Future data center energy-conservation and emission-reduction technologies in the context of smart and low-carbon city construction

H Zhu, D Zhang, HH Goh, S Wang, T Ahmad… - Sustainable Cities and …, 2023 - Elsevier
The energy consumption of data centers accounts for approximately 1% of that of the world,
the average power usage effectiveness is in the range of 1.4–1.6, and the associated carbon …

[HTML][HTML] Comprehensive survey on energy-aware server consolidation techniques in cloud computing

N Chaurasia, M Kumar, R Chaudhry… - The Journal of …, 2021 - Springer
The objective of cloud computing is to provide seamless services using virtualization
technology over the Internet to serve the Quality of Service (QoS)-driven end users …

AFED-EF: An energy-efficient VM allocation algorithm for IoT applications in a cloud data center

Z Zhou, M Shojafar, M Alazab… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Cloud Data Centers (CDCs) have become a vital computing infrastructure for enterprises.
However, CDCs consume substantial energy due to the increased demand for computing …

Real-time virtual machine scheduling in industry IoT network: A reinforcement learning method

X Ma, H Xu, H Gao, M Bian… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The widespread adoption of Industrial Internet of Things (IIoT)-based applications has driven
the emergence and development of cloud-related computing paradigms with the ability to …

Electronic health records based reinforcement learning for treatment optimizing

T Li, Z Wang, W Lu, Q Zhang, D Li - Information Systems, 2022 - Elsevier
Abstract Electronic Health Records (EHRs) have become one of the main sources of
evidence to evaluate clinical actions, improve medical quality, predict disease-risk, and …

[HTML][HTML] Adaptive computational solutions to energy efficiency in cloud computing environment using VM consolidation

B Magotra, D Malhotra, AK Dogra - Archives of Computational Methods in …, 2023 - Springer
Cloud Computing has emerged as a computing paradigm where services are provided
through the internet in recent years. Offering on-demand services has transformed the IT …

[HTML][HTML] Realizing self-adaptive systems via online reinforcement learning and feature-model-guided exploration

A Metzger, C Quinton, ZÁ Mann, L Baresi, K Pohl - Computing, 2024 - Springer
A self-adaptive system can automatically maintain its quality requirements in the presence of
dynamic environment changes. Developing a self-adaptive system may be difficult due to …

Environmental performance evaluation of electric enterprises during a power crisis: Evidence from DEA methods and AI prediction algorithms

Y Pan, CC Zhang, CC Lee, S Lv - Energy Economics, 2024 - Elsevier
With the continuous occurrence of power crisis events worldwide, meeting society's demand
for electricity has kept coal-fired power generation high, which leads to a large amount of …

Scalable virtual machine migration using reinforcement learning

AR Hummaida, NW Paton, R Sakellariou - Journal of Grid Computing, 2022 - Springer
Heuristic approaches require fixed knowledge of how resource allocation should be carried
out, and this can be limiting when managing variable cloud workloads. Solutions based on …

Dynamic thermal environment management technologies for data center: A review

Y Du, Z Zhou, X Yang, X Yang, C Wang, J Liu… - … and Sustainable Energy …, 2023 - Elsevier
The energy demand of the data center (DC) industry has accounted for 2% of the total global
energy consumption, and its operating power consumption has reached 50 times that of the …