Traffic Forecasting and Planning of WiMAX under Multiple Priority Using Fuzzy Time Series Analysis ()
ABSTRACT
Network traffic prediction plays a
fundamental role in characterizing the network performance and it is of
significant interests in many network applications, such as admission control or
network management. Therefore, The main idea behind this work, is the
development of a WIMAX Traffic Forecasting System for predicting traffic time
series based on the daily and monthly traffic data recorded (TRD) with
association of feed forward multi-layer perceptron (FFMLP). The quality of
forecasting WIMAX Traffic obtained by comparing different configurations of the
FFMLP that consist of investigating different FFMLP model architectures and
different Learning Algorithms. The decision of changing the FFMLP architecture
is essentially based on prediction results to obtain the FFMLP model for flow
traffic prediction model. The different configurations were tested using daily
and monthly real traffic data recorded at each of the two base stations (A and
B) that belongs to a Libyan WiMAX Network. We evaluate our approach with
statistical measurement and a good statistic measure of FMLP indicates the
performance of selected neural network configuration. The developed system
indicates promising results in which it successfully network traffic prediction
through daily and monthly traffic data recorded (TRD) association with
artificial neural network.
Share and Cite:
Abdullah, I. , Daw, D. and Seman, K. (2015) Traffic Forecasting and Planning of WiMAX under Multiple Priority Using Fuzzy Time Series Analysis.
Journal of Applied Mathematics and Physics,
3, 68-74. doi:
10.4236/jamp.2015.31009.