3rd National Conference on Computer, Information Technology and Application of Artificial Intelligence , 2020-02-05

Title : ( Improving the Statistical Information Collection Overhead in Software Defined Networks )

Authors: Nemat Allah Biabani , Seyed Amin Hosseini Seno ,

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Abstract

the collection of statistical information in software defined networks is vital for network management. Collection of information from a network causes traffic and processing overheads in nodes and controllers. Despite the substantial importance of information collection, it is known as the monitoring overhead. Numerous studies have also been carried out to reduce the monitoring overhead and use the network potential for the transmission of user information. One of the important overhead reduction solutions determines the selection of a set of nodes and the information fetched from each node. In this paper, the genetic algorithm and Boolean algebra is used to propose a solution for the more effective node selection. This solution also helps identify the flows to fetch the statistical information from each node. The results of analyses were reported, the statistical information overlap was eliminated, and the traffic and communication overhead was reduced.

Keywords

, component; software defined network, traffic statistics, network monitoring, software defined measurement
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@inproceedings{paperid:1078702,
author = {Biabani, Nemat Allah and Hosseini Seno, Seyed Amin},
title = {Improving the Statistical Information Collection Overhead in Software Defined Networks},
booktitle = {3rd National Conference on Computer, Information Technology and Application of Artificial Intelligence},
year = {2020},
location = {اهواز, IRAN},
keywords = {component; software defined network; traffic statistics; network monitoring; software defined measurement},
}

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%0 Conference Proceedings
%T Improving the Statistical Information Collection Overhead in Software Defined Networks
%A Biabani, Nemat Allah
%A Hosseini Seno, Seyed Amin
%J 3rd National Conference on Computer, Information Technology and Application of Artificial Intelligence
%D 2020

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