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Representative Measurement Point Selection to Monitor Software-defined Networks

Key:HGK+18
Author:Rhaban Hark, Mohamed Ghanmi, Sounak Kar, Nils Richerzhagen, Amr Rizk, Ralf Steinmetz
Date:October 2018
Kind:In proceedings - use for conference & workshop papers
Publisher:IEEE
Organization:IEEE
Address:Chicago, USA
Book title:The 43nd IEEE Conference on Local Computer Networks (LCN)
Pages:1-8
Language:english
Keywords:monitor placement, software-defined networking, flow size distribution
Number of characters:49000
Research Area(s):Peer-to-Peer Networking
Abstract:Network state monitoring is a fundamental task for network management. However, determining the full network state in Software defined Networks requires disproportionately too many resources. This stems from the discrepancy between the established methods used for state monitoring compared to the varying contribution in terms of information obtained from every additionally monitored network node. This relationship may even become more complicated depending on the network state information of interest. One solution to overcome bottlenecks by reducing the overall monitoring footprint is the use of spatial sampling, which allows the estimation of the network state based a fraction of the overall state. In this work, we propose schemes to place a small number of measurement points in the SDN network to maximize the obtained network state information. Considering different conditions, we utilize routing information and graph theoretic centrality metrics, respectively, to estimate the amount of information a node provides. Based on this knowledge, we, furthermore develop a mechanism to place multiple measurement points while avoiding redundant measurements. For demonstration purpose, we use the developed mechanisms to estimate the Flow Size Distribution in SDN environments. An emulative evaluation taking several known topologies shows the effectiveness of spatial sampling using the proposed scheme.
URL:https://www.ieeelcn.org/Program_technical.html
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