Key-value (k-v) storage has been used as a crucial component for many network applications, such as social networks, online retailing, and cloud computing. Such storage usually provides support for operations on key-value pairs, and can be stored in memory to speed up responses to queries. So far, existing methods have been deterministic: they will faithfully return previously inserted key-valu...

The classical proof for Bloom filter false positive rates was shown to be incorrect due to a subtle error regarding independence of events. Although the previously computed false positive rate is asymptotically still correct, it is incorrect for small parameter values and is generally only a lower bound [BGK08]. Indeed, the correct analysis for Bloom filters does not admit a convenient closed f...

For a standard Bloom filter, each of the h hash functions could map item o to any element of the bit array. The bit array will often be very large, much larger than the processor cache. Thus, each probe into the bit array is likely to cause a cache miss. Putze et al [5] propose a blocked Bloom filter. Given a block size b, the first hash function H0(o) is used to select a size-b block of consec...

In a partially connected ad hoc network, two nodes communicate and share data when they are in proximity. For the query based (QB) scheme, a node retrieves data from another node by querying. Search efficiency deteriorates when the query success probability is small. We propose a Bloom filter based (BF) scheme to improve search efficiency. A data holder summarizes its content by a Bloom filter ...

Epidemic forwarding has been proposed as a forwarding technique to achieve opportunistic communication in Delay Tolerant Networks. Even if this technique is well known and widely referred, one has to first deal with several practical problems before using it. In particular, in order to manage the redundancy and to avoid useless transmissions, it has been proposed to ask nodes to exchange inform...

Interest dissemination in constrained environments such as wireless sensor networks utilizes Bloom filters commonly. A Bloom filter is a probabilistic data structure of fixed length, which can be used to encode the set of sensor nodes to be awake. In this way an application can disseminate interest in specific sensor nodes by broadcasting the Bloom filter throughout the complete wireless sensor...

Bloom filter is a probabilistic and space efficient data structure designed to check the membership of an element in a set. The trade-off to use Bloom filter may have configurable risk of false positives. The percentages of a false positive can be made low if the hash bit map is sufficiently massive. Spam is an unsolicited or irrelevant message sent on the internet to an outsized range of users...

Despite the rapid advance in networking technologies, detection of network anomalies at high-speed switches/routers is still far from maturity. To push the frontier, two major technologies need to be addressed. The first one is efficient feature-extraction algorithms/hardware that can match a line rate in the order of Gb/s; the second one is fast and effective anomaly detection schemes. In this...

The function of the comparing fingerprints algorithm was to judge whether a new partitioned data chunk was in a storage system a decade ago. At present, in the most de-duplication backup system the fingerprints of the big data chunks are huge and cannot be stored in the memory completely. The performance of the system is unavoidably retarded by data chunks accessing the storage system at the qu...

The Bloom Filter (BF), a space-and-time-efficient hashcoding method, is used as one of the fundamental modules in several network processing algorithms and applications such as route lookups, cache hits, packet classification, per-flow state management or network monitoring. BF is a simple space-efficient randomized data structure used to represent a data set in order to support membership quer...