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Spatially-decaying aggregation over a network

机译:网络上的空间衰减聚合

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Data items are often associated with a location in which they are present or collected, and their relevance or influence decays with their distance. Aggregate values over such data thus depend on the observing location, where the weight given to each item depends on its distance from that location. We term such aggregation spatially-decaying. Spatially-decaying aggregation has numerous applications: Individual sensor nodes collect readings of an environmental parameter such as contamination level or parking spot availability; the nodes then communicate to integrate their readings so that each location obtains contamination level or parking availability in its neighborhood. Nodes in a p2p network could use a summary of content and properties of nodes in their neighborhood in order to guide search. In graphical databases such as Web hyperlink structure, properties such as subject of pages that can reach or be reached from a page using link traversals provide information on the page. We formalize the notion of spatially-decaying aggregation and develop efficient algorithms for fundamental aggregation functions, including sums and averages, random sampling, heavy hitters, quantiles, and L_p norms.
机译:数据项通常与它们存在或收集的位置相关联,并且它们的相关性或影响力随它们的距离而衰减。因此,此类数据的合计值取决于观察位置,其中赋予每个项目的权重取决于其与该位置的距离。我们称这种聚集在空间上衰减。空间衰减聚合具有许多应用:单个传感器节点收集环境参数的读数,例如污染水平或停车位可用性;然后,节点进行通信以整合其读数,以便每个位置都获得其附近的污染水平或停车位。 p2p网络中的节点可以使用其附近节点的内容和属性摘要来指导搜索。在诸如Web超链接结构的图形数据库中,可以使用链接遍历从页面访问或从页面访问的属性(例如页面主题)提供页面信息。我们将空间衰减聚合的概念形式化,并为基本聚合函数开发有效的算法,包括求和和平均值,随机采样,沉重的敲击者,分位数和L_p范数。

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