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 baseline 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

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