Probabilistic counting algorithms for data base applications

Probabilistic Counting Algorithms for Data Base Applications

Near-Optimal Compression of Probabilistic Counting Sketches for Networking Applications

Sketches—data structures for probabilistic, duplicate insensitive counting—are central building blocks of a number of recently proposed network protocols, for example in the context of wireless sensor networks. They can be used to perform robust, distributed data aggregation in a broad range of settings and applications. However, the structure of these sketches is very redundant, making effecti...

Algorithms for Counting 2-SatSolutions and Colorings with Applications

An algorithm is presented for exactly solving (in fact, counting) the number of maximum weight satisfying assignments of a 2-Cnf formula. The worst case running time of O(1.246) for formulas with n variables improves on the previous bound of O(1.256) by Dahllöf, Jonsson, and Wahlström. The algorithm uses only polynomial space. As a consequence we get an O(1.246) time algorithm for counting maxi...

Probabilistic Data Consistency for Wide-Area Applications

Wide-area applications, such as electronic commerce, groupware, directory service etc., rely on distributed data management services which often employ data replication to meet availability and response time constraints imposed by the target domains. Since many of these applications can tolerate some staleness in the data they access, the constraints may be better met by exploiting relaxed data...

Applications of Probabilistic Quorums to Iterative Algorithms

This paper presents a definition of a read-write register that sometimes returns out-of-date values, shows that the definition is implemented by the probabilistic quorum algorithm of [19], and shows how to program with such registers using the framework of Üresin and Dubois [25]. Consequently, existing iterative algorithms for an interesting class of problems (including finding shortest paths, ...