Prediction‐Based Resource Deployment and Task Scheduling in Edge‐Cloud Collaborative Computing

M Su, G Wang, KKR Choo - Wireless Communications and …, 2022 - Wiley Online Library
Edge computing is becoming increasingly commonplace, as consumer devices become
more computationally capable and network connectivity improves (eg, due to 5G). With the …

Meeting users' QoS in a edge-to-cloud platform via optimally placing services and scheduling tasks

M Turner, H Khamfroush - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
This paper considers the problem of service placement and task scheduling on a three-
tiered edge-to-cloud platform when user requests must be met by a certain deadline. Time …

[HTML][HTML] SLA-ORECS: an SLA-oriented framework for reallocating resources in edge-cloud systems

S Lan, Z Duan, S Lu, B Tan, S Chen, Y Liang… - Journal of Cloud …, 2024 - Springer
The emergence of the Fifth Generation (5G) era has ushered in a new era of diverse
business scenarios, primarily characterized by data-intensive and latency-sensitive …

Deep-deterministic policy gradient based multi-resource allocation in edge-cloud system: a distributed approach

A Qadeer, MJ Lee - IEEE Access, 2023 - ieeexplore.ieee.org
Edge Cloud (EC) empowers the beyond 5G (B5G) wireless networks to cope with large-
scale and real-time traffics of Internet-of-Things (IoT) by minimizing the latency and providing …

Application Placement in Edge Computing–Optimization, Game, and Deep Reinforcement Learning

Z Cao - 2021 - search.proquest.com
Edge computing is a promising computing paradigm that will meet the service requirements
of the latency-sensitive and/or bandwidth-hungry applications brought by the rapidly …

Ehga: A genetic algorithm based approach for scheduling tasks on distributed edge-cloud infrastructures

A Mahjoubi, KJ Grinnemo… - 2022 13th International …, 2022 - ieeexplore.ieee.org
Due to cloud computing's limitations, edge computing has emerged to address computation-
intensive and time-sensitive applications. In edge computing, users can offload their tasks to …

DDPG-edge-cloud: A deep-deterministic policy gradient based multi-resource allocation in edge-cloud system

A Qadeer, MJ Lee - … on Artificial Intelligence in Information and …, 2022 - ieeexplore.ieee.org
5G and beyond is the key enabler for extreme mobile-broadband (xMBB), Massive and Ultra-
reliable machine-type communication (mMTC, uMTC). To handle such large-scale and real …

MPDM: A Multi-Paradigm Deployment Model for Large-Scale Edge-Cloud Intelligence

L Wang, X Ren, C Zhao, F Zhao… - IEEE Internet of Things …, 2022 - ieeexplore.ieee.org
The development of cloud and edge computing has enabled the easy access of artificial
intelligence (AI) services for massive heterogeneous and resource-constrained devices …

Efficient resource allocation policy for cloud edge end framework by reinforcement learning

C Yang, H Xu, S Fan, X Cheng, M Liu… - 2022 IEEE 8th …, 2022 - ieeexplore.ieee.org
Recently, Mobile Edge Cloud Computing (MECC) emerges as a promising partial offloading
paradigm to provide computing services. However, the design of computation resource …

Enabling mobile virtual reality with open 5G, fog computing and reinforcement learning

Y Sun, J Chen, Z Wang, M Peng, S Mao - IEEE Network, 2022 - ieeexplore.ieee.org
Virtual reality (VR) is an emerging technology reshaping interactive experience and can be
widely applied in gaming, operation training, and so on. Despite its great potentials, most …