Priority assignment in realtime active databases Active databases and realtime databases have been important areas of research in the recent past. It has been recognized that many benefits can be gained by integrating realtime and active database technologies. However, not much work has been done in the area of transaction processing in realtime active databases. This paper deals with an important aspect of transaction processing in realtime active databases, namely the problem of assigning priorities to transactions. In these systems, timeconstrained transactions trigger other transactions during their execution. We present three policies for assigning priorities to parent, immediate and deferred transactions executing on a multiprocessor system and then evaluate the policies through simulation. The policies use different amounts of semantic information about transactions to assign the priorities. The simulator has been validated against the results of earlier published studies. We conducted experiments in three settings: a task setting, a main memory database setting and a diskresident database setting. Our results demonstrate that dynamically changing the priorities of transactions, depending on their behavior (triggering rules), yields a substantial improvement in the number of triggering transactions that meet their deadline in all three settings.

Schedulability analysis of dependent probabilistic realtime tasks The complexity of modern architectures has increased the timing variability of programs (or tasks). In this context, new approaches based on probabilistic methods are proposed to decrease the pessimism by associating probabilities to the worst case values of the programs (tasks) time execution. In this paper, we extend the original work of Chetto et al. 7 on precedence constrained tasks to the case of tasks with worst case execution times described by probability distributions. The precedence constraints between tasks are defined by acyclic directed graphs and these constraints are transformed in appropriate release times and deadlines. The new release times and deadlines are built using new maximum and minimum relations between pairs of probability distributions. We provide a probabilistic schedulability condition based on these new relations.