-based resource management schemes are developed such that terrestrial and aerial spectrum, computing, and storage resources can be cooperatively allocated for guaranteeing the quality of service requirements from different applications. Also, the joint management of the spectrum and computing resources is presented to demonstrate the effectiveness of the AI-based resource management schemes. Finally, we draw concluding remarks in Sect. 2.4.
MEC-Assisted Vehicular Networking
Wireless Networks
2012-02-24
24 pages
Article/Chapter (Book)
Electronic Resource
English
Multi-access edge computing , Autonomous vehicles , Software defined networking , Network function virtualization , Aerial-assisted vehicular network , Artificial intelligence , Resource management Engineering , Cyber-physical systems, IoT , Communications Engineering, Networks , Transportation Technology and Traffic Engineering , Computer Science
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