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Implementing error detection in fast counting Bloom filters

机译:在快速计数的Bloom过滤器中实现错误检测

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Bloom filters have found numerous applications in computing and networking systems. They are used to determine whether a given element is present in a set. Counting Bloom filters (CBFs) are an extension of Bloom filters that supports the removal of elements from the set. Traditional Bloom filters require several memory accesses to determine whether an element is present in the set. Recently, fast CBFs that can complete a search operation with only one memory access have been presented. Modern electronic systems are prone to soft errors. These errors can corrupt the contents of memories, causing system failures. In the case of Bloom filters, errors can cause failures where an element that is in the set is classified as not being in the set and the other way around. To avoid those failures, a per-word parity bit is commonly added to detect errors in memories. It is shown that error detection can be implemented in fast CBFs without adding any parity bit. This is achieved by exploiting the properties of the filters to implement error detection.
机译:布隆过滤器在计算和网络系统中发现了许多应用。它们用于确定集合中是否存在给定元素。计数布隆过滤器(CBF)是布隆过滤器的扩展,支持从集合中删除元素。传统的布隆过滤器需要几次内存访问才能确定集合中是否存在元素。近来,已经提出了仅用一个存储器访问就可以完成搜索操作的快速CBF。现代电子系统容易出现软错误。这些错误可能会破坏内存的内容,从而导致系统故障。对于布隆过滤器,如果将集合中的元素分类为不在集合中,则错误可能导致失败。为了避免这些故障,通常会添加每个字的奇偶校验位以检测内存中的错误。结果表明,可以在快速CBF中实现错误检测,而无需添加任何奇偶校验位。这是通过利用过滤器的属性来实现错误检测来实现的。

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