Automated Source Code Extension for Debugging of OpenFlow based Networks

Hommes, Stefan; Hermann, Frank; State, Radu; Engel, Thomas

Reference : Automated Source Code Extension for Debugging of OpenFlow based Networks


	Document type :	Scientific congresses, symposiums and conference proceedings : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science
	To cite this reference:	http://hdl.handle.net/10993/9539

Title :	Automated Source Code Extension for Debugging of OpenFlow based Networks
Language :	English
Author, co-author :	Hommes, Stefan [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Hermann, Frank [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	State, Radu [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
	Engel, Thomas [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Publication date :	Oct-2013
Main document title :	Proc. 9th International Conference on Network and Service Management (CNSM)
Pages :	105-108
Peer reviewed :	Yes
ISBN :	978-3-901882-53-1
Event name :	9th International Conference on Network and Service Management (CNSM)
Event date :	from 14-10-2013 to 18-10-2013
Keywords :	[en] OpenFlow ; debugging
Abstract :	[en] Software-Defined Networks using OpenFlow have to provide a reliable way to to detect network faults in operational environments. Since the functionality of such networks is mainly based on the installed software, tools are required in order to determine software bugs. Moreover, network debugging might be necessary in order to detect faults that occurred on the network devices. To determine such activities, existing controller programs must be extended with the relevant functionality. In this paper we propose a framework that can modify controller programs transparently by using graph transformation, making possible online fault management through logging of network parameters in a NoSQL database. Latter acts as a storage system for flow entries and respective parameters, that can be leveraged to detect network anomalies or to perform forensic analysis.
Permalink :	http://hdl.handle.net/10993/9539

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