State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems
Tohoku University · NTT (Japan)
Indexed incrossref
Abstract
Currently, the network traffic control systems are mainly composed of the Internet core and wired/wireless heterogeneous backbone networks. Recently, these packet-switched systems are experiencing an explosive network traffic growth due to the rapid development of communication technologies. The existing network policies are not sophisticated enough to cope with the continually varying network conditions arising from the tremendous traffic growth. Deep learning, with the recent breakthrough in the machine learning/intelligence area, appears to be a viable approach for the network operators to configure and manage their networks in a more intelligent and autonomous fashion. While deep learning has received a…
Citation impact
822
total citations
- FWCI
- 86.14
- Percentile
- 100%
- References
- 319
Citations per year
Authors
7Topics & keywords
Topics
Keywords
- Computer science
- Deep learning
- Artificial intelligence
- Network traffic control
- Distributed computing
- Traffic generation model
- Machine learning
- Computer network
No related works found for this paper.