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Rate-sensitive Load Shedding In Data Stream Systems

机译:数据流系统中速率敏感的负载减载

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Traditional load shedding algorithms for data stream systems calculate current operator selectivity over several ran periods and use them to determine where to shed load during the next run period. In this paper, we show that the current selectivity may change due to the implementation of load shedding. Our algorithm, called RLS, determines the optimum drop location by these changed selectivity rather than those pre-calculated values. Simulation results demonstrate that RLS achieves higher accuracy than traditional algorithms.
机译:用于数据流系统的传统减载算法在多个运行周期内计算当前操作员的选择性,并使用它们来确定在下一个运行周期内将负载分配到何处。在本文中,我们表明由于实施减载,当前的选择性可能会发生变化。我们的算法称为RLS,它通过这些变化的选择性而不是那些预先计算的值来确定最佳墨滴位置。仿真结果表明RLS比传统算法具有更高的精度。

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