With the rapid development and deployment of 5G wireless technology, mobile edge
computing (MEC) has emerged as a new computing paradigm to facilitate a large variety of …

In this paper, we investigate strategies for the allocation of computational resources using
deep reinforcement learning in mobile edge computing networks that operate with finite …

A fundamental issue in multiaccess edge computing (MEC) is efficiently offloading multiple
tasks to multiple helper nodes (MTMH), ie, MEC servers. However, most of the existing …

We consider a multi-user multi-server mobile edge computing (MEC) network with time-
varying fading channels and formulate an offloading decision and resource allocation …

This paper investigates the multi-part collaborative task offloading with multiple servers in
mobile edge computing (MEC) systems by considering server overload and long-term …

As demands for multi-access edge computing (MEC) increase exponentially, resource
limitations at individual edge servers (ESs) will inevitably become bottlenecks. Most existing …

Multi-access edge computing promises satisfactory user experience by offloading tasks to
the MEC server deployed at the network edge. However, since the MEC server is often …

Multi-access edge computing (MEC) is a promising computing paradigm that incorporates
computing capability into a radio access network (RAN) nearby user equipment (UE) to …

Fifth-Generation (5G) networks have adopted a multi-tier structural model which includes
femtocells, picocells, and macrocells to ensure the user quality-of-service (QoS). To meet …