ERCIM News No.35 - October 1998

Intelligent Event Notification based on Active Database and Fuzzy Triggers

by Antoni Wolski

A new breed of active databases incorporates soft reasoning about the data state. The technology may be utilized to help the operators of large industrial installations to detect complex and, potentially, hazardous conditions in a process. The RapidBase-S intelligent database system incorporating history database, temporal triggers and fuzzy rules was developed at VTT Information Technology (Espoo, Finland).

In industrial process management systems like those used, for example, in control rooms of power stations and chemical plants, vast amounts of measurement data are being collected and analysed. The sheer magnitude of the data flux - reaching thousands of measurements per second - is a challenge for a real-time process management system. If, additionally, condition testing or reasoning has to be performed on the data, most existing techniques do not perform adequately in real-life situations. In traditional rule-based system, large data sets, especially when they are formed as time series cause performance problems. Utilizing traditional databases is to no avail because they are too slow for the data acquisition, do not accommodate time series, and require the management applications to poll the database continuously, leading to performance problems again.

The solution we are proposing in our SENSE project is an intelligent active database system built to handle efficiently time series data and to reason therefrom. Instead of having rules outside of the database, we are putting them into the database in the form of crisp and fuzzy triggers. Because rules are precompiled at the moment of creation, the rule system can run the rules and access the process data with unprecedented speed, without the need to cross the external database interface boundary. For example, in our current implementation we are able run even a thousand database-initiated fuzzy rule set executions per second, in a typical Intel-based PC equipment.

Essential concepts of the RapidBase data model

We have developed a system called RapidBase-S which contains all the necessary components of an intelligent active database. Its central part is a main-memory-based database engine supporting an extended relational-time-series data model. The model is based on the traditional relational data model, with the addition of a new column type: a history column. A value of a history column is a time series of history records, as illustrated in the figure. Thus any attribute or a set of attributes of a real-life object may be defined as having only a current (snapshot) value or a temporal (time series) value.

A model based on the relational model has the advantage that the data can be naturally manipulated through the current view which corresponds to a traditional relational table showing only the latest data. Standard SQL statements may be used to do that. For example, in order to add a new record to a time series, only a standard UPDATE statement is required. It changes the state of the current view according to the SQL semantics but, in the same time, it has an effect of appending a record to a history.
The time travel through a history is possible using extended syntax.

The trigger engine is responsible for the active behaviour of the system. Various triggers may be defined at run-time, including temporal ones. For example, it is possible to define the rule: ”when the value of the data point A has been above the alarm limit L for more then 10 minutes, then do ... “

More precisely, trigger definitions are expressed in the form of CREATE TRIGGER statements of an SQL-based definition language. In a true spirit of contemporary databases, triggers may be defined and modified at run-time.

The basic form of a trigger includes a regular Boolean crisp predicate evaluated over the whole database. We have also introduced several ways to introduce reasoning to trigger condition evaluation. Fuzzy rule sets are used as a basic unit of imprecise reasoning. For example, using fuzzy rules, fuzzy set quantifiers and fuzzy temporal restrictors, it is possible to express a rule like this: ”when most pump motors have been slightly overheated for few minutes, then do ... “

Several pilot trials of RapidBase-S are under preparation. They involve industries like cellulose pulp production industrial drive systems and telecommunications systems.

More information about this and other projects on industrial database technology is at: /projects/industrialdb/

Please contact:

Antoni Wolski - VTT Information Technology
Tel: +358 9 456 6012

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