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 transaction scheduling policies are proposed. Informally, data-deadline is a deadline assigned to a transaction due to the temporal constraints of the data accessed by the transaction. 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 realtime 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.

A crucial consideration in environments where data is broadcast to clients is the low bandwidth available for clients to communicate with servers. Advanced applications in such environments do need to read data that is mutually consistent as well as current. However, given the asymmetric communication capabilities and the needs of clients in mobile environments, traditional serializability-based approaches are too restrictive, unnecessary, and impractical. We thus propose the use of a weaker correctness criterion called update consistency and outline mechanisms based on this criterion that ensure (1) the mutual consistency of data maintained by the server and read by clients, and (2) the currency of data read by clients. Using these mechanisms, clients can obtain data that is current and mutually consistent “off the air”, i.e., without contacting the server to, say, obtain locks. Experimental results show a substantial reduction in response times as compared to existing (serializability-based) approaches. A further attractive feature of the approach is that if caching is possible at a client, weaker forms of currency can be obtained while still satisfying the mutual consistency of data.

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.