Volume 11, Issue 2 (June 2015)                   IJEEE 2015, 11(2): 101-108 | Back to browse issues page


XML Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Farabi F, Mosavi M R, Karami S. Optimal Choice of Random Variables in D-ITG Traffic Generating Tool using Evolutionary Algorithms. IJEEE 2015; 11 (2) :101-108
URL: http://ijeee.iust.ac.ir/article-1-692-en.html
Abstract:   (5637 Views)

Impressive development of computer networks has been required precise evaluation of efficiency of these networks for users and especially internet service providers. Considering the extent of these networks, there has been numerous factors affecting their performance and thoroughly investigation of these networks needs evaluation of the effective parameters by using suitable tools. There are several tools to measure network's performance which evaluate and analyze the parameters affecting the performance of the network. D-ITG traffic generator and measuring tool is one of the efficient tools in this field with significant advantages over other tools. One of D-ITG drawbacks is the need to determine input parameters by user in which the procedure of determining the input variables would have an important role on the results. So, introducing an automatic method to determine the input parameters considering the characteristics of the network to be tested would be a great improvement in the application of this tool. In this paper, an efficient method has been proposed to determine optimal input variables applying evolutionary algorithms. Then, automatic D-ITG tool operation would be studied. The results indicate that these algorithms effectively determine the optimal input variables which significantly improve the D-ITG application.

AWT IMAGE

Full-Text [PDF 573 kb]   (3151 Downloads)    
Type of Study: Research Paper | Subject: Internet Engineering
Received: 2014/04/25 | Revised: 2016/04/24 | Accepted: 2015/06/27

Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Creative Commons License
© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.