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 …
Task co-offloading for D2D-assisted mobile edge computing in industrial internet of things
Mobile edge computing (MEC) and device-to-device (D2D) offloading are two promising
paradigms in the industrial Internet of Things (IIoT). In this article, we investigate task co …
paradigms in the industrial Internet of Things (IIoT). In this article, we investigate task co …
Reverse auction-based computation offloading and resource allocation in mobile cloud-edge computing
This article proposes a novel Reverse Auction-based Computation Offloading and Resource
Allocation Mechanism, named RACORAM for the mobile Cloud-Edge computing. The basic …
Allocation Mechanism, named RACORAM for the mobile Cloud-Edge computing. The basic …
Machine Learning Empowered Emerging Wireless Networks in 6G: Recent Advancements, Challenges & Future Trends
The upcoming 6G networks are sixth-sense next-generation communication networks with
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …
an ever-increasing demand for enhanced end-to-end (E2E) connectivity towards a …
Distributed deep multi-agent reinforcement learning for cooperative edge caching in internet-of-vehicles
Edge caching is a promising approach to reduce duplicate content transmission in Internet-
of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have …
of-Vehicles (IoVs). Several Reinforcement Learning (RL) based edge caching methods have …
Joint optimization of computing offloading and service caching in edge computing-based smart grid
With the continuous expansion of the power Internet of Things (IoT) and the rapid increase in
the number of Smart Devices (SDs), the data generated by SDs has exponentially …
the number of Smart Devices (SDs), the data generated by SDs has exponentially …
Cost minimization-oriented computation offloading and service caching in mobile cloud-edge computing: An A3C-based approach
This paper considers computation offloading and service caching in a three-tier mobile
cloud-edge computing structure, in which Mobile Users (MUs) have subscribed to the Cloud …
cloud-edge computing structure, in which Mobile Users (MUs) have subscribed to the Cloud …
UAV-aided computation offloading in mobile-edge computing networks: A Stackelberg game approach
Unmanned aerial vehicles (UAVs) are considered as a promising method to provide
additional computation capability and wide coverage for mobile users (MUs), especially …
additional computation capability and wide coverage for mobile users (MUs), especially …
Accelerating deep learning inference via model parallelism and partial computation offloading
With the rapid development of Internet-of-Things (IoT) and the explosive advance of deep
learning, there is an urgent need to enable deep learning inference on IoT devices in Mobile …
learning, there is an urgent need to enable deep learning inference on IoT devices in Mobile …
A deep reinforcement learning-based resource management game in vehicular edge computing
X Zhu, Y Luo, A Liu, NN **ong… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is a promising paradigm that leverages the vehicles to
offload computation tasks to the nearby VEC server with the aim of supporting the low …
offload computation tasks to the nearby VEC server with the aim of supporting the low …