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Glendenning_Thesis.pdf (4.91 MB)

ETD Abstract Container

Abstract Header

Browser Based Visualization for Parameter Spaces of Big Data Using Client-Server Model

Glendenning, Kurtis M.
http://rave.ohiolink.edu/etdc/view?acc_num=wright1441203223

Abstract Details

2015, Master of Science (MS), Wright State University, Computer Science.
Visualization is an important task in data analytics, as it allows researchers to view abstract patterns within the data instead of reading through extensive raw data. Allowing the ability to interact with the visualizations is an essential aspect since it provides the ability to intuitively explore data to find meaning and patterns more efficiently. Interactivity, however, becomes progressively more difficult as the size of the dataset increases. This project begins by leveraging existing web-based data visualization technologies and extends their functionality through the use of parallel processing. This methodology utilizes state-of-the-art techniques, such as Node.js, to split the visualization rendering and user interactivity controls between a client-server infrastructure. The approach minimizes data transfer by performing the rendering step on the server while allowing for the use of HPC systems to render the visualizations more quickly. In order to improve the scaling of the system with larger datasets, parallel processing and visualization optimization techniques are used.
Thomas Wischgoll, Ph.D. (Advisor)
Michael Raymer, Ph.D. (Committee Member)
Derek Doran, Ph.D. (Committee Member)
46 p.
Computer Science
big data, visualization, parallel coordinate plot, client-server model, parallel processing

Recommended Citations

Citations

  • Glendenning, K. M. (2015). Browser Based Visualization for Parameter Spaces of Big Data Using Client-Server Model [Master's thesis, Wright State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=wright1441203223

    APA Style (7th edition)

  • Glendenning, Kurtis. Browser Based Visualization for Parameter Spaces of Big Data Using Client-Server Model. 2015. Wright State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=wright1441203223.

    MLA Style (8th edition)

  • Glendenning, Kurtis. "Browser Based Visualization for Parameter Spaces of Big Data Using Client-Server Model." Master's thesis, Wright State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=wright1441203223

    Chicago Manual of Style (17th edition)

wright1441203223
891
© 2015, all rights reserved.
This open access ETD is published by Wright State University and OhioLINK.
Release 3.2.12