Deep reinforcement learning based mobile edge computing for intelligent Internet of Things

R Zhao, X Wang, J Xia, L Fan - Physical Communication, 2020 - Elsevier
In this paper, we investigate mobile edge computing (MEC) networks for intelligent internet
of things (IoT), where multiple users have some computational tasks assisted by multiple …

HetMEC: Heterogeneous multi-layer mobile edge computing in the 6 G era

Y Zhang, B Di, P Wang, J Lin… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Driven by an increasing number of mobile applications, mobile edge computing (MEC) has
been considered as a promising candidate to support the huge amount of data processing …

Smart resource allocation for mobile edge computing: A deep reinforcement learning approach

J Wang, L Zhao, J Liu, N Kato - IEEE Transactions on emerging …, 2019 - ieeexplore.ieee.org
The development of mobile devices with improving communication and perceptual
capabilities has brought about a proliferation of numerous complex and computation …

Deep reinforcement learning based performance optimization in blockchain-enabled internet of vehicle

M Liu, Y Teng, FR Yu, VCM Leung… - ICC 2019-2019 IEEE …, 2019 - ieeexplore.ieee.org
The rapid development of Internet of Vehicles (IoV) necessitates a secure and reliable
infrastructure to store and share the massive data. Blockchain, a distributed and immutable …

B-ReST: Blockchain-enabled resource sharing and transactions in fog computing

Y Gao, W Wu, P Si, Z Yang… - IEEE Wireless …, 2021 - ieeexplore.ieee.org
Driven by the extensively emerging applications requiring big data processing, a series of
heterogeneous network architectures have been proposed to meet user experience …

Edge intelligence for energy-efficient computation offloading and resource allocation in 5G beyond

Y Dai, K Zhang, S Maharjan… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
5G beyond is an end-edge-cloud orchestrated network that can exploit heterogeneous
capabilities of the end devices, edge servers, and the cloud and thus has the potential to …

SDN-based resource allocation in edge and cloud computing systems: An evolutionary Stackelberg differential game approach

J Du, C Jiang, A Benslimane, S Guo… - IEEE/ACM Transactions …, 2022 - ieeexplore.ieee.org
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 …

Dynamic task offloading and resource allocation for mobile-edge computing in dense cloud RAN

Q Zhang, L Gui, F Hou, J Chen, S Zhu… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
With the unprecedented development of smart mobile devices (SMDs), eg, Internet-of-
Things devices and smartphones, various computation-intensive applications are …

Distributed dynamic resource management and pricing in the IoT systems with blockchain-as-a-service and UAV-enabled mobile edge computing

A Asheralieva, D Niyato - IEEE Internet of Things Journal, 2019 - ieeexplore.ieee.org
In this article, we study the pricing and resource management in the Internet of Things (IoT)
system with blockchain-as-a-service (BaaS) and mobile-edge computing (MEC). The BaaS …

Blockchain-based multi-access edge computing for future vehicular networks: A deep compressed neural network approach

D Zhang, FR Yu, R Yang - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
Vehicular ad hoc networks (VANETs) have become an important branch of future 6G smart
wireless communications. As an emerging key technology, multi-access edge computing …