Reinforcement learning methods for computation offloading: a systematic review
Z Zabihi, AM Eftekhari Moghadam… - ACM Computing …, 2023 - dl.acm.org
Today, cloud computation offloading may not be an appropriate solution for delay-sensitive
applications due to the long distance between end-devices and remote datacenters. In …
applications due to the long distance between end-devices and remote datacenters. In …
[HTML][HTML] A comprehensive survey on reinforcement-learning-based computation offloading techniques in edge computing systems
In recent years, the number of embedded computing devices connected to the Internet has
exponentially increased. At the same time, new applications are becoming more complex …
exponentially increased. At the same time, new applications are becoming more complex …
A survey of multi-access edge computing in 5G and beyond: Fundamentals, technology integration, and state-of-the-art
Driven by the emergence of new compute-intensive applications and the vision of the
Internet of Things (IoT), it is foreseen that the emerging 5G network will face an …
Internet of Things (IoT), it is foreseen that the emerging 5G network will face an …
Deep reinforcement learning for dynamic computation offloading and resource allocation in cache-assisted mobile edge computing systems
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 …
wireless communication systems. In this paper, we study the problem of dynamic caching …
Partial computation offloading in NOMA-assisted mobile-edge computing systems using deep reinforcement learning
Mobile-edge computing (MEC) and nonorthogonal multiple access (NOMA) have been
regarded as promising technologies for beyond fifth-generation (B5G) and sixth-generation …
regarded as promising technologies for beyond fifth-generation (B5G) and sixth-generation …
Machine learning meets communication networks: Current trends and future challenges
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …
massively expanding number of connected devices and online services, require intelligent …
Reinforcement learning for intelligent online computation offloading in wireless powered edge networks
The method of charging mobile devices with wireless power transfer (WPT) from the base
station (BS) integrated with mobile edge computing (MEC) increases the potential of MEC …
station (BS) integrated with mobile edge computing (MEC) increases the potential of MEC …
A review of intelligent computation offloading in multiaccess edge computing
H Jin, MA Gregory, S Li - IEEE Access, 2022 - ieeexplore.ieee.org
Multi-Access Edge Computing (MEC) is a standardized architecture that enables cloud
computing capabilities at the edge of heterogeneous networks. The concept is to reduce …
computing capabilities at the edge of heterogeneous networks. The concept is to reduce …
Deep reinforcement learning for shared offloading strategy in vehicle edge computing
X Peng, Z Han, W Xie, C Yu, P Zhu, J Xiao… - IEEE Systems …, 2022 - ieeexplore.ieee.org
Vehicular edge computing (VEC) effectively reduces the computing load of vehicles by
offloading computing tasks from vehicle terminals to edge servers. However, offloading of …
offloading computing tasks from vehicle terminals to edge servers. However, offloading of …
Multi-agent reinforcement learning-based resource management for end-to-end network slicing
To meet the explosive growth of mobile traffic, the 5G network is designed to be flexible and
support multi-access edge computing (MEC), thereby improving the end-to-end quality of …
support multi-access edge computing (MEC), thereby improving the end-to-end quality of …