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|Title:||Resource management in space-air-ground integrated vehicular networks: SDN contorl and AI algorithm design||Author(s):||Xu, Wenchao||Author(s):||Wu, H.
Shen, X. S.
|Issue Date:||2020||Publisher:||IEEE||Journal:||IEEE Wireless Communications||Volume:||27||Issue:||6||Start page:||52||End page:||60||Abstract:||
With its potential versatility and reliability, the space-air-ground integrated vehicular network (SAGVN) is envisioned as a promising solution to deliver quality vehicular services anywhere at any time. This article proposes a software defined framework for SAGVN to achieve flexible, reliable, and scalable network resource management. First, key applications and research challenges in resource management are identified. Then we propose a hybrid and hierarchical SAGVN control architecture to balance the trade-off between system status acquisition and signaling overhead in different scenarios. Considering the dynamic networking environment with multi-dimensional resources and diverse services, it is challenging to make optimal resource management decisions in real time; thus, artificial intelligence (AI)-based engineering solutions are investigated to facilitate efficient network slicing, mobility management, and cooperative content caching and delivery. A trace-driven case study is presented to demonstrate the effectiveness of the proposed SAGVN framework with AI-based methods in increasing the SAGVN throughput performance.
|URI:||https://repository.cihe.edu.hk/jspui/handle/cihe/705||DOI:||10.1109/MWC.001.2000130||CIHE Affiliated Publication:||Yes|
|Appears in Collections:||CIS Publication|
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