Author Type

Graduate Student

Date of Award

2017

Document Type

Thesis

Publication Status

Version of Record

Submission Date

October 2026

Thesis/Dissertation Advisor [Chair]

Kalva, Hari

Abstract

There is now more data being created than ever before and this data can be any form of data, textual, multimedia, spatial etc. To process this data, several big data processing platforms have been developed including Hadoop, based on the MapReduce model and LexisNexis’ HPCC systems. In this thesis we evaluate the HPCC Systems framework with a special interest in multimedia data analysis and propose a framework for multimedia data processing. It is important to note that multimedia data encompasses a wide variety of data including but not limited to image data, video data, audio data and even textual data. While developing a unified framework for such wide variety of data, we have to consider computational complexity in dealing with the data. Preliminary results show that HPCC can potentially reduce the computational complexity significantly.

Extent

42 p.

Comments

Includes bibliography.|Thesis (M.S.)--Florida Atlantic University, 2017.|FAU Electronic Theses and Dissertations Collection|Includes bibliography.

Identifier

FA00004875

Format

pdf

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