Cover
Vol. 9 No. 2 (2013)

Published: December 31, 2013

Pages: 48-57

Original Article

A Modified Wavenet-Based Link Status Predictor for Computer Networks

Jassim M. Abdul-Jabbar 1 Omar A. Hazim
1Computer Engineering Department, College of Engineering, University of Mosul, Mosul, Iraq.
History
  • Received: October 31, 2013
  • Available Online: December 31, 2013
DOI

https://doi.org/10.37917/ijeee.9.2.2

Abstract

In this paper, a modified wavelet neural network (WNN) (or wavenet)-based predictor is introduced to predict link status (congestion with load indication) of each link in the computer network. On the contrary of previous wavenet-based predictors, the proposed modified wavenet-based link state predictor (MWBLSP) generates two indicating outputs for congestion and load status of each link based on th e premeasured power burden (square values) of utilization on each link in the previous time intervals. Fortunately, WNNs possess all learning and generalization capabilities of traditional neural networks. In addition, the ability of such WNNs are efficiently enhanced by the local characteristics of wavelet functions to deal with sudden changes and burst network load. The use of power burden utilization at the predictor input supports some non-linear distri butions of the predicted values in a more efficient manner. The proposed MWBLSP pre dictor can be used in the context of active congestion control and link load balancing techniques to improve the performance of all links in the network with best utilization of network resources.

Keywords

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