Fast on-demand 5G connectivity can be deployed through the usage of aerial platforms. Indeed, the usage of moving nodes represents at the moment the most interesting and cost-affordable way to bring connectivity and network services in emergency scenarios or in the absence of the network infrastructure. This article presents an architecture for using drones as movable base stations, interconnected with a high altitude platform, capable of deploying multi-access edge computing following current ETSI standards. Moreover, a reinforcement learning algorithm is proposed to enable proper resource allocation in order to guarantee QoS requirements.

Design of an On-Demand Agile 5G Multi-Access Edge Computing Platform Using Aerial Vehicles

Costa, Cristina;
2020

Abstract

Fast on-demand 5G connectivity can be deployed through the usage of aerial platforms. Indeed, the usage of moving nodes represents at the moment the most interesting and cost-affordable way to bring connectivity and network services in emergency scenarios or in the absence of the network infrastructure. This article presents an architecture for using drones as movable base stations, interconnected with a high altitude platform, capable of deploying multi-access edge computing following current ETSI standards. Moreover, a reinforcement learning algorithm is proposed to enable proper resource allocation in order to guarantee QoS requirements.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/324970
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