Network Traffic Prediction and Applications Based on Time Series Model

Authors:
Jun Lv;Xing Li;Tong Li
Affiliations:
The Academy of Armored Force Engineering, Beijing, China;China Education and Research Network, Tsinghua University,;The Academy of Armored Force Engineering, Beijing, China
Venue:
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
Year:
2009

Citing 4
Cited 0

On the self-similar nature of Ethernet traffic (extended version)

IEEE/ACM Transactions on Networking (TON)
Wide-area traffic: the failure of Poisson modeling

SIGCOMM '94 Proceedings of the conference on Communications architectures, protocols and applications
Adaptive filter theory (3rd ed.)

Adaptive filter theory (3rd ed.)
Fast, approximate synthesis of fractional Gaussian noise for generating self-similar network traffic

ACM SIGCOMM Computer Communication Review

Quantified Score

Hi-index	0.00

Visualization

Abstract

Network traffic prediction is a very complex and difficult issue in the network management and design. This paper shows a model with a new algorithm (MLSL), and the model parameters can be modified by the new algorithm, which improves the adaptive ability of the model and makes the model adaptive function. Simulation and actual network traffic data experiment has proved that this algorithm has the advantage of high prediction accuracy and fast convergence, and its computing complexity is lower than other related algorithms.