TY - GEN
T1 - A novel LMS method for real-time network traffic prediction
AU - Xinyu, Yang
AU - Ming, Zeng
AU - Rui, Zhao
AU - Yi, Shi
PY - 2004
Y1 - 2004
N2 - Real-time traffic prediction could give important information to both network efficiency and QoS guarantees. On the basis of LMS algorithm, this paper presents an improved LMS predictor - EaLMS (Error-adjusted LMS) -for fundamental traffic prediction. The main idea of EaLMS is using previous prediction errors to adjust the LMS prediction value, so that the prediction delay could be decreased. The prediction experiment based on real traffic trace has proved that for short-term traffic prediction, compared with traditional LMS predictor, EaLMS significantly reduces prediction delay, especially at traffic burst moments, and avoids the problem of augmenting prediction error at the same time.
AB - Real-time traffic prediction could give important information to both network efficiency and QoS guarantees. On the basis of LMS algorithm, this paper presents an improved LMS predictor - EaLMS (Error-adjusted LMS) -for fundamental traffic prediction. The main idea of EaLMS is using previous prediction errors to adjust the LMS prediction value, so that the prediction delay could be decreased. The prediction experiment based on real traffic trace has proved that for short-term traffic prediction, compared with traditional LMS predictor, EaLMS significantly reduces prediction delay, especially at traffic burst moments, and avoids the problem of augmenting prediction error at the same time.
UR - https://www.scopus.com/pages/publications/77949770633
U2 - 10.1007/978-3-540-24768-5_14
DO - 10.1007/978-3-540-24768-5_14
M3 - 会议稿件
AN - SCOPUS:77949770633
SN - 3540220607
SN - 9783540220602
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 127
EP - 136
BT - Computational Science and Its Applications - ICCSA 2004 - International Conference, Proceedings
PB - Springer Verlag
T2 - International Conference on Computational Science and Its Applications, ICCSA 2004
Y2 - 14 May 2004 through 17 May 2004
ER -