Joint server selection, cooperative offloading and handover in multi-access edge computing wireless network: A deep reinforcement learning approach
Multi-access edge computing (MEC) is the key enabling technology that supports compute-
intensive applications in 5G networks. By deploying powerful servers at the edge of wireless …
intensive applications in 5G networks. By deploying powerful servers at the edge of wireless …
Joint computation offloading and task caching for multi-user and multi-task MEC systems: reinforcement learning-based algorithms
IA Elgendy, WZ Zhang, H He, BB Gupta… - Wireless …, 2021 - Springer
Computation offloading at mobile edge computing (MEC) servers can mitigate the resource
limitation and reduce the communication latency for mobile devices. Thereby, in this study …
limitation and reduce the communication latency for mobile devices. Thereby, in this study …
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 …
Optimization for computational offloading in multi-access edge computing: A deep reinforcement learning scheme
J Wang, H Ke, X Liu, H Wang - Computer Networks, 2022 - Elsevier
Owing to their limited computing power and battery level, wireless users (WUs) can hardly
handle compute-intensive workflows by the local processor. Multi-access edge computing …
handle compute-intensive workflows by the local processor. Multi-access edge computing …
[HTML][HTML] Multi-server multi-user multi-task computation offloading for mobile edge computing networks
This paper studies mobile edge computing (MEC) networks where multiple wireless devices
(WDs) offload their computation tasks to multiple edge servers and one cloud server …
(WDs) offload their computation tasks to multiple edge servers and one cloud server …
Dynamic offloading for multiuser muti-CAP MEC networks: A deep reinforcement learning approach
In this paper, we study a multiuser mobile edge computing (MEC) network, where tasks from
users can be partially offloaded to multiple computational access points (CAPs). We …
users can be partially offloaded to multiple computational access points (CAPs). We …
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 …
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 …
Performance optimization in mobile-edge computing via deep reinforcement learning
To improve the quality of computation experience for mobile devices, mobile-edge
computing (MEC) is emerging as a promising paradigm by providing computing capabilities …
computing (MEC) is emerging as a promising paradigm by providing computing capabilities …
Adaptive computation offloading policy for multi-access edge computing in heterogeneous wireless networks
H Ke, H Wang, W Sun, H Sun - IEEE Transactions on Network …, 2021 - ieeexplore.ieee.org
In heterogeneous wireless networks, massive mobile terminals randomly generate a large
number of computation tasks (payloads). How to better manage these mobile terminals …
number of computation tasks (payloads). How to better manage these mobile terminals …