Distributed and Collaborative VisualizationK.W. Brodlie, D.A, Duce, J.R. Gallop, J.P.R.B Walton and J.D. Wood

University of Amsterdam

Amir Masoud Abdol

Definitions

▪ Scientific Visualization is computationally intensive.

▪ Many Machine: Grid computing allows us to do intensive job.

▪ Many human: Collaboration allows group of people to think about one or more subject at the same time.

▪ Goal:

▪ To combine the collaboration workspaces or features like video conferencing or file sharing with the power of Grid computing.

▪ To harness the processing power of many humans and many machines.

Different Combinations of Using Many People and Many Machine

▪ Distributed Visualization System

▪ Facilities to use many machine

▪ Collaborative Visualization System

▪ Facilities to use share and talk about visualization result

▪ Distributed and Collaborative Visualization System

▪ Facilities to use many machine and share result or maybe modifying model

What you should consider to build such a system?

▪ Rules and Privilege of Users

▪ Users should have different rules in process

▪ Place and Time of Process

▪ Different situation according to the time and place of members

▪ Layers of the System

▪ Different layers of distributed collaborative system

Click icon to add picture

Applegate Place-time matrix

Same time, same place

Meeting in meeting room

Different time, different place

Sending data via mails or fax

Same time, different place

Video Conferencing

Different time, same place!

Layers of System: 3-Layer Model

▪ Conceptual Layer (Visualization Design)

▪ Logical Layer (Software Engineering)

▪ Physical Layer (Implementation)

Conceptual Layer (Visualization Design)

Tasks

▪ Designing the visualization process

Possible Collaboration

▪ Using video conference to argue different method

▪ Screen Sharing

▪ Document Sharing

▪ Editing,

▪ Annotation,

▪ and …

Logical Layer (Software engineering)

Tasks

▪ Expressing visualization as a particular configuration of software entities without considering hardware.

▪ Sub-layer▪ Logical visualization design▪ Description of the composition of

modules into a network

▪ Core software▪ Available modules in a system

Possible Collaboration

▪ Using packages on local or server

▪ Using data on local or server

▪ Computing results on the cloud

▪ See data on cloud, download it and visualize it on local machine

Physical Layer (Implementation)

Tasks

▪ Binding logical visualization design and core software to particular resources.

Possible Collaboration

• Working on code

Different implementations of Distributed and Collaborative Visualization

Client Based Visualization

Data on Server

•Private (Only one person can access)

•Shared (Many users can access it)

Data and Design

•Visualization design is also available on Server

Server Based Visualization

• Image display on client

• Model rendering on the client

Web Based Visualization

Full Service

• Visualization is created remotely by the service provider

• Only Graphical data deliver to local system

• Using Java Applet for interactivity

Software Delivery

• Visualization Software download to local machine, and read data from server and visualize it.

Choosing Design

Java for Interactivity

Java for communication and visualization

Main difference between Web-based and Server-Based maybe is data representation, In Server-based user can use any core software but in Web-based Java uses to implement the result into HTML pages.

Different Factors of Distributed and Collaborative Visualization System

▪ Base Visualization System Collaboration

▪ Ability to collaborate between different visualization system

▪ Multiple Platform

▪ Collaboration between different platform, for instance, operation systems

▪ Functionality

▪ Exchanging of data, Exchanging of parameters, Exchanging of modules, Exchanging of networks

Different Factor of Collaborative Visualization System

▪ Participation

▪ Setting up the system (Adminstratation)

▪ Joining/ Leaving (Registration)

▪ Automatic Launch/connection (Sharing Elements)

▪ Floor Control (Privileges)

▪ Data Privacy

▪ Global View

Different Factor of Collaborative Visualization System

▪ System

▪ Performance

▪ Reliability

▪ Scalability

▪ Target Users

▪ Visualization Programmer

▪ Visualization End User

System and Framework

▪ Visualization Tools

▪ VTK

▪ Amira

▪  AVS5 and AVS/Express, Cactus, COVISE, Ensight, IDL and PV-Wave, IRIS Explorer,  MATLAB, OpenDX, pV3, SCIRun, VisAD

▪ Collaboration Tools

▪ Desktop Sharing Tools

▪ VNC

▪ NetMeeting

• Remote Rendering

• SGI VIzserver

Questions?