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首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >An intelligent scheme for assigning queries
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An intelligent scheme for assigning queries

机译：用于分配查询的智能方案

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摘要

Analytics provided on top of large scale data streams are the key research subject for future decision making applications. The huge volumes of data make their partitioning imperative to efficiently support novel applications. Such applications should be based on intelligent, efficient methods for querying multiple data partitions. A processor is placed in front of each partition dedicated to manage/execute queries for the specific piece of data. Continuous queries over these data sources require intelligent mechanisms to result the final outcome (query response) in the minimum time with the maximum performance. This paper proposes a mechanism for handling the behavior of an entity that undertakes the responsibility of handling the incoming queries. Our mechanism adopts a time-optimized scheme for selecting the appropriate processor(s) for each incoming query through the use of the Odds algorithm. We try to result the optimal assignment, i.e., queries to processors, in the minimum time while maximizing the performance. We provide mathematical formulations for describing the discussed problem and present simulation results and a comparative analysis. Through a large number of experiments, we reveal the advantages of the model and give numerical results comparing it with a deterministic model as well as with other efforts in the domain.
机译：在大规模数据流之上提供的分析是未来决策应用的主要研究主题。巨大的数据卷使其分区必须有效地支持新颖的应用程序。此类应用程序应基于智能，有效的查询多个数据分区的方法。处理器放置在专用于管理/执行特定数据的查询的每个分区前面。在这些数据源上的连续查询需要智能机制，以在最大性能的最小时间内导致最终结果（查询响应）。本文提出了一种处理实体行为的机制，该机制承担处理来回查询的责任。我们的机制采用时间优化方案来通过使用赔率算法来为每个来电选择适当的处理器。我们尝试在最短时间内导致最佳分配，即对处理器查询，同时最大限度地提高性能。我们提供数学制剂，用于描述讨论的问题和目前的模拟结果和比较分析。通过大量的实验，我们揭示了模型的优势，并给出了与确定性模型以及域中其他努力进行比较的数字结果。

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