Cluster management system design for big data infrastructures

Doctoral thesis (2016)

Authors

S. Gupta Algorithmics - EEMCS
Research Group
Algorithmics (EEMCS) (TU Delft)
Copyright: © 2016 S. Gupta
DOI: https://doi.org/10.4233/uuid:de1d4543-9bbe-4a2f-ac9a-f648f4066d0f
More Info
expand_more

Published Date

2016

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Software Technology

Research Group

Algorithmics

Abstract

In recent years,we have seen amajor shift in computing systems: data volumes are growing very fast, but hardware capabilities to store, process, and transfer the massive data are not speeding up at the same rate. Today, data are generated from a variety of sources, such as social networking websites, business transactions, banking sectors, etc. These data are valuable and contain lots of vital information if they are analyzed efficiently. The processing capabilities of single machines, however, are not sufficient enough, which
makes it harder to use them for data analysis. As a result, most web companies, but also the traditional business organizations, research labs, and universities, are scaling out their major computational frameworks to clusters of thousands of machines. To find the hidden and interesting insights from the data, in addition to simple queries, also complex machine learning algorithms and graphs processing are becoming a common choice in many areas. Nowadays, the problem to collect, store and analyze these data is called the Big Data problem.