Abstract
This paper proposes a framework for soft real-time text classification system, which use control theory as a scientific underpinning, rather than ad hoc solutions. In order to provide real-time guarantee, two control loops are adopted. The feed forward control loop estimates the suitable number of classifiers according to the current workload, while the feedback control loop provides fine-grained control to the number of classifiers that perform imprecise computation. The soft real-time classification system can accommodate to the change of workload and transitional overload. The theory analysis and experiments result further prove its effectiveness: the variation range of the average response time is kept within ± 3% of the desired value; the computational resource is dynamically reallocated and reclaimed.
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Wang, H., Chen, Y., Dai, Y. (2005). A Soft Real-Time Web News Classification System with Double Control Loops. In: Fan, W., Wu, Z., Yang, J. (eds) Advances in Web-Age Information Management. WAIM 2005. Lecture Notes in Computer Science, vol 3739. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11563952_8
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DOI: https://doi.org/10.1007/11563952_8
Publisher Name: Springer, Berlin, Heidelberg
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