Deep reinforcement learning towards real-world dynamic thermal management of data centers
Abstract Deep Reinforcement Learning has been increasingly researched for Dynamic
Thermal Management in Data Centers. However, existing works typically evaluate the …
Thermal Management in Data Centers. However, existing works typically evaluate the …
DRL-S: Toward safe real-world learning of dynamic thermal management in data center
Abstract Deep Reinforcement Learning has been researched for Dynamic Thermal
Management in Data Centers. An objective of Dynamic Thermal Management is to minimize …
Management in Data Centers. An objective of Dynamic Thermal Management is to minimize …
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 …
SafeCool: safe and energy-efficient cooling management in data centers with model-based reinforcement learning
J Wan, Y Duan, X Gui, C Liu, L Li… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Optimizing the cooling system plays a central role for capping the data center power
consumption. However, the performance of traditional cooling management strategies is not …
consumption. However, the performance of traditional cooling management strategies is not …
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 …
GreenDRL: managing green datacenters using deep reinforcement learning
Managing datacenters to maximize efficiency and sustain-ability is a complex and
challenging problem. In this work, we explore the use of deep reinforcement learning (RL) to …
challenging problem. In this work, we explore the use of deep reinforcement learning (RL) to …
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 …
Reinforcement learning testbed for power-consumption optimization
Common approaches to control a data-center cooling system rely on approximated
system/environment models that are built upon the knowledge of mechanical cooling and …
system/environment models that are built upon the knowledge of mechanical cooling and …
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 …
Toward physics-guided safe deep reinforcement learning for green data center cooling control
Deep reinforcement learning (DRL) has shown good performance in tackling Markov
decision process (MDP) problems. As DRL opti-mizes a long-term reward, it is a promising …
decision process (MDP) problems. As DRL opti-mizes a long-term reward, it is a promising …