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ABSTRACT
The periodic update transaction model has been used to maintain freshness (or temporal validity) of real-time data. Period and deadline assignment has been the main focus in the past studies such as the More-Less scheme [25] in which update transactions are guaranteed by the Deadline Monotonic scheduling algorithm [16] to complete by their deadlines. In this article, we propose a deferrable scheduling algorithm for fixed priority transactions - a novel approach for minimizing update workload while maintaining the temporal validity of real-time data. In contrast to prior work on maintaining data freshness periodically, update transactions follow an aperiodic task model in the deferrable scheduling algorithm. The deferrable scheduling algorithm exploits the semantics of temporal validity constraint of real-time data by judiciously deferring the sampling times of update transaction jobs as late as possible. We present a theoretical estimation of its processor utilization, and a sufficient condition for its schedulability. Our experimental results verify the theoretical estimation of the processor utilization. We demonstrate through the experiments that the deferrable scheduling algorithm is an effective approach, and it significantly outperforms the More-Less scheme in terms of reducing processor workload.
INDEX TERMS
Real-time systems and embedded systems, Scheduling, Real-time and embedded systems
CITATION
Ming Xiong, Deji Chen, Song Han, Kam-Yiu Lam, "Deferrable Scheduling for Maintaining Real-Time Data Freshness: Algorithms, Analysis, and Results", IEEE Transactions on Computers, vol. 57, no. , pp. 952-964, July 2008, doi:10.1109/TC.2008.16
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