We present a novel game-theoretic (GT) and reinforcement learning (RL) framework for
computational offloading in the mobile edge computing (MEC) network operated by multiple …

With the development of Unmanned Aerial Vehicles (UAVs) in recent years, UAV-mounted
Mobile Edge Computing (MEC) systems are widely used for broadband connectivity and …

With the emergence of multi-access edge computing (MEC) paradigm, mobile users who
have computation-intensive and low-latency tasks can exploit computing resources of …

In order to meet the double-sided challenges brought by the shortage of computation
resources and energy of users, we investigate in this paper the optimization of energy …

In this paper, we investigate the joint impact of task priority and mobile computing service on
the mobile edge computing (MEC) networks, in which one unmanned aerial vehicle (UAV) …

Mobile edge computing (MEC) harvests the computation capability at the network edge to
perform the computation intensive tasks for diverse IoT applications. Meanwhile, the …

The proliferation of Internet-of-Things (IoTs) devices provides a promising platform for
various intelligent applications such as virtual reality. However, because of the limited …

This paper studies a deep reinforcement learning (DRL) approach for the unmanned aerial
vehicle (UAV)-assisted mobile edge computing (MEC) networks where a UAV-mounted …

With the high flexibility of supporting resource-intensive and time-sensitive applications,
unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) is proposed as an …

Deploying unmanned aerial vehicles (UAVs) as mobile edge computing (MEC) servers has
been attracting significant attention, since the UAVs' inherent maneuverability and mobility …