Quality of service guarantee for temporal consistency of real-time transactions

The More-Less (ML) scheme has been shown to be an efficient approach for maintaining temporal consistency of real-time data objects. Although ML provides a deterministic guarantee in temporal consistency, the number of update transactions that can be supported in a system is limited. This is due to its use of the worst-case computation time in deriving deadlines and periods of update transactions. This paper studies the problem of temporal consistency maintenance where a certain degree of temporal inconsistency is tolerable. A suite of Statistical More-Less (SML) approaches are proposed to explore the trade-off between quality of service (QoS) of temporal consistency and the number of supported transactions. It begins with a base-line algorithm, SML-BA, which provides the requested QoS of temporal consistency. Then, SML with Optimization (SML-OPT) is proposed to further improve the QoS by better utilizing the excess processor capacity. Finally, SML-OPT is enhanced with a Slack Reclaiming scheme (SML-SR). The reclaimed slacks are used to process jobs whose required computation time is larger than the guaranteed computation time. Simulation experiments are conducted to compare the performance of these schemes ( SML-BA, SML-OPT, and SML-SR) together with the deterministic More-Less and Half-Half schemes. The results show that the SML schemes are effective in trading the schedulability of transactions for the QoS guaranteed. Moreover, SML-SR performs best and offers a significant QoS improvement over SML-BA and SML-OPT.