Title :
Network Traffic Demand Prediction with Confidence
Author :
Dashevskiy, Mikhail ; Luo, Zhiyuan
Author_Institution :
Comput. Learning Res. Centre, Univ. of London, Egham
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.
Keywords :
telecommunication computing; telecommunication network management; telecommunication traffic; time series; conformal predictor; network resource management; network traffic demand prediction; time series data; Computer networks; Learning systems; Machine learning algorithms; Neural networks; Prediction algorithms; Resource management; Routing; Statistical analysis; Telecommunication traffic; Time series analysis;
Conference_Titel :
Global Telecommunications Conference, 2008. IEEE GLOBECOM 2008. IEEE
Conference_Location :
New Orleans, LO
Print_ISBN :
978-1-4244-2324-8
DOI :
10.1109/GLOCOM.2008.ECP.284
