Multi-Access Edge Computing (MEC) is an extension of cloud computing that aims to provide computation, storage, and networking capabilities at the edge network in close proximity end-users. The MEC architecture supports applications services bridge between includes devices systems are interconnected, layered, flexibly deployed. As a result technological advancements, facing myriad highly sophis...

Multi-access edge computing (MEC) is capable of meeting the challenging requirements next-generation networks, e.g., 6G, as a benefit providing and caching capabilities in close proximity users. However, traditional MEC architecture relies on specialized hardware its bespoke software functions are closely integrated with hardware, hence it too rigid for supporting rapidly evolving scenarios fac...

This letter considers a multi-access mobile edge computing (MEC) network consisting of multiple users, base stations, and malicious eavesdropper. Specifically, the users adopt partial offloading strategy by partitioning computation task into several parts. One is executed locally others are securely offloaded to MEC servers integrated stations leveraging physical layer security combat eavesdrop...

Using reinforcement learning technologies to learn offloading strategies for multi-access edge computing systems has been developed by researchers. However, large-scale are unsuitable learning, due their huge state spaces and behaviors. For this reason, work introduces the centralized training decentralized execution mechanism, designing a model systems. Considering cloud server several servers...