Notification of data-stream events in Publish/Subscribe systems using fuzzy matching

Abstract

Data streams are vast sources of information. In such streams only certain episodic points called events are interesting. The number of events occurring in a data stream can be very large, and a given user would not be interested in all of them. Thus, there is a need to selectively disseminate information about the occurrence of events to users who express interest in them. Publish/Subscribe is a distributed paradigm of messaging in which events published by publishers are automatically sent to subscribers who have expressed interest in them. In this work, we apply the publish/subscribe paradigm to notify a user when an event of interest occurs. Furthermore, user subscriptions may often be vague and non-specific. To capture this uncertainty, we use fuzzy set theory in the modeling of the subscriptions. The use of fuzzy sets gives a user more expressive power in subscriptions and gives better notifications of events.