Hybrid algorithms for 3-SAT optimisation using MapReduce on clouds. (2018)

• Record Type: Journal Article
• Authors: Barreto, Marcos; Nesmachnow, Sergio; Tchernykh, Andrei
• Is Part Of: International journal of innovative computing and applications. Volume 9:Number 1(2018)
• Page Start: 44
• Page End: 64
• Publication Date: 2018
• Subjects: MapReduce -- Hadoop -- optimisation -- cloud -- 3-SAT; Evolutionary computation -- Periodicals; Neural networks (Computer science) -- Periodicals; Genetic programming (Computer science) -- Periodicals; Biologically-inspired computing -- Periodicals; Swarm intelligence -- Periodicals; Quantum computers -- Periodicals; 006.3
• Languages: English
• ISSNs: 1751-648X

Abstract

This article presents the advances on applying a MapReduce approach for solving optimisation problems using Hadoop on cloud computing systems. The main advantages and limitations of the proposed strategy are presented and commented. A concrete case study is reported, analysing several algorithmic approaches to solve the 3-SAT, a well-known version of the Boolean satisfiability problem. Several variants of the MapReduce 3-SAT solver are designed and evaluated to demonstrate that the collaborative approach is a promising option for solving optimisation problems in the cloud.