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TOF: A Throughput Oriented Framework for Spatial Queries Processing in Multi-core Environment

机译:TOF:多核环境中的空间查询处理的吞吐量框架

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In this paper, we develop a Throughput Oriented Framework (TOF) for efficient processing of spatiotemporal queries in multi-core environment. Traditional approaches to spatial query processing were focused on reduction of query latency. In real world, most LBS applications emphasize throughput rather than query latency. TOF is designed to achieve maximum throughput. Instead of resorting to complex indexes, TOF chooses to execute a batch queries at each run, so it can maximize data locality and parallelism on multi-core platforms. Using TOF, we designed algorithms for processing range queries and kNN queries respectively. Experimental study shows that these algorithms outperform the existing approaches significantly in terms of throughput.
机译:在本文中,我们开发了一种面向漏价的框架(TOF),以便在多核环境中有效地处理时空查询。空间查询处理的传统方法侧重于降低查询延迟。在现实世界中,大多数LBS应用程序强调吞吐量而不是查询延迟。 TOF旨在实现最大吞吐量。 ToF选择在每个运行时执行批量查询而不是诉诸复杂的索引,而是可以最大限度地提高多核平台上的数据局部性和并行性。使用TOF,我们设计了用于处理范围查询和KNN查询的算法。实验研究表明,这些算法在吞吐量方面优于现有的方法。

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