large scale simulation experimentation and analysis n.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Large-Scale Simulation Experimentation and Analysis PowerPoint Presentation
Download Presentation
Large-Scale Simulation Experimentation and Analysis

Loading in 2 Seconds...

play fullscreen
1 / 19

Large-Scale Simulation Experimentation and Analysis - PowerPoint PPT Presentation


  • 124 Views
  • Uploaded on

Large-Scale Simulation Experimentation and Analysis. Database Programming Using Java. Agenda. Background on problem presented by the simulations. Architecture of the Scalable Data Grid (SDG) solution. Java technology choices. Future Directions for SDG Questions. Simulation Environment.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Large-Scale Simulation Experimentation and Analysis' - kelly-moody


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
large scale simulation experimentation and analysis

Large-Scale Simulation Experimentation and Analysis

Database Programming Using Java

Craig E. Ward

agenda
Agenda
  • Background on problem presented by the simulations.
  • Architecture of the Scalable Data Grid (SDG) solution.
  • Java technology choices.
  • Future Directions for SDG
  • Questions

Craig E. Ward

simulation environment
Simulation Environment
  • Joint Semi-Autonomous Forces (JSAF) environment in Urban Resolve experiments.
  • Distributed across multiple workstations and two 128-node clusters.
  • Goal of simulating 1,000,000 entities.

Craig E. Ward

logging simulation data
Logging Simulation Data
  • Data loggers captured simulation data from JSAF environment
  • Before analysis, data moved to central store.
  • Experiments generating multiple terabytes of data.
  • Data difficult to manage and analyze.

Craig E. Ward

scaleable data grid
Scaleable Data Grid
  • SDG is a system for distributed collection and analysis of large amounts of data.
  • Initial prototype deployment for JSAF environment in Urban Resolve 2015 experiment.
  • Goals
    • Make the analysis of the data more useful.
    • Make the management of data more convenient.

Craig E. Ward

sdg n tier architecture
SDG n-tier Architecture
  • Java applications
    • Services between nodes
    • Services to client simulations
  • Web application
    • User Interface
  • Database engine
    • MySQL

Craig E. Ward

multidimensional cubes

Detection Cube

Multidimensional Cubes
  • Use the raw data to create multidimensional cubes of dimensions of interest.
  • Dimensions “roll up” into categories of greater abstraction.

Craig E. Ward

sdg cube implementation concepts
SDG Cube Implementation Concepts
  • Cube Description
    • What the possible ranges are for indices (coordinates) and measures in a Cube.
  • Cube View
    • A selection of a subset of the possible indices and measures of interest in a query.
  • Cube
    • A instantiation of a Cube that matches a Cube View.
    • Comprised of Elements with indices and measures.

Craig E. Ward

distributed communication
Distributed Communication
  • Communication between processes and nodes with Remote Method Invocation (RMI).
  • Cube Manager classes register handles with RMI servers
  • Managers return handles to Cubes
  • Descriptions and Views are serialized and passed to clients.

Craig E. Ward

slide12
JDBC
  • Cubes do not exist in their entirety outside of the database tables.
  • Tables store simple elements of the Cubes.
    • Measures at the coordinates in relational table.
  • Elements are very simple Java objects.

Craig E. Ward

threaded processing
Threaded Processing
  • Interface to simulations using sockets and pooled Thread objects.
  • Internal mechanisms use Java 5 Executor classes and thread-safe queues from the concurrent processing package.
    • Generator
    • Query
    • Aggregation

Craig E. Ward

sdg web application
SDG Web Application
  • HTML
    • Forms for query selection.
    • Display of results of queries.
  • Java Server Pages
    • Create HTML pages.
  • JavaScript
    • Manipulate DOM to display form.
  • Java servlets
    • Interface between backend and JSP pages.

Craig E. Ward

java technologies used
Java Technologies used
  • JDBC
    • Interaction with the database.
  • RMI
    • Communication between nodes.
  • Threads
    • “Traditional” and new Java 5 concurrent classes.
  • Sockets
    • Interface to simulations.

Craig E. Ward

technologies not used
Technologies Not Used
  • Java Data Objects
    • Complicates build process.
  • Hibernate
    • Another product to configure and distribute.
  • Java EE
    • Too complex.
  • Clustered JDBC (Sequoia)
    • Requires that tables be uniform.

Craig E. Ward

future sdg development
Future SDG Development (?)
  • Enhance web application with JSF, Ajax.
  • Caching of cube view results.
  • Develop ad hoc query capability.
  • Implement an algebra for manipulating cubes.
  • Dynamic update of cube descriptions.
  • Dynamic reconfiguration of communication links.

Craig E. Ward