Adaptive sampling in measuring traffic parameters in a computer network using a fuzzy regulator and a neural network

Authors:
J. Giertl;J. Baca;F. Jakab;R. Andoga
Affiliations:
Technical university, Kosice, Slovakia;Technical university, Kosice, Slovakia;Technical university, Kosice, Slovakia;Technical university, Kosice, Slovakia
Venue:
Cybernetics and Systems Analysis
Year:
2008

Citing 2
Cited 2

Self-organizing maps

Self-organizing maps
Adaptive Sampling for Network Management

Journal of Network and Systems Management

Improving network measurement efficiency through multiadaptive sampling

TMA'12 Proceedings of the 4th international conference on Traffic Monitoring and Analysis
A multiadaptive sampling technique for cost-effective network measurements

Computer Networks: The International Journal of Computer and Telecommunications Networking

Quantified Score

Hi-index	0.00

Visualization

Abstract

Adaptive sampling using a neural network and a fuzzy regulator is described as applied to computer network traffics. The objective of this approach is to maximally reduce the amount of data to be processed with preservation of acceptable measurement accuracy. The results of experimental verification of sampling efficiency are also presented that are based on the traffic data archive of a real computer network.