Doctoral Dissertations

Orcid ID

0000-0002-6269-7881

Date of Award

12-2023

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Computer Science

Major Professor

Jian Huang

Committee Members

Audris Mockus, Michela Taufer, Jitendra Kumar, Tom Peterka

Abstract

The rapid growth of data in scientific visualization has posed significant challenges to the scalability and availability of interactive visualization tools. These challenges can be largely attributed to the limitations of traditional monolithic applications in handling large datasets and accommodating multiple users or devices. To address these issues, the Visualization-as-a-Service (VaaS) architecture has emerged as a promising solution. VaaS leverages cloud-based visualization capabilities to provide on-demand and cost-effective interactive visualization. Existing VaaS has been simplistic by design with focuses on task-parallelism with single-user-per-device tasks for predetermined visualizations. This dissertation aims to extend the capabilities of VaaS by exploring data-parallel visualization services with multi-device support and hypothesis-driven explorations. By incorporating stateful information and enabling dynamic computation, VaaS' performance and flexibility for various real-world applications is improved. This dissertation explores the history of monolithic and VaaS architectures, the design and implementations of 3 new VaaS applications, and a final exploration of the future of VaaS. This research contributes to the advancement of interactive scientific visualization, addressing the challenges posed by large datasets and remote collaboration scenarios.

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