Sasa Tomic

Satisfying timing constraints of real-time databases

Abstract A real-time database has deadlines for processing transactions. Approximate query processing (AQP) has been presented as a strategy to satisfy these timing constraints by providing approximate answers to queries at the deadline instead of missing deadlines. In order to produce approximate answers, semantic information is maintained about the database and a computational overhead is required. In this paper the performance of AQP is examined to determine its effect on satisfying the timing constraints of real-time databases. Query and update transactions are modeled as periodic tasks with hard deadlines. A lock-based concurrency control is used and the effect of workload characteristics, such as the scheduling algorithm, the number of transactions and the percentage of update transactions, are examined. We compare the number of missed deadlines and approximate answers produced during AQP to the number of missed deadlines occurring during traditional query processing (TQP). Results demonstrate that despite the overhead, fewer deadlines are missed during approximate query processing than during TQP.

Satisfying temporal consistency constraints of real-time databases

Abstract In addition to timing constraints, a real-time database has temporal consistency constraints for its temporal data. The temporal consistency constraints require the data to represent a state of the real-world that is up-to-date and also require data to represent past states of the real-world with values that are close in time. Factors, such as concurrency control, can cause transactions to miss their deadlines and data to become temporally inconsistent. Approximate query processing (AQP) has been proposed as a strategy to satisfy the timing constraints of real-time databases. Approximate answers are provided by AQP if it is not possible to produce an exact answer by a specified deadline. In this paper, we examine the temporal consistency of the data during traditional and AQP. Four metrics of temporal consistency are utilized to compare the age and dispersion of the data during traditional query processing (TQP) versus approximate query processing. Simulation results identify factors, such as the concurrency control algorithm, the number of transactions and the percentage of query transactions, that affect the temporal inconsistency of the data.

Concurrency Control for Approximate Query Processing of Real-Time Database Systems

Real-time database systems [2, 8] can have timing constraints in the form of deadlines for the processing of database transactions. It is not always possible for real-time database systems to meet deadlines. A network partition or a host failure can cause some needed data to become inaccessible. Similarly, database transactions in a real-time system can share data, and while con-currency control is needed to ensure data integrity, concurrency control can cause transactions to miss their deadlines. For many real-time systems, such as computer integrated manufacturing, air traffic control systems and reservoir operation control, producing an approximate answer to a database query by a deadline is more useful than waiting for an exact answer and missing the deadline. Approximate query processing [14, 16] satisfies the timing constraints of real-time databases by providing approximate answers, instead of missing deadlines.