TY - CHAP
T1 - Machine Learning Empowered Intelligent Data Center Networking
AU - Wang, Ting
AU - Li, Bo
AU - Chen, Mingsong
AU - Yu, Shui
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
PY - 2023
Y1 - 2023
N2 - 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, compare, and discuss the existing work in the following research areas: flow prediction, flow classification, load balancing, resource management, energy management, routing optimization, congestion control, fault management, network security, and new intelligent networking concepts.
AB - 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, compare, and discuss the existing work in the following research areas: flow prediction, flow classification, load balancing, resource management, energy management, routing optimization, congestion control, fault management, network security, and new intelligent networking concepts.
UR - http://www.scopus.com/inward/record.url?scp=85149441018&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85149441018&partnerID=8YFLogxK
U2 - 10.1007/978-981-19-7395-6_3
DO - 10.1007/978-981-19-7395-6_3
M3 - Chapter
AN - SCOPUS:85149441018
T3 - SpringerBriefs in Computer Science
SP - 15
EP - 99
BT - SpringerBriefs in Computer Science
PB - Springer
ER -