Supporting mobile payment QOS by data mining GSM network traffic

Authors:
Edison Lai;Simon Fong;Yang Hang
Affiliations:
University of Macau, Macao SAR, China;University of Macau, Macao SAR, China;University of Macau, Macao SAR, China
Venue:
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
Year:
2008

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Abstract

In mobile commerce, short-message-service (SMS) is an important technique for delivering payment instruction. A payment model "SMS Credit" was proposed earlier [1]. Such payment service or similar relies on the transmission of SMS; it is needed to reduce the occurrence of packet losses and delay, to improve the quality of packet transmission services (QOS) in the network. This paper discusses how the payment service operates in a configurable radio resource environment via data mining. A Radio Resource Management and Prediction Server equipped with data mining algorithms will optimize the radio resources for both voice and data services in order to provide an optimized QOS. Specifically, data mining techniques are applied to define traffic policy and to calculate optimization result through traffic profile analysis.