DSMS scheduling regarding complex QoS metrics

In data stream management systems (DSMSs), data do not appear in the form of persistent relations, but rather arrives in multiple, continuous, rapid, time-varying streams. Achieving a good performance in these systems is still the main challenge. Minimizing run-time memory usage and response time are the most important performance issues. Choosing a better scheduling algorithm implies a better performance. Variety of schedulers and customized quality of service (QoS) metrics (related to the amount of user´s satisfaction), motivated us to find an approach for choosing the best scheduler per case. In this paper, a new static periodic scheduler called meta-scheduler is proposed. Our concentration is on non-real-time DSMSs dealing with semi-regular streams (not too bursty) using complex QoS metrics. We have used coloured Petri net models to choose the best scheduling algorithm for each period regarding complex QoS metrics and varying system statistics. We have studied our scheduler in the context of our new DSMS prototype. Finally, we showed that how meta-scheduler outperforms simple schedulers when a user defines a complex QoS metric.