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Integration of QoS Metrics, Rules and Semantic Uplift for Advanced IPTV Monitoring
TSSG, Waterford Institute of Technology, Waterford, Ireland.ORCID iD: 0000-0002-3912-1470
University College Dublin.
Trinity College Dublin.
Trinity College Dublin.
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2014 (English)In: Journal of Network and Systems Management, ISSN 1573-7705, Vol. 23, no 3, 1-36 p.Article in journal (Refereed) Published
Abstract [en]

Increasing and variable traffic demands due to triple play services pose significant Internet Protocol Television (IPTV) resource management challenges for service providers. Managing subscriber expectations via consolidated IPTV quality reporting will play a crucial role in guaranteeing return-on-investment for players in the increasingly competitive IPTV delivery ecosystem. We propose a fault diagnosis and problem isolation solution that addresses the IPTV monitoring challenge and recommends problem-specific remedial action. IPTV delivery-specific metrics are collected at various points in the delivery topology, the residential gateway and the Digital Subscriber Line Access Multiplexer through to the video Head-End. They are then pre-processed using new metric rules. A semantic uplift engine takes these raw metric logs; it then transforms them into World Wide Web Consortium’s standard Resource Description Framework for knowledge representation and annotates them with expert knowledge from the IPTV domain. This system is then integrated with a monitoring visualization framework that displays monitoring events, alarms, and recommends solutions. A suite of IPTV fault scenarios is presented and used to evaluate the feasibility of the solution. We demonstrate that professional service providers can provide timely reports on the quality of IPTV service delivery using this system.

Place, publisher, year, edition, pages
Springer, 2014. Vol. 23, no 3, 1-36 p.
Keyword [en]
Network and system monitoring, Measures, Quality of Service, IPTV Monitoring, Semantic uplift
National Category
Communication Systems Computer Systems
Research subject
Computer Science
URN: urn:nbn:se:kth:diva-173810DOI: 10.1007/s10922-014-9313-9ISI: 000356295800010ScopusID: 2-s2.0-84931270827OAI: diva2:854987

QC 20150921

Available from: 2015-09-18 Created: 2015-09-18 Last updated: 2016-03-07Bibliographically approved

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de Fréin, Ruairí
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