… cloud computing to edge networks, Mobile Edge Computing (MEC) pushes computing and …
as deploys applications in distributed mobile edge servers to provide a variety of computation-…

… , mobile-edge computing (MEC) is emerging as a promising paradigm by providing
computing … To break the curse of high dimensionality in state space, we propose a deep Q-network-…

… Abstract—Mobile edge computing (MEC) is a promising technology to support mission-… In
this paper, a collaborative edge computing framework is developed to reduce the computing …

… edge computing (MEC) networks for intelligent internet of things (IoT), where multiple users
have some computational tasks assisted by multiple computational … the deep reinforcement …

… tasks as well as edge load dynamics, and formulate a task offloading problem to minimize
the expected long-term cost. We propose a model-free deep reinforcement learning-based …

… edge applications. Thus, we propose a resource allocation policy for the IoT edge computing
… A deep reinforcement learning approach is applied to solve the problem. We also propose …

… edge computing network architecture in which the vehicles can act as the mobile edge …
long-term utility of the vehicle edge computing network. Considering the stochastic vehicle …

… computing capability at the edge of pervasive radio access networks close to users. A critical
research challenge of edge computing … tasks can be offloaded to edge servers with limited …

… , mobile-edge computing (MEC) is a promising paradigm by providing computing capabilities
… To break the curse of high dimensionality in state space, we first propose a double deep Q-…

… In this article, we investigate task scheduling in edge computing for which only one edge
server is deployed. The objective is to maximize the long-term task satisfaction of all tasks, …