Management of QoS and data freshness in RTDBSs using feedback control scheduling and data versions

These recent years, a lot of real-time applications are becoming increasingly sophisticated in their data needs, resulting in a greater demand for real-time data services. Real-time database systems (RTDBS) can manage these applications, but the workload in these systems is unpredictable, then RTDBS may become overloaded. A lot of work dealing with quality of service (QoS) has been done to control the transient overshoot. They are based on feedback control real-time scheduling theory. In this paper, we propose a work which allows to execute transactions before their deadlines while using the fresh data. We have extended the feedback-based miss ratio control, by using a multi versions data architecture to guarantee a set of requirements on the behavior of RTDBS and we have considered two data management policies. In the first policy, we have limited the maximum number of data versions and this number is the same for all the data items. In the second policy, the number is dynamically adjusted for each data item.