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AN INDEXING METHOD FOR SUPPORTING SPATIAL QUERIES IN STRUCTURED PEER-TO-PEER SYSTEMS

机译:一种用于支持结构对等系统中的空间查询的索引方法

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To provide the efficient supporting spatial data queries in peer-to-peer systems has recently received much attention. Most proposed methods tried to use hop count to represent the transmission delay, and the total message count to estimate the cost of query processing. For the ignorance of the differences between DHT lookups and spatial queries, and distinction between physical networks and overlay networks, the efficiency and cost of their query processing can't be indicated properly. In addition, their experimental results are achieved by using point data sets, while the fact that the overlap of spatial objects usually exists in real applications is not considered, and it may cause multi path query processing and then results in plenty of peers visiting and routing messages. In this paper, we propose an indexing method which efficiently supports spatial queries in structured peer-to-peer systems. It adopts an overlap minimization algorithm which takes the query rate of data into account to reasonably reduce the holistic cost of queries. We also introduce a dynamically adaptive distributed optimization scheme that dynamically adapting to the time-varying overlay architecture and data usage concerns. Theoretical analysis and simulation results both indicate that our method is efficient and effective.
机译:为了提供对等系统中的高效支持空间数据查询最近受到了很多关注。最拟议的方法试图使用跳数来表示传输延迟,并且总消息计数估计查询处理的成本。对于DHT查找和空间查询之间的差异的无知,并且物理网络和覆盖网络之间的区别,无法正确地指示查询处理的效率和成本。此外,它们的实验结果是通过使用点数据集实现的,而空间对象的重叠通常存在通常存在于实际应用中的事实,并且它可能导致多路径查询处理,然后导致大量的对等体访问和路由消息。在本文中,我们提出了一种索引方法,其有效地支持结构化的对等系统中的空间查询。它采用重叠最小化算法,该算法考虑到数据查询率,以合理地降低查询的整体成本。我们还介绍了一种动态自适应的分布式优化方案,可动态适应时变覆盖架构和数据使用问题。理论分析和仿真结果表明,我们的方法是有效且有效的。

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