Employing mutual-exclusion algorithms for collaborative immersive visualization--CTHRU_C: a case study

Gary Morris; Niushant Kaul; Adel L. Ali; Conrad Johnson

doi:10.1117/12.438113

23 August 2001 Employing mutual-exclusion algorithms for collaborative immersive visualization--CTHRU-C: a case study

Gary Morris, Niushant Kaul, Adel L. Ali, Conrad Johnson

Proceedings Volume 4368, Visualization of Temporal and Spatial Data for Civilian and Defense Applications; (2001) https://doi.org/10.1117/12.438113
Event: Aerospace/Defense Sensing, Simulation, and Controls, 2001, Orlando, FL, United States

Abstract

CTHRU is a high performance visualization tool that is used to visualize temporal 3D datasets in an immersion environment. It was developed by Mississippi State University to visualize ocean models. This paper describes the design, development, and implementation of an enhanced version of CTHRU in order to add new collaborative capabilities. The CTHRU-C software package allows remote users to view and manipulate temporal datasets in real-time. Developing a multi-collaborative package with homogeneous software on both sides may run a risk of message duplication, which would lead to every message being repeatedly sent over the network and since, the options work in a toggled manner this would wreck havoc on the systems. To solve this problem a new mutual exclusion algorithms was developed. The paper also describes the network design scheme including propagation techniques. To implement a multi-user environment one master is needed that everyone would connect to. The paper also describes the network design scheme including propagation techniques. To implement a multi-user environment one mater is needed that everyone would connect to. The master would farm out all connections. This connection was implemented in CTHRU-C as a floating master. The software is designed around OpenGL, CAVERNsoft and CAVElibs to interface to the immersion environment. The tool was successfully tested on local machines at the Central of Higher Learning and Mississippi State University. The paper also addresses the guidelines that should \be taken into consideration while designing similar packages if one the design objectives is to add collaborative mode in the future.

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Gary Morris, Niushant Kaul, Adel L. Ali, and Conrad Johnson "Employing mutual-exclusion algorithms for collaborative immersive visualization--CTHRU-C: a case study", Proc. SPIE 4368, Visualization of Temporal and Spatial Data for Civilian and Defense Applications, (23 August 2001); https://doi.org/10.1117/12.438113

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KEYWORDS

Visualization

Data modeling

Virtual reality

Data communications

Network architectures

Algorithm development

C++

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