点对点关键字搜索的环状过滤器

Y. Sei, S. Honiden
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引用次数: 1

摘要

分布式哈希表(dht)是一类分散的分布式系统,可以有效地搜索用户所需的对象。然而,大量的通信流量来自于多词搜索。为了减少这种流量,已经做了大量的工作,使用布隆过滤器,这是一种空间效率高的概率数据结构。有两种类型的布隆过滤器:固定大小和可变大小的布隆过滤器。我们不能使用可变大小的布隆过滤器,因为这样做意味着浪费时间来计算哈希值。另一方面,当使用固定大小的布隆过滤器时,DHT中的所有节点都无法调整其假阳性率参数。因此,流量的减少是有限的,因为最佳的假阳性率因节点而异。此外,在相关作品中,作者只考虑了双词搜索。在本文中,我们提出了一种确定三个或更多单词搜索的最佳误报率的方法。我们还使用了一种新的滤波器,称为环状滤波器,其中每个节点可以设置近似最佳误报率。实验表明,环形滤波器可以大大减少流量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ringed Filters for Peer-to-Peer Keyword Searching
Distributed hash tables (DHTs) are a class of decentralized distributed systems that can efficiently search for objects desired by the user. However, a lot of communication traffic comes from multi-word searches. A lot of work has been done to reduce this traffic by using bloom filters, which are space-efficient probabilistic data structures. There are two kinds of bloom filters: fixed-size and variable-size bloom filters. We cannot use variable- size bloom filters because doing so would mean wasting time to calculating hash values. On the other hand, when using fixed- size bloom filters, all the nodes in a DHT are unable to adjust their false positive rate parameters. Therefore, the reduction of traffic is limited because the best false positive rate differs from one node to another. Moreover, in related works, the authors took only two-word searches into consideration. In this paper, we present a method for determining the best false positive rate for three- or more word searches. We also used a new filter called a ringed filter, in which each node can set the approximately best false positive rate. Experiments showed that the ringed filter was able to greatly reduce the traffic.
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