不规则可逆Bloom查找表
Irregular Invertible Bloom Look-Up Tables
摘要：
我们考虑可逆布隆查找表（IBLT），这是概率数据结构，允许存储键值对。IBLT支持插入和删除键-值对，以及恢复所有已插入的键-值对，只要IBLT中存储的键-值对的数量不超过一定数量。IBLT上的恢复操作可以表示为二分图上的剥离过程。我们提出了一个密度演化分析的IBLT，它允许预测的最大数量的键-值对，可以插入到表中，使恢复仍然是成功的概率很高。这种分析适用于任意不规则度分布，并推广了文献中的结果。我们补充我们的分析，我们自己的IBLT设计的数值模拟，允许恢复大量的键值对作为国家的最先进的IBLT相同的大小。
英文摘要：
We consider invertible Bloom lookup tables (IBLTs) which are probabilistic data structures that allow to store keyvalue pairs. An IBLT supports insertion and deletion of key-value pairs, as well as the recovery of all key-value pairs that have been inserted, as long as the number of key-value pairs stored in the IBLT does not exceed a certain number. The recovery operation on an IBLT can be represented as a peeling process on a bipartite graph. We present a density evolution analysis of IBLTs which allows to predict the maximum number of key-value pairs that can be inserted in the table so that recovery is still successful with high probability. This analysis holds for arbitrary irregular degree distributions and generalizes results in the literature. We complement our analysis by numerical simulations of our own IBLT design which allows to recover a larger number of key-value pairs as state-of-the-art IBLTs of same size.
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