Adaptive Data Stream Management System Using Learning Automata
In many modern applications, data are received as infinite, rapid, unpredictable and time-variant data elements that are known as data streams. Systems which are able to process data streams with such properties are called Data Stream Management Systems (DSMS). Due to the unpredictable and time-variant properties of data streams as well as system, adaptivity of the DSMS is a major requirement for each DSMS. Accordingly, determining parameters which are effective on the most important performance metric of a DSMS (i.e., response time) and analyzing them will affect on designing an adaptive DSMS.