Tulchinsky V. Models and methods for parallel and distributed big data processing

Українська версія

Thesis for the degree of Doctor of Science (DSc)

State registration number

0516U000532

Thesis Registration Form

0516U000532.pdf

Applicant for

Specialization

  • 01.05.03 - Математичне та програмне забезпечення обчислювальних машин і систем

03-06-2016

Specialized Academic Board

Д 26.194.02

V.M. Glushkov Institute of Cybernetics of National Academy of Sciences of Ukraine

Essay

The problem of efficient processing and analysis of raising data streams by parallel and distributed computing systems is investigated. А model of cluster system performance is proposed. It enables to predict parallel program run time depending on the number of used processors. A method of data processing acceleration due to data compressing is proposed. For the data collected during a long time the impact of possible pattern change considering on mistake risk is analyzed. For big data of complex structure a method of the problem solving rule synthesis from partial patterns is developed. The implementation for several big application problems is described.

Read more

Files

aref.doc

dis.doc

Similar theses

0421U104038

Petrenko Maksym V.

Methods of integration of heterogeneous bibliographic data

0421U104040

Artabaev Yurii Z.

A technique for increasing the accuracy of integrated navigation systems based on predictive models using genetic algorithms.

0421U103593

Zubko Roman Anatoliyovych

Improving methods to increase the time efficiency of fractal image compression

0421U103401

Chystyakova Inna S.

Mapping method between the description logic and the relational data model.

0421U103320

Bielozorova Yana Andriivna

Method of application of wavelet analysis in problems of identification of speech information