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<p><it>Abstract</it>—We study the performance of concurrency control algorithms in maintaining temporal consistency of shared data in hard real-time systems. In our model, a hard real-time system consists of periodic tasks which are either write-only, read-only or update transactions. Transactions may share data. Data objects are temporally inconsistent when their ages and dispersions are greater than the absolute and relative thresholds allowed by the application. Real-time transactions must read temporally consistent data in order to deliver correct results. Based on this model, we have evaluated the performance of two well-known classes of concurrency control algorithms that handle multiversion data: the two-phase locking and the optimistic algorithms, as well as the rate-monotonic and earliest-deadline-first scheduling algorithms. The effects of using the priority inheritance and stack-based protocols with lock-based concurrency control are also studied.</p>
Data temporal consistency, periodic job model, real-time scheduling, multiversion concurrency control, performance evaluation.
Jane W.S. Liu, Xiaohui (Carol) Song, "Maintaining Temporal Consistency: Pessimistic vs. Optimistic Concurrency Control", IEEE Transactions on Knowledge & Data Engineering, vol. 7, no. , pp. 786-796, October 1995, doi:10.1109/69.469820
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