Deep reinforcement learning-based methods for resource scheduling in cloud computing: A review and future directions

G Zhou, W Tian, R Buyya, R Xue, L Song - Artificial Intelligence Review, 2024 - Springer
With the acceleration of the Internet in Web 2.0, Cloud computing is a new paradigm to offer
dynamic, reliable and elastic computing services. Efficient scheduling of resources or …

Adaptive and efficient resource allocation in cloud datacenters using actor-critic deep reinforcement learning

Z Chen, J Hu, G Min, C Luo… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The ever-expanding scale of cloud datacenters necessitates automated resource
provisioning to best meet the requirements of low latency and high energy-efficiency …

Multi-dimensional resource allocation in distributed data centers using deep reinforcement learning

W Wei, H Gu, K Wang, J Li, X Zhang… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
With the development of edge-cloud computing technologies, distributed data centers (DCs)
have been extensively deployed across the global Internet. Since different …

Towards attack-resistant service function chain migration: A model-based adaptive proximal policy optimization approach

T Zhang, C Xu, B Zhang, X Li, X Kuang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Network function virtualization (NFV) supports the rapid development of service function
chain (SFC), which efficiently connects a sequence of network virtual function instances …

Deep reinforcement learning-based algorithms selectors for the resource scheduling in hierarchical cloud computing

G Zhou, R Wen, W Tian, R Buyya - Journal of Network and Computer …, 2022 - Elsevier
Cloud computing environment is becoming increasingly complex due to its large-scale
information growth and increasing heterogeneity of computing resources. Hierarchical …

Fault tolerance and quality of service aware virtual machine scheduling algorithm in cloud data centers

H Xu, S Xu, W Wei, N Guo - The Journal of Supercomputing, 2023 - Springer
How to improve resource utilization of cloud data centers (CDCs) and ensure users' quality
of service (QoS) through efficient virtual machine (VM) scheduling is an urgent problem …

Optimal policy characterization enhanced proximal policy optimization for multitask scheduling in cloud computing

J **, Y Xu - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
For a serving system with multiple servers and a public queue, we study the scheduling of
multiple tasks with deadlines, under random task arrivals and renewable energy generation …

A systematic literature review on contemporary and future trends in virtual machine scheduling techniques in cloud and multi-access computing

N Rana, F Jeribi, Z Khan, W Alrawagfeh… - Frontiers in Computer …, 2024 - frontiersin.org
Introduction The migration of business and scientific operations to the cloud and the surge in
data from IoT devices have intensified the complexity of cloud resource scheduling …

[HTML][HTML] A design and application of municipal service platform based on cloud-edge collaboration for smart cities

J Yang, TY Lee, WT Lee, L Xu - Sensors, 2022 - mdpi.com
Information and Communication Technology (ICT) makes cities “smart”, capable of providing
advanced municipal services to citizens more efficiently. In the literature, many applications …

An energy-aware ant colony optimization strategy for virtual machine placement in cloud computing

LT Duan, J Wang, HY Wang - Cluster Computing, 2024 - Springer
Virtual machine placement (VMP) directly impacts the energy consumption, resource
utilization, and service quality of cloud data centers (CDCs), and it has become an active …