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Sensors 2017, 17(4), 731; doi:10.3390/s17040731

Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks

Group of Analysis, Security and Systems (GASS), Department of Software Engineering and Artificial Intelligence (DISIA), Faculty of Information Technology and Computer Science, Office 431, Universidad Complutense de Madrid (UCM), Calle Profesor José García Santesmases, 9, Ciudad Universitaria, 28040 Madrid, Spain
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Received: 27 December 2016 / Revised: 28 March 2017 / Accepted: 29 March 2017 / Published: 31 March 2017
(This article belongs to the Special Issue Advances on Resources Management for Multi-Platform Infrastructures)

Abstract

This paper presents the Monitoring and Discovery Framework of the Self-Organized Network Management in Virtualized and Software Defined Networks SELFNET project. This design takes into account the scalability and flexibility requirements needed by 5G infrastructures. In this context, the present framework focuses on gathering and storing the information (low-level metrics) related to physical and virtual devices, cloud environments, flow metrics, SDN traffic and sensors. Similarly, it provides the monitoring data as a generic information source in order to allow the correlation and aggregation tasks. Our design enables the collection and storing of information provided by all the underlying SELFNET sublayers, including the dynamically onboarded and instantiated SDN/NFV Apps, also known as SELFNET sensors. View Full-Text
Keywords: 5G; Monitoring; NFV; SDN 5G; Monitoring; NFV; SDN
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Caraguay, Á.L.V.; Villalba, L.J.G. Monitoring and Discovery for Self-Organized Network Management in Virtualized and Software Defined Networks. Sensors 2017, 17, 731.

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