TY - GEN
T1 - QoS-predictions service
T2 - OTM 2006 Workshops - OTM Confederated International Workshops
AU - Wac, Katarzyna
AU - Van Halteren, Aart
AU - Konstantas, Dimitri
PY - 2006/1/1
Y1 - 2006/1/1
N2 - Today's mobile data 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 offered by the underlying networks. As the services operate in a heterogeneous networking environment, we argue that the generic information about the networks' offered-QoS may enable an anyhow mobile service delivery based on an intelligent (proactive) selection of 'any' network available in the user's context (location and time). Towards this direction, we develop a QoS-predictions service provider, which includes functionality for the acquisition of generic offered-QoS information and which, via a multidimensional processing and history-based reasoning, will provide predictions of the expected offered-QoS in a reliable and timely manner. We acquire the generic QoS-information from distributed mobile services' components quantitatively (actively and passively) measuring the application-level QoS, while the reasoning is based on statistical data mining and pattern recognition techniques.
AB - Today's mobile data 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 offered by the underlying networks. As the services operate in a heterogeneous networking environment, we argue that the generic information about the networks' offered-QoS may enable an anyhow mobile service delivery based on an intelligent (proactive) selection of 'any' network available in the user's context (location and time). Towards this direction, we develop a QoS-predictions service provider, which includes functionality for the acquisition of generic offered-QoS information and which, via a multidimensional processing and history-based reasoning, will provide predictions of the expected offered-QoS in a reliable and timely manner. We acquire the generic QoS-information from distributed mobile services' components quantitatively (actively and passively) measuring the application-level QoS, while the reasoning is based on statistical data mining and pattern recognition techniques.
UR - http://www.scopus.com/inward/record.url?scp=33845413676&partnerID=8YFLogxK
M3 - Article in proceedings
AN - SCOPUS:33845413676
SN - 3540482733
SN - 9783540482734
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 1924
EP - 1933
BT - On the Move to Meaningful Internet Systems 2006
PB - Springer Verlag
Y2 - 29 October 2006 through 3 November 2006
ER -