Schlüsselwörter
(Englisch)
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Traffic Monitoring; Traffic Analysis; QoS prediction; QoE; Geo-localisation; mobile services; wireless networks
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Forschungsprogramme
(Englisch)
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COST-Action IC0703 - Traffic Monitoring and Analysis: theory, techniques, tools and applications for the future networks
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Kurzbeschreibung
(Englisch)
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Today's mobile services and applications aspire to deliver services to a user anywhere - anytime while fulfilling his Quality of Service (QoS) requirements. However, the success of the service delivery heavily relies on the QoS provided by the underlying wireless networks. As the mobile services operate in a heterogeneous networking environment including wireless (access) and wired (core) networks, precise and in-advance knowledge of the real (i.e. user-observed, application-level) QoS is required by the service for the optimization of the service quality and user experience. This optimization can be achieved via an intelligent (i.e. proactive) selection of suitable wireless network as available in the user's context (location and time) or via the application adaptation. Towards this direction, we are working on the definition of Traffic Monitoring and Analysis techniques and tools in heterogeneous networking environment towards the design and development of a QoS-prediction service. This service will be based on multidimensional processing and history-based reasoning on QoS- information collected by the users' applications and will provide predictions of the expected wireless networks' provided-QoS in a reliable and timely manner. We acquire the generic QoS-information from distributed mobile applications components quantitatively (actively and passively) measuring the application-level QoS, while the reasoning upon this information is based on statistical data mining and pattern recognition techniques. Our proposed solution constitutes a collaborative service between mobile users, who share their application-level QoS information to enrich the QoS-Predictions Service. Therefore the proposed solution neither requires nor it is based on any internal knowledge of infrastructures of wireless network operators.
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Weitere Hinweise und Angaben
(Englisch)
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Full name of research-institution/enterprise: Université de Genève Centre Universitaire d'Informatique, Faculty of Social and Economic Sciences Battelle, Bât. A
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Partner und Internationale Organisationen
(Englisch)
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AT, BE, BG, CH, CY, DE, DK, ES, FI, FR, GR, HR, HU, IE, IL, IT, NL, NO, PL, PT, SE, UK
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Abstract
(Englisch)
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Today's mobile services and applications aspire to deliver services to a user anywhere - anytime while fulfilling his Quality of Service (QoS) requirements. However, the success of the service delivery heavily relies on the QoS provided by the underlying wireless networks. As the mobile services operate in a heterogeneous networking environment including wireless (access) and wired (core) networks, precise and in-advance knowledge of the real (i.e., user-observed, application-level) QoS is required by the service for the optimization of the service quality and user's quality of experience (QoE). This optimization can be achieved via an intelligent (i.e., proactive) selection of suitable wireless access network as available in the user's context (location and time) or via the application adaptation. Towards this direction, we are researching definition of a Traffic Monitoring and Analysis techniques and tools in heterogeneous networking environment towards development of the QoS-Prediction Service. This service will be based on multi-dimensional processing and history-based reasoning on QoS- information collected by the user's applications and will provide predictions of the expected wireless access network's provided-QoS in a reliable and timely manner. We acquire the generic QoS-information from distributed mobile application's components quantitatively (actively and passively) measuring the application-level QoS, while the reasoning upon this information is based on statistical data mining and pattern recognition techniques. Our proposed solution constitutes a collaborative service between mobile users, who share their application-level QoS information to enrich the QoS-Predictions Service. Therefore the proposed solution neither requires nor it is based on any internal knowledge of infrastructures of wireless network operators.
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Datenbankreferenzen
(Englisch)
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Swiss Database: COST-DB of the State Secretariat for Education and Research Hallwylstrasse 4 CH-3003 Berne, Switzerland Tel. +41 31 322 74 82 Swiss Project-Number: C08.0025
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