Fast adaptive task offloading in edge computing based on meta reinforcement learning
Multi-access edge computing (MEC) aims to extend cloud service to the network edge to
reduce network traffic and service latency. A fundamental problem in MEC is how to …
reduce network traffic and service latency. A fundamental problem in MEC is how to …
Computation offloading in multi-access edge computing using a deep sequential model based on reinforcement learning
MEC is an emerging paradigm that utilizes computing resources at the network edge to
deploy heterogeneous applications and services. In the MEC system, mobile users and …
deploy heterogeneous applications and services. In the MEC system, mobile users and …
Digital twin-assisted and mobility-aware service migration in mobile edge computing
E Bozkaya - Computer Networks, 2023 - Elsevier
Abstract Mobile Edge Computing (MEC) is emerging as one of the key technologies to
process massive amount of data at the edge of the network for upcoming 6G networks. In the …
process massive amount of data at the edge of the network for upcoming 6G networks. In the …
Intelligent task offloading in vehicular edge computing networks
Recently, traditional transportation systems have been gradually evolving to ITS, inspired by
both artificial intelligence and wireless communications technologies. The vehicles get …
both artificial intelligence and wireless communications technologies. The vehicles get …
Digital twin-assisted URLLC-enabled task offloading in mobile edge network via robust combinatorial optimization
Digital twin (DT)-assisted mobile edge network can achieve energy-efficient task offloading
by optimizing the decision-making in real time. Although many DT-assisted task offloading …
by optimizing the decision-making in real time. Although many DT-assisted task offloading …
An integrated optimization-learning framework for online combinatorial computation offloading in MEC networks
Mobile edge computing (MEC) is a promising paradigm to accommodate the increasingly
prosperous delay-sensitive and computation-intensive applications in 5G systems. To …
prosperous delay-sensitive and computation-intensive applications in 5G systems. To …
Resource-efficient generative mobile edge networks in 6G era: Fundamentals, framework and case study
As the next-generation wireless communication system, sixth-generation (6G) technologies
are emerging, enabling various mobile edge networks that can revolutionize wireless …
are emerging, enabling various mobile edge networks that can revolutionize wireless …
Graph-reinforcement-learning-based task offloading for multiaccess edge computing
Z Sun, Y Mo, C Yu - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
Network applications involve massive heterogeneous data fusion and analysis. Artificial
intelligence can significantly improve the convenience and user experience, but it requires a …
intelligence can significantly improve the convenience and user experience, but it requires a …
Edge intelligence computing for mobile augmented reality with deep reinforcement learning approach
Abstract Convergence of Augmented Reality (AR) and Next Generation Internet-of-Things
(NG-IoT) can create new opportunities in many emerging areas, where the real-time data …
(NG-IoT) can create new opportunities in many emerging areas, where the real-time data …
Context-aware multi-user offloading in mobile edge computing: a federated learning-based approach
A Shahidinejad, F Farahbakhsh… - Journal of Grid …, 2021 - Springer
Mobile edge computing (MEC) provides an effective solution to help the Internet of Things
(IoT) devices with delay-sensitive and computation-intensive tasks by offering computing …
(IoT) devices with delay-sensitive and computation-intensive tasks by offering computing …