Optimizing energy efficiency for data center via parameterized deep reinforcement learning
The rapid advancements in cloud computing, Big Data and their related applications have
led to a skyrocketing increase in data center energy consumption year by year. The prior …
led to a skyrocketing increase in data center energy consumption year by year. The prior …
Deepee: Joint optimization of job scheduling and cooling control for data center energy efficiency using deep reinforcement learning
The past decade witnessed the tremendous growth of power consumption in data centers
due to the rapid development of cloud computing, big data analytics, and machine learning …
due to the rapid development of cloud computing, big data analytics, and machine learning …
Optimizing data center energy efficiency via event-driven deep reinforcement learning
To reduce the skyrocketing energy consumption of data centers, the prevailing approaches
adopt the time-driven manner to control IT and cooling subsystems. These methods suffer …
adopt the time-driven manner to control IT and cooling subsystems. These methods suffer …
Transforming cooling optimization for green data center via deep reinforcement learning
Data center (DC) plays an important role to support services, such as e-commerce and cloud
computing. The resulting energy consumption from this growing market has drawn …
computing. The resulting energy consumption from this growing market has drawn …
[HTML][HTML] Cooperatively improving data center energy efficiency based on multi-agent deep reinforcement learning
C Chi, K Ji, P Song, A Marahatta, S Zhang, F Zhang… - Energies, 2021 - mdpi.com
The problem of high power consumption in data centers is becoming more and more
prominent. In order to improve the energy efficiency of data centers, cooperatively optimizing …
prominent. In order to improve the energy efficiency of data centers, cooperatively optimizing …
Jointly optimizing the IT and cooling systems for data center energy efficiency based on multi-agent deep reinforcement learning
C Chi, K Ji, A Marahatta, P Song, F Zhang… - Proceedings of the …, 2020 - dl.acm.org
With the development and application of cloud computing, the increasing amount of data
centers has resulted in huge energy consumption and severe environmental problems …
centers has resulted in huge energy consumption and severe environmental problems …
Towards an energy-efficient Data Center Network based on deep reinforcement learning
Abstract Data Center Network (DCN) plays a crucial role in orchestrating the physical or
virtual resources in data centers to meet the requirements of Internet of Things and Cloud …
virtual resources in data centers to meet the requirements of Internet of Things and Cloud …
Parameterized deep reinforcement learning with hybrid action space for energy efficient data center networks
To ensure the delivery of high-performance and reliable services, data center networks
(DCNs) are often over-provisioned for peak workload and traffic bursts. However, in real …
(DCNs) are often over-provisioned for peak workload and traffic bursts. However, in real …
Toward efficient compute-intensive job allocation for green data centers: A deep reinforcement learning approach
Reducing the energy consumption of the servers in a data center via proper job allocation is
desirable. Existing advanced job allocation algorithms, based on constrained optimization …
desirable. Existing advanced job allocation algorithms, based on constrained optimization …
Energy saving evaluation of an energy efficient data center using a model-free reinforcement learning approach
To reduce cooling energy consumption, data centers are recommended to raise temperature
setpoints of server intake. However, in tropical climates, Data Center operators are still found …
setpoints of server intake. However, in tropical climates, Data Center operators are still found …