Machine learning in beyond 5G/6G networks—State-of-the-art and future trends
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
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 …
Dynamic task offloading for mobile edge computing with hybrid energy supply
Y Chen, F Zhao, Y Lu, X Chen - Tsinghua Science and …, 2022 - ieeexplore.ieee.org
Mobile edge computing (MEC), as a new distributed computing model, satisfies the low
energy consumption and low latency requirements of computation-intensive services. The …
energy consumption and low latency requirements of computation-intensive services. The …
Machine learning for 6G wireless networks: Carrying forward enhanced bandwidth, massive access, and ultrareliable/low-latency service
To satisfy the expected plethora of demanding services, the future generation of wireless
networks (6G) has been mandated as a revolutionary paradigm to carry forward the …
networks (6G) has been mandated as a revolutionary paradigm to carry forward the …
A DRL agent for jointly optimizing computation offloading and resource allocation in MEC
This article studies the joint optimization problem of computation offloading and resource
allocation (JCORA) in mobile-edge computing (MEC). Deep reinforcement learning (DRL) is …
allocation (JCORA) in mobile-edge computing (MEC). Deep reinforcement learning (DRL) is …
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 …
Priority-aware task offloading in vehicular fog computing based on deep reinforcement learning
Vehicular fog computing (VFC) has been expected as a promising scheme that can increase
the computational capability of vehicles without relying on servers. Comparing with …
the computational capability of vehicles without relying on servers. Comparing with …
Blockchain-enabled task offloading with energy harvesting in multi-UAV-assisted IoT networks: A multi-agent DRL approach
Unmanned Aerial Vehicle (UAV) is a promising technology that can serve as aerial base
stations to assist Internet of Things (IoT) networks, solving various problems such as …
stations to assist Internet of Things (IoT) networks, solving various problems such as …
SDN-based resource allocation in edge and cloud computing systems: An evolutionary stackelberg differential game approach
Recently, the boosting growth of computation-heavy applications raises great challenges for
the Fifth Generation (5G) and future wireless networks. As responding, the hybrid edge and …
the Fifth Generation (5G) and future wireless networks. As responding, the hybrid edge and …
Self-learning based computation offloading for internet of vehicles: Model and algorithm
With the fast development of Internet of Vehicles (IoV), various types of computation-
intensive vehicular applications pose significant challenges to resource-constrained …
intensive vehicular applications pose significant challenges to resource-constrained …