ISSN 1991-2927
 

ACP № 2 (56) 2019

Author: "Sergei Orestovich Smerechinskii"

Valeriia Vadimovna Voronina, Ulyanovsk State Technical University, Candidate of Engineering; graduated from the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Associate Professor at the Department of Information Systems of Ulyanovsk State Technical University; an author of articles in the field of intellectual analysis of time series. [e-mail: vvsh85@mail.ru]V. Voronina,

Sergei Orestovich Smerechinskii, “AIS Gorod” Company, Magister; finished his Master’s studies at the Faculty of Information Systems and Technologies of Ulyanovsk State Technical University; Software Engineer at “AIS Gorod” Company; an author of articles in the field of software development. [e-mail: quigon173@gmail.com]S. Smerechinskii

The System for Modelling the Cluster Simulating Processes of Big Data Analysis 000_9.pdf

The subject area for processing Big Data with the use of cluster systems is described in the article. The paper examines the existing methods of processing Big Data on which the proposed solution for increasing the efficiency of the cluster functioning is based. As basic solutions for building and proposing ways to increase the efficiency of the cluster, the Hadoop technology and the MapReduce methodology were chosen. The efficiency of cluster systems involves consideration of cluster processes in the form of the hierarchical architecture consisting of three levels: cluster node level, cluster segment level and cluster topology level. The paper indicates solutions that can be useful in order to improve the efficiency of cluster resource allocation by choosing the topology of cluster construction, using the more efficient load-balancing algorithm, and using graphics processors, which involves distributing computational loads between CPU and GPU. Recommendations proposed in the article are verified experimentally.

Big data, cpu, gpu, mapreduce, big data, cluster, balancing algorithm, topology, cpu, gpu, mapreduce.

2017_ 3

Sections: Information systems

Subjects: Information systems, Automated control systems.


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