An algorithm to reduce the communication traffic for multi-word searches in a distributed hash table

In distributed hash tables, much communication traffic comes from multi-word searches. The aim of this work is to reduce the amount of traffic by using a bloom filter, which is a space-efficient probabilistic data structure used to test whether or not an element is a member of a set. However, bloom filters have a limited role if several sets have different numbers of elements. In the proposed method, extra data storage is generated when contents' keys are registered in a distributed hash table system. Accordingly, we propose a "divided bloom filter" to solve the problem of a normal bloom filter. Using the divided bloom filter, we aim to reduce both the amount of communication traffic and the amount of data storage.4th IFIP International Conference on Theoretical Computer ScienceRed de Universidades con Carreras en Informática (RedUNCI

An algorithm to reduce the communication traffic for multi-word searches in a distributed hash table

In distributed hash tables, much communication traffic comes from multi-word searches. The aim of this work is to reduce the amount of traffic by using a bloom filter, which is a space-efficient probabilistic data structure used to test whether or not an element is a member of a set. However, bloom filters have a limited role if several sets have different numbers of elements. In the proposed method, extra data storage is generated when contents' keys are registered in a distributed hash table system. Accordingly, we propose a "divided bloom filter" to solve the problem of a normal bloom filter. Using the divided bloom filter, we aim to reduce both the amount of communication traffic and the amount of data storage.4th IFIP International Conference on Theoretical Computer ScienceRed de Universidades con Carreras en Informática (RedUNCI

An algorithm to reduce the communication traffic for multi-word searches in a distributed hash table

In distributed hash tables, much communication traffic comes from multi-word searches. The aim of this work is to reduce the amount of traffic by using a bloom filter, which is a space-efficient probabilistic data structure used to test whether or not an element is a member of a set. However, bloom filters have a limited role if several sets have different numbers of elements. In the proposed method, extra data storage is generated when contents' keys are registered in a distributed hash table system. Accordingly, we propose a "divided bloom filter" to solve the problem of a normal bloom filter. Using the divided bloom filter, we aim to reduce both the amount of communication traffic and the amount of data storage.4th IFIP International Conference on Theoretical Computer ScienceRed de Universidades con Carreras en Informática (RedUNCI

An Algorithm to Reduce the Communication Traffic for Multi-Word Searches in a Distributed Hash Table

Abstract. In distributed hash tables, much communication traffic comes from multi-word searches. The aim of this work is to reduce the amount of traffic by using a bloom filter, which is a space-efficient probabilistic data structure used to test whether or not an element is a member of a set. However, bloom filters have a limited role if several sets have different numbers of elements. In the proposed method, extra data storage is generated when contents' keys are registered in a distributed hash table system. Accordingly, we propose a "divided bloom filter" to solve the problem of a normal bloom filter. Using the divided bloom filter, we aim to reduce both the amount of communication traffic and the amount of data storage

Abstract Automatic Inversion Generates Divide-and-Conquer Parallel Programs

Divide-and-conquer algorithms are suitable for modern parallel machines, tending to have large amounts of inherent parallelism and working well with caches and deep memory hierarchies. Among others, list homomorphisms are a class of recursive functions on lists, which match very well with the divide-and-conquer paradigm. However, direct programming with list homomorphisms is a challenge for many programmers. In this paper, we propose and implement a novel system that can automatically derive costoptimal list homomorphisms from a pair of sequential programs, based on the third homomorphism theorem. Our idea is to reduce extraction of list homomorphisms to derivation of weak right inverses. We show that a weak right inverse always exists and can be automatically generated from a wide class of sequential programs. We demonstrate our system with several nontrivial examples, including the maximum prefix sum problem, the prefix sum computation, the maximum segment sum problem, and the line-ofsight problem. The experimental results show practical efficiency of our automatic parallelization algorithm and good speedups of the generated parallel programs