Dynamic service placement in multi-access edge computing: A systematic literature review

HT Malazi, SR Chaudhry, A Kazmi, A Palade… - IEEE …, 2022 - ieeexplore.ieee.org
The advent of new cloud-based applications such as mixed reality, online gaming,
autonomous driving, and healthcare has introduced infrastructure management challenges …

Edge intelligence: The confluence of edge computing and artificial intelligence

S Deng, H Zhao, W Fang, J Yin… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Along with the rapid developments in communication technologies and the surge in the use
of mobile devices, a brand-new computation paradigm, edge computing, is surging in …

Distributed redundant placement for microservice-based applications at the edge

H Zhao, S Deng, Z Liu, J Yin… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Multi-access edge computing (MEC) is booming as a promising paradigm to push the
computation and communication resources from cloud to the network edge to provide …

IoT microservice deployment in edge-cloud hybrid environment using reinforcement learning

L Chen, Y Xu, Z Lu, J Wu, K Gai… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
The edge-cloud hybrid environment requires complex deployment strategies to enable the
smart Internet-of-Things (IoT) system. However, current service deployment strategies use …

Dynamic energy-saving offloading strategy guided by Lyapunov optimization for IoT devices

Z Tong, J Cai, J Mei, K Li, K Li - IEEE Internet of Things Journal, 2022 - ieeexplore.ieee.org
In the Internet of Everything era, various Internet of Things (IoT) devices have become
popular, and the number of computing-intensive applications has increased substantially. As …

Adaptive service function chaining mappings in 5G using deep Q-learning

G Li, B Feng, H Zhou, Y Zhang, K Sood, S Yu - Computer Communications, 2020 - Elsevier
Abstract With introduction of Software-Defined Networking (SDN) and Network Functions
Virtualization (NFV) technologies, mobile network operators are able to provide on-demand …

Cooperative resource allocation for computation-intensive IIoT applications in aerial computing

J Liu, G Li, Q Huang, M Bilal, X Xu… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
Unmanned aerial vehicles (UAVs) will be a vital part of the massive Industrial Internet of
Things (IIoT) in the 5G and 6G paradigms. The UAVs are required to collaborate with each …

An adaptive mechanism for dynamically collaborative computing power and task scheduling in edge environment

Y Xu, L Chen, Z Lu, X Du, J Wu… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
Edge computing can provide high bandwidth and low-latency service for big data tasks by
leveraging the edge side's computing, storage, and network resources. With the …

Optimized task allocation for IoT application in mobile-edge computing

J Liu, C Liu, B Wang, G Gao… - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
With the rapid upgrading and explosive growth of Internet of Things (IoT) devices in mobile-
edge computing, more and more IoT applications with high resource requirements are …

Reinforcement learning for cost-effective IoT service caching at the edge

B Huang, X Liu, Y Xiang, D Yu, S Deng… - Journal of Parallel and …, 2022 - Elsevier
In the edge computing environment, Internet of Things (IoT) application service providers
can rent resources from edge servers to cache their service items such as datasets and code …