Skip-Webs：多维数据集的高效分布式数据结构
Skip-Webs: Efficient Distributed Data Structures for Multi-Dimensional Data Sets
摘要：
我们提出了一个设计有效的分布式数据结构的多维数据的框架。我们的结构，我们称之为跳跃网，扩展和改进以前的随机分布数据结构，包括跳跃网和跳跃图。我们的框架适用于一般类的数据查询场景，其中包括线性（一维）数据，如排序集，以及多维数据，如d维八叉树和数字尝试的字符串定义在一个固定的字母表。我们将展示如何执行这样一组n个项目的查询，分布在n个主机使用O（log n / log log n）的一维数据的消息，或O（log n）的消息固定维的数据，而每个主机只使用O（log n）的空间。我们还展示了如何使这样的结构动态，以便允许插入和删除在O（log n）的消息四叉树，八叉树，和数字尝试，和O（log n / log log n）的一维数据的消息。最后，我们展示了如何将阻塞策略应用于跳过Web，以进一步提高主机可以存储更多数据时一维数据的消息复杂性。
英文摘要：
We present a framework for designing efficient distributed data structures for multi-dimensional data. Our structures, which we call skip-webs, extend and improve previous randomized distributed data structures, including skipnets and skip graphs. Our framework applies to a general class of data querying scenarios, which include linear (one-dimensional) data, such as sorted sets, as well as multi-dimensional data, such as d-dimensional octrees and digital tries of character strings defined over a fixed alphabet. We show how to perform a query over such a set of n items spread among n hosts using O(log n / log log n) messages for one-dimensional data, or O(log n) messages for fixed-dimensional data, while using only O(log n) space per host. We also show how to make such structures dynamic so as to allow for insertions and deletions in O(log n) messages for quadtrees, octrees, and digital tries, and O(log n / log log n) messages for one-dimensional data. Finally, we show how to apply a blocking strategy to skip-webs to further improve message complexity for one-dimensional data when hosts can store more data.
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