Algorithm Development for Measurement and Prediction the Traffic in Broad Band Integrated Service Networks

Abstract

Problem statement: In this study an effort had been made to develop an algorithm for traffic prediction and measurement for a wide use networks such as B-ISDN. Such algorithm should base on valuable parameters during the various stages of data elements transmission. The offered algorithm was expected to enforce the main sources of congestion problem in network. With this technique the admission decision is made according to the prediction of a few quality of service parameters expected for the new connections. Approach: This research aimed to find out the suitable method for improving the performance and the quality of service during the real time work in wide used networks now days. The improvement of quality of services in B-ISDN can be achieved by a significant estimation of the network state and discovering the most critical situation during the work time. The most repeated problems in such networks are loses of connection, delay time and saturation of communication lines. These problems are known and some solution could be sufficient to deal with, but not for a long time. Results: The proposed solution was based on the need of traffic prediction method in real time to determine the state of network and decide how to deal with. Such method should base on finding the most significant parameters in network during the real time work and use them as prediction variable to predict the situation or the state of network in the future time and then take the appropriate action. Suffering from permanent problems finding the most significant parameters, which can be estimated at the real time to help for solving a raw problems which encountered during the work in networks such as saturation, bottleneck, disconnecting and time delay. Conclusion: The results which achieved by this research was based on the developed algorithm which can be used to predict the traffic in B-ISDN, optimizing the bandwidth and making the bandwidth available to the behaving sources under congestion situation and also when there is no congestion. Meet the QoS demands of the network traffic during congestion situation and also when there is no congestion. Reject/drop all the packets. First guideline for future study in this direction is investigation additional objective functions, such as bandwidth limitation for archive more general results.