Research Of The Scheduling Algorithms Of Periodic Transaction Set In Real-Time Database System

The decisive performance of real-time database systems is to maximize the number of scheduled transactions that completed before their deadlines, so it is essential to schedule the transactions in supporting time-critical applications. The transaction's real-time scheduling policies are the key factor to judge the RTDBS performance. However, the traditional certainty scheduling algorithms are not enough for prior-time applications, and it also does not support the situation that so few transactions in probability can miss their deadlines. Using the More-Less method to guarantee the objects updated by the transactions to be consistency is common usage nowadays. But the increased system resource utilization is made by the pessimistic way to use the worst-case computing time to schedule the transaction jobs, and the reduction in the number of scheduled transaction jobs which can satisfy the condition of their deadline constraints, eventually the decline in system performance is led. Therefore, in order to optimize the system performance, a new approach should be provided to support the temporal consistency for the objects and the scheduled-feature for transactions, while the minimum system resource utilization is also hoped in the processes of the transactions being scheduled.In this paper, the time features of the updating transaction and real-time data of the RTDBS are discussed firstly, the real-time data correctness definition is present. Firstly, the traditional certainty scheduling algorithms of the updating transactions are analyzed and compared each other. Based on these studies, a way by deferring the job release time of updating transactions is studied carefully for optimizing the utilization of system resource. Secondly, the temporal relationship between the release time and the relative deadline in the schedued process is discussed. Thirdly, an uncertainty method based on probability statistic is introduced into the soft and solid real-time systems. After that, a new method is improved by putting the probability statistic theory into the original deferrable scheduling algorithms under the condition that the real-time data consistency is ensured, while the optimal resource utilization and the required QOS of the updating transactions can be satisfied in this method. Finally, both the experiment theory and results show that this method can show better system performance.