Scheduling transactions with temporal constraints: exploiting data semantics

Abstract

In this paper, issues involved in the design of a real-time database which maintains data temporal consistency are discussed. The concept of data-deadline is introduced and time cognizant non-waiting transaction scheduling policies are proposed. Further, two time cognizant forced wait policies which improve performance significantly by forcing a transaction to delay further execution until a new version of sensor data becomes available are proposed. A way to exploit temporal data similarity to improve performance is also proposed. Finally, these policies are evaluated through detailed simulation experiments. The simulation results show that taking advantage of temporal data semantics in transaction scheduling can significantly improve the performance of user transactions in real-time database systems. In particular, it is demonstrated that under the forced wait policy, the performance can be improved significantly. Further improvements result by exploiting data similarity.