Deep reinforcement learning for dynamic computation offloading and resource allocation in cache-assisted mobile edge computing systems

S Nath, J Wu - Intelligent and Converged Networks, 2020 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) is one of the most promising techniques for next-generation
wireless communication systems. In this paper, we study the problem of dynamic caching …

Lyapunov-guided deep reinforcement learning for stable online computation offloading in mobile-edge computing networks

S Bi, L Huang, H Wang… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Opportunistic computation offloading is an effective method to improve the computation
performance of mobile-edge computing (MEC) networks under dynamic edge environment …

Learning for computation offloading in mobile edge computing

TQ Dinh, QD La, TQS Quek… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Mobile edge computing (MEC) is expected to provide cloud-like capacities for mobile users
(MUs) at the edge of wireless networks. However, deploying MEC systems faces many …

Computation offloading in multi-access edge computing networks: A multi-task learning approach

B Yang, X Cao, J Bassey, X Li… - ICC 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
Multi-access edge computing (MEC) has already shown the potential in enabling mobile
devices to bear the computation-intensive applications by offloading some tasks to a nearby …

Offloading and resource allocation with general task graph in mobile edge computing: A deep reinforcement learning approach

J Yan, S Bi, YJA Zhang - IEEE Transactions on Wireless …, 2020 - ieeexplore.ieee.org
In this paper, we consider a mobile-edge computing (MEC) system, where an access point
(AP) assists a mobile device (MD) to execute an application consisting of multiple tasks …

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 …

Deep Q-Learning Based Computation Offloading Strategy for Mobile Edge Computing.

Y Wei, Z Wang, D Guo, FR Yu - Computers, Materials & …, 2019 - search.ebscohost.com
To reduce the transmission latency and mitigate the backhaul burden of the centralized
cloud-based network services, the mobile edge computing (MEC) has been drawing …

Computation offloading in multi-access edge computing: A multi-task learning approach

B Yang, X Cao, J Bassey, X Li… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Multi-access edge computing (MEC) has already shown great potential in enabling mobile
devices to bear the computation-intensive applications by offloading some computing jobs to …

[HTML][HTML] Deep reinforcement learning-based joint task offloading and bandwidth allocation for multi-user mobile edge computing

L Huang, X Feng, C Zhang, L Qian, Y Wu - Digital Communications and …, 2019 - Elsevier
The rapid growth of mobile internet services has yielded a variety of computation-intensive
applications such as virtual/augmented reality. Mobile Edge Computing (MEC), which …

Energy efficient joint computation offloading and service caching for mobile edge computing: A deep reinforcement learning approach

H Zhou, Z Zhang, Y Wu, M Dong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) meets the delay requirements of emerging applications and
reduces energy consumption by pushing cloud functions to the edge of the networks …