Abstract
Content-based publish/subscribe (CPS) systems are widely used in many fields to achieve selective data distribution. Event matching is a key component in the CPS system. Many efficient algorithms have been proposed to improve matching performance. However, most of the existing work seldom considers the hardware characteristics, resulting in performance degradation due to a large number of repetitive operations, such as comparison, addition and assignment. In this paper, we propose a Hardware-aware Event Matching algorithm called HEM. The basic idea behind HEM is that we perform as many bit OR operations as possible during the matching process, which is most efficient for the hardware. In addition, we build a performance analysis model that quantifies the trade-off between memory consumption and performance improvement. We conducted extensive experiments to evaluate the performance of HEM. On average, HEM reduces matching time by up to 86.8% compared with the counterparts.
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Acknowledgments
This work was supported by the National Key Research and Development Program of China (2019YFB1704400), the National Natural Science Foundation of China (61772334, 61702151), and the Special Fund for Scientific Instruments of the National Natural Science Foundation of China (61827810).
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Shi, W., Qian, S. (2022). HEM: A Hardware-Aware Event Matching Algorithm for Content-Based Pub/Sub Systems. In: Bhattacharya, A., et al. Database Systems for Advanced Applications. DASFAA 2022. Lecture Notes in Computer Science, vol 13245. Springer, Cham. https://doi.org/10.1007/978-3-031-00123-9_23
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DOI: https://doi.org/10.1007/978-3-031-00123-9_23
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