Abstract
Many network resource management solutions typically employ traffic prediction algorithms to improve the performance of a network. In this paper we extend a newly developed method for prediction with confidence to time series data and apply it to the network traffic demand prediction problem. We investigate the performance of the proposed algorithm on a number of publicly available network traffic demand datasets. The experimental results are very promising.
| Original language | English |
|---|---|
| Title of host publication | IEEE GLOBECOM 2008 |
| Pages | 1-5 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2008 |
Projects
- 2 Finished
-
Machine learning for resource management in next-generation optical networks
Luo, Z. (PI)
1/10/06 → 30/09/09
Project: Research
-
Machine learning for resource management in next-generation optical networks
Luo, Z. (PI)
Eng & Phys Sci Res Council EPSRC
1/10/06 → 30/09/09
Project: Research
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