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 …
energy consumption, and its operating power consumption has reached 50 times that of the …
When machine learning meets congestion control: A survey and comparison
Abstract Machine learning has seen a significant surge and uptake across many diverse
applications. The high flexibility, adaptability, and computing capabilities it provides extend …
applications. The high flexibility, adaptability, and computing capabilities it provides extend …
A survey on traffic management in software-defined networks: challenges, effective approaches, and potential measures
Abstract Software-defined networks (SDNs), as an emerging paradigm by separating the
control plane from the data plane, increases flexibility and network utilization and reduces …
control plane from the data plane, increases flexibility and network utilization and reduces …
Congestion control in SDN-based networks via multi-task deep reinforcement learning
K Lei, Y Liang, W Li - IEEE Network, 2020 - ieeexplore.ieee.org
Congestion control is a fundamental network task that modulates the data transmission rates
of traffic sources to efficiently utilize network capacity. With the advent of machine learning …
of traffic sources to efficiently utilize network capacity. With the advent of machine learning …
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs
As communication protocols evolve, datacenter network utilization increases. As a result,
congestion is more frequent, causing higher latency and packet loss. Combined with the …
congestion is more frequent, causing higher latency and packet loss. Combined with the …
Machine learning empowered intelligent data center networking: A survey
To support the needs of ever-growing cloud-based services, the number of servers and
network devices in data centers is increasing exponentially, which in turn results in high …
network devices in data centers is increasing exponentially, which in turn results in high …
电磁频谱空间射频机器学习及其应用综述.
周福辉， 张子彤， 丁锐， 徐铭， 袁璐… - … /Shu Ju Cai Ji Yu Chu …, 2022 - search.ebscohost.com
针对电磁频谱空间中频谱资源日益稀缺的问题, 新兴的射频机器学习旨在结合电磁频谱领域知识
, 设计专门的机器学习模型, 具有快速, 小样本甚至零样本, 可解释性和高性能的优势 …
, 设计专门的机器学习模型, 具有快速, 小样本甚至零样本, 可解释性和高性能的优势 …
Sdn/legacy hybrid network control system
F Kuliesius, M Giedraitis - 2019 Eleventh International …, 2019 - ieeexplore.ieee.org
The widespread replacement of traditional network to SDN is still restricted in the enterprise
environment, and hybrid network where SDN and legacy network appliances coexist by …
environment, and hybrid network where SDN and legacy network appliances coexist by …
An end-to-end flow control method based on dqn
G Gao, R Jin - 2022 International Conference on Big Data …, 2022 - ieeexplore.ieee.org
We propose an end-to-end flow control method based on DQN (Deep-Q-Network). The flow
control method is intelligent and flow-based, it is suitable for those DCNs (Data Center …
control method is intelligent and flow-based, it is suitable for those DCNs (Data Center …
Machine learning empowered intelligent data center networking
Abstract Machine learning has been widely studied and practiced in data center networks,
and a large number of achievements have been made. In this chapter, we will review …
and a large number of achievements have been made. In this chapter, we will review …