Transcript Integrating Geographical Information Systems and Grid Applications Marlon Pierce ([email protected]) Contributions: Ahmet Sayar, Galip Aydin, Mehmet Aktas, Harshawardhan Gadgil, Zhigang Qi Community Grids Lab Indiana University Project Funding:

Integrating Geographical
Information Systems and Grid
Applications
Marlon Pierce ([email protected])
Contributions: Ahmet Sayar, Galip Aydin, Mehmet Aktas,
Harshawardhan Gadgil, Zhigang Qi
Community Grids Lab
Indiana University
Project Funding: NASA AIST, ACCESS
QuakeSim Project Overview
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QuakeSim is a NASA funded collaboration of
geophysicists and computer scientists to
build cyber-infrastructure for geophysical
research.
CI research and development includes
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Portlet-based portals
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AJAX enabled
Geographical Information System services
Application services to run codes.
QuakeSim Project Development
Overview
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Portlet-based portal components allow different portlets to be
exchanged between projects.
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Form-based portlets --> Interactive Maps
These are clients to Web services
Share with collaborators of REASoN portal.
Sensor Grid: Topic based publish-subscribe systems support
operations on streaming data.
Web services allow request/response style access to data
and codes.
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GIS services (WMS, WFS)
“Execution grid” services for running codes: RDAHMM, ST_Filter
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Use application specific WSDL on top of generic code management
services.
GPS daily archive Web Services provided by Scripps.
Sensor Grid Overview
Sensor Grid Overview
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SensorGrid architecture supports access to both
archived (databases), and real-time geospatial data
through universal GIS standards and Web Service
interfaces.
The architecture provides tools for coupling
geospatial data with scientific data assimilation,
analysis and visualization codes, such as:
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Pattern Informatics
Virtual California
IEISS
RDAHMM
Real-Time Services for GPS Observations
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Real-time data processing is supported by
employing filters around publish/subscribe
messaging system.
The filters are small applications extended
from a generic Filter class to inherit publish
and subscribe capabilities.
Input Signal
Filter
Output Signal
Filter Chains
NaradaBrokering Topics
Real-Time positions on Google maps
Real-Time Station Position Changes
RDAHMM + Real-Time GPS Integration
Federating Map Servers
Zao Liu, Marlon Pierce, Geoffrey Fox
Community Grids Laboratory
Indiana University
Integrating Map Servers
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Geographical Information Systems combine online dynamic
maps and databases.
Many GIS software packages exist
GIS servers around state of Indiana
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ESRI ArcIMS and ArcMap Server (Marion, Vanderburgh,
Hancock, Kosciusco, Huntington, Tippecanoe)
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Autodesk MapGuide (Hamilton, Hendricks, Monroe,
Wayne)
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WTH Mapserver™ Web Mapping Application (Fulton,
Cass, Daviess, City of Huntingburg) based on several
Open Source projects (Minnesota Map Server)
Challenge: make 17 different county map servers from different
companies work together.
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92 counties in Indiana, so potentially 92 different map
servers.
Considerations
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We assume heterogeneity in GIS map and feature
servers.
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We must reconcile ESRI, Autodesk, OGC, Google Map,
and other technical approaches.
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GIS services are organized bottom-up rather than top-down.
Local city governments, 92 different county governments,
multiple Indiana state agencies, inter-state (Ohio, Kentucky)
consideration, federal government data providers (Hazus).
Must find a way to federate existing services.
Must try to take advantage of Google, ESRI, etc rather than
compete.
We must have good performance and interactivity.
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Servers must respond quickly--launching queries to 20 different
map servers is very inefficient.
Clients should have simplicity and interactivity of Google Maps
and similar AJAX style applications.
Caching and Tiling Maps
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Federation through caching:
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WMS and WFS resources are queried and results are stored on the cache
servers.
WMS images are stored as tiles.
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These can be assembled into new images on demand (c. f. Google Maps).
Projections and styling can be reconciled.
We can store multiple layers this way.
We build adapters that can work with ESRI and OGC products; tailor to
specific counties.
Serving images as tiles
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Client programs obtain images directly from our tile server.
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That is, don’t go back to the original WMS for every request.
Similar approaches can be used to mediate WFS requests.
This works with Google Map-based clients.
The tile server can re-cache and tile on demand if tile sections are missing.
Map Server Example
Marion and Hancock
county parcel plots
and IDs are overlaid
on IU aerial
photographic images
that are accessed by
this mashup using
Google Map APIs.
We cache and tile all
the images from
several different map
servers. (Marion and
Hancock actually use
different commercial
software.)