Edge Intelligence for Multi-Dimensional Resource Management in Aerial-Assisted Vehicular Networks
Haixia Peng, Huaqing Wu, Xuemin Shen
Abstract
A new architecture with drone-assisted multi-access edge computing (MEC) is proposed for vehicular networks to support computation-intensive and delay-sensitive applications and services. Artificial intelligence (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. A case study on the joint management of the spectrum and computing resources is presented to demonstrate the effectiveness of AI-based resource management schemes.
Topics & Concepts
Computer scienceResource management (computing)Edge computingQuality of serviceDistributed computingResource allocationSpectrum managementDroneComputer networkEnhanced Data Rates for GSM EvolutionService (business)ServerResource (disambiguation)Artificial intelligenceTelecommunicationsWirelessCognitive radioGeneticsEconomyEconomicsBiologyUAV Applications and OptimizationAir Traffic Management and OptimizationVehicular Ad Hoc Networks (VANETs)