Dynamic computation offloading and resource allocation for multi-user mobile edge computing
We study the problem of dynamic computation offloading and resource allocation in mobile
edge computing (MEC) systems consisting of multiple mobile users (MUs) with stochastic …
edge computing (MEC) systems consisting of multiple mobile users (MUs) with stochastic …
Multi-user multi-channel computation offloading and resource allocation for mobile edge computing
We study the problem of computation offloading and resourceallocation in multi-user multi-
channel mobile edge computing (MEC) systems. Each user equipment (UE) in the system …
channel mobile edge computing (MEC) systems. Each user equipment (UE) in the system …
Lyapunov-guided deep reinforcement learning for stable online computation offloading in mobile-edge computing networks
Opportunistic computation offloading is an effective method to improve the computation
performance of mobile-edge computing (MEC) networks under dynamic edge environment …
performance of mobile-edge computing (MEC) networks under dynamic edge environment …
Decentralized computation offloading for multi-user mobile edge computing: A deep reinforcement learning approach
Z Chen, X Wang - EURASIP Journal on Wireless Communications and …, 2020 - Springer
Mobile edge computing (MEC) emerges recently as a promising solution to relieve resource-
limited mobile devices from computation-intensive tasks, which enables devices to offload …
limited mobile devices from computation-intensive tasks, which enables devices to offload …
Sequential offloading for distributed dnn computation in multiuser mec systems
This article studies a sequential task offloading problem for a multiuser mobile-edge
computing (MEC) system. While most of the existing works consider static one-shot …
computing (MEC) system. While most of the existing works consider static one-shot …
Optimized computation offloading performance in virtual edge computing systems via deep reinforcement learning
To improve the quality of computation experience for mobile devices, mobile-edge
computing (MEC) is a promising paradigm by providing computing capabilities in close …
computing (MEC) is a promising paradigm by providing computing capabilities in close …
Deep reinforcement learning for energy-efficient computation offloading in mobile-edge computing
Mobile-edge computing (MEC) has emerged as a promising computing paradigm in the 5G
architecture, which can empower user equipments (UEs) with computation and energy …
architecture, which can empower user equipments (UEs) with computation and energy …
Stochastic computation offloading and scheduling based on mobile edge computing
To improve the quality of service (QoS) for mobile users (MUs) and the quality of experience
(QoE) of mobile devices (MDs), mobile edge computing (MEC) is a promising approach that …
(QoE) of mobile devices (MDs), mobile edge computing (MEC) is a promising approach that …
Deep reinforcement learning based computation offloading and resource allocation for MEC
Mobile edge computing (MEC) has the potential to enable computation-intensive
applications in 5G networks. MEC can extend the computational capacity at the edge of …
applications in 5G networks. MEC can extend the computational capacity at the edge of …
A deep reinforcement learning approach for collaborative mobile edge computing
J Wu, H Lin, H Liu, L Gao - ICC 2022-IEEE International …, 2022 - ieeexplore.ieee.org
Mobile edge computing (MEC) is a promising approach to reduce the network traffic load
and alleviate the back-haul congestion by pushing computation down to the network edge …
and alleviate the back-haul congestion by pushing computation down to the network edge …