Digital Communications and Networking Commons^™

Incentivization In Mobile Edge Computing Using A Full Bayesian Approach, Sean Lebien

Electrical and Computer Engineering ETDs

The advances of multi-access edge computing (MEC) have paved the way for the integration of the MEC servers, as intelligent entities into the Internet of Things (IoT) environment as well as into the 5G radio access networks. In this thesis, a novel artificial intelligence-based MEC servers’ activation mechanism is proposed, by adopting the principles of Reinforcement Learning (RL) and Bayesian Reasoning. The considered problem enables the MEC servers’ activation decision-making, aiming at enhancing the reputation of the overall MEC system, as well as considering the total computing costs to serve efficiently the users’ computing demands, guaranteeing at the same time …