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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support. Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support. Aengus McCullough, Newcastle University Philip James, Stuart Barr. [email protected]

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Aengus McCullough, Newcastle University

Philip James, Stuart Barr

[email protected]


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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

What is the Sensor Web?

“A coordinated observation infrastructure composed of a distributed collection of resources that can collectively behave as a single, autonomous, task-able, dynamically adaptive and reconfigurable observing system that provides raw and processed data, along with associated meta-data, via a set of standards-based service-oriented interfaces.” (Glenn, 2007)

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Sensor Web Enablement

Sourced from Reichardt (2005)

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Compute Nodes

Sensors

MIDDLEWARE

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Research Goals

  • To what extent can standards in Geospatial Web Services, Sensor Web and Distributed Computing be integrated within a geoprocessing context?

  • What are the potential bottlenecks in a real time monitoring and prediction system in relation to distributed geoprocessing?

  • Are there any generic methods of distributing real time geoprocessing operations?

  • To what degree is distributed computing a suitable tool for earth systems monitoring?

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Use Case: The ANGEL project

Goals:

  • To monitor the position of vehicles carrying dangerous goods

  • To determine the optimum route to their destination

  • Minimise cost, fuel-consumption and the risk of hijacking

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

System Overview

  • Loosely coupled service-oriented architecture

  • Utilise live traffic and vehicle position data.

  • Use OGC web services as the major data source.

  • Use the Grid to perform computationally intensive processing, enabling the system to scale over multiple vehicles and large geographic areas whilst minimising the use of computing resources.

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Scalability Issues

  • Geographic Data is voluminous

  • Shortest Path computations are expensive = problem for large graphs

Standards Issues

  • OGC, OGSA, WS-I, WSRF, OASIS……

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Implementation To Date:

  • Services implemented

    • Data services

    • Pre-processing services

  • Next Step:

    • Build processing services on top of grid middleware

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Sensor Web, Grid Computing and Geospatial Web Services for Real Time Decision Support

Questions?

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Thanks for Listening


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