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Towards the improvement of diagnostic metrics Fault diagnosis for DSL-Based IPTV networks using the Rényi entropy

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Publication date3/12/2012
Host publication2012 IEEE Global Communications Conference (GLOBECOM)
PublisherIEEE
Pages2779-2784
Number of pages6
ISBN (electronic)9781467309219
ISBN (print)9781467309202
<mark>Original language</mark>English
EventIEEE Global Communications Conference (GLOBECOM) - Anaheim, Canada
Duration: 3/12/20127/12/2012

Conference

ConferenceIEEE Global Communications Conference (GLOBECOM)
Country/TerritoryCanada
Period3/12/127/12/12

Publication series

Name2012 IEEE Global Communications Conference
PublisherIEEE
ISSN (Print)1930-529X

Conference

ConferenceIEEE Global Communications Conference (GLOBECOM)
Country/TerritoryCanada
Period3/12/127/12/12

Abstract

IPTV networks blindly rely on the adequate operation and management of the underlying infrastructure that in numerous cases is threaten by unexpected anomalous events which consequently cause QoS degradation to the end-user. Thus, it is of great importance to deploy techniques embodied with diagnostic and self-protection metrics for determining and predicting the arrival of such events in order to proactively charge defense mechanisms without the need of an exhaustive manual inspection by the network operator. In this paper we propose and demonstrate the applicability of the Rényi entropy as a useful diagnosis feature for explicitly characterizing DSL-level anomalies issued in an IPTV network of a large European ISP. It is revealed that different orders of the Rényi entropy can formulate meaningful detection and categorization of phenomena occurring on specific Digital Subscriber Line Access Multiplexers (DSLAMs) within the DSL infrastructure. Via the synergistic exploitation of the local maxima peaks generated by each Rényi-based distribution we exhibit the feasibility to extract and identify lightweight anomalies that under simple metrics cannot be detected.