Scalable and Efficient Diagnosis for 5G Data Center Network Traffic
Data center networks (DCNs) for 5G are expected to support a large number of different bandwidth-hungry applications with exploding data, such as real-time search and data analysis. As a result, significant challenges are imposed to identify the cause of link congestion between any pair of switch po...
Main Authors: | Chi Harold Liu, Jun Fan |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2014-01-01
|
Series: | IEEE Access |
Online Access: | https://ieeexplore.ieee.org/document/6879489/ |
Similar Items
-
Efficient traffic monitoring in 5G Core Network
by: Girondi, Massimo
Published: (2020) -
TrafficGather: An Efficient and Scalable Data Collection Protocol for Vehicular Ad Hoc Networks
by: Bo-Xuan Chen, et al.
Published: (2007) -
Scalable Intelligence-Enabled Networking with Traffic Engineering in 5G Scenarios for Future Audio-Visual-Tactile Internet
by: Yiqiang Sheng
Published: (2018-01-01) -
Network-Layer Protocols for Data Center Scalability
by: Desmouceaux, Yoann
Published: (2019) -
Scalability and Performance Analysis in 5G Core Network Slicing
by: Carlos Hernan Tobar Arteaga, et al.
Published: (2020-01-01)