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Integrating Geographical Information Systems and Grid Applications

Integrating Geographical Information Systems and Grid Applications. Marlon Pierce (mpierce@cs.indiana.edu) Contributions: Ahmet Sayar, Galip Aydin, Mehmet Aktas, Harshawardhan Gadgil Community Grids Lab Indiana University. Geographical Information Systems and Grid Applications.

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Integrating Geographical Information Systems and Grid Applications

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  1. Integrating Geographical Information Systems and Grid Applications Marlon Pierce (mpierce@cs.indiana.edu) Contributions: Ahmet Sayar, Galip Aydin, Mehmet Aktas, Harshawardhan Gadgil Community Grids Lab Indiana University

  2. Geographical Information Systems and Grid Applications • Pattern Informatics • Earthquake forecasting code developed by Prof. John Rundle (UC Davis) and collaborators. • Uses seismic archives as input • Regularized Dynamic Annealing Hidden Markov Method (RDAHMM) • Time series analysis code by Dr. Robert Granat (JPL). • Can be applied to GPS and seismic archives. • Can be applied to real-time data. • GeoFEST • Finite element method code developed by Dr. Jay Parker (JPL) and Prof. Greg Lyzenga (JPL/Harvey Mudd College) • Uses fault models as input. • Virtual California • Prof. Rundle’s UC-Davis group • Used for simulating time evolution of fault systems using fault and fault friction models.

  3. Pattern Informatics in a Grid Environment • PI in a Grid environment: • Hotspot forecasts are made using publicly available seismic records. • Southern California Earthquake Data Center • Advanced National Seismic System (ANSS) catalogs • Code location is unimportant, can be a service through remote execution • Results need to be stored, shared, modified • Grid/Web Services can provide these capabilities • Problems: • How do we provide programming interfaces (not just user interfaces) to the above catalogs? • How do we connect remote data sources directly to the PI code. • How do we automate this for the entire planet? • Solutions: • Use GIS services to provide the input data, plot the output data • Web Feature Service for data archives • Web Map Service for generating maps • Use HPSearch tool to tie together and manage the distributed data sources and code.

  4. Plotting Google satellite maps with QuakeTables fault overlays for Los Angeles.

  5. Web Map Client WSDL Aggregating WMS Stubs Stubs HTTP SOAP WSDL WSDL “REST” WFS + Seismic Rec. WFS + State Bounds … WMS + OnEarth Or Google Maps

  6. Tying It All Together: HPSearch • HPSearch is an engine for orchestrating distributed Web Service interactions • It uses an event system and supports both file transfers and data streams. • Legacy name • HPSearch flows can be scripted with JavaScript • HPSearch engine binds the flow to a particular set of remote services and executes the script. • HPSearch engines are Web Services, can be distributed interoperate for load balancing. • Boss/Worker model • ProxyWebService: a wrapper class that adds notification and streaming support to a Web Service. • More info: http://www.hpsearch.org

  7. HPSearch (TRex) HPSearch (Danube) Actual Data flow HPSearch controls the Web services Final Output pulled by the WMS HPSearch Engines communicate using NB Messaging infrastructure Data can be stored and retrieved from the 3rd part repository (Context Service) WS Context (Tambora) WFS (Gridfarm001) NaradaBroker network: Used by HPSearch engines as well as for data transfer WMS Data Filter (Danube) Virtual Data flow WMS submits script execution request (URI of script, parameters) HPSearch hosts an AXIS service for remote deployment of scripts • PI Code Runner • (Danube) • Accumulate Data • Run PI Code • Create Graph • Convert RAW -> GML GML (Danube)

  8. RDAHMM: GPS Time Series SegmentationSlide Courtesy of Robert Granat, JPL GPS displacement (3D) length two years.Divided automatically by HMM into 7 classes. • Complex data with subtle signals is difficult for humans to analyze, leading to gaps in analysis • HMM segmentation provides an automatic way to focus attention on the most interesting parts of the time • Features: • Dip due to aquifer drainage (days 120-250) • Hector Mine earthquake (day 626) • Noisy period at end of time series

  9. SOPAC GPS Services

  10. GIS and Collaboration Tools

  11. (Next set shows non-slideshow version)

  12. Electric Power and Natural Gas data Zoom-in Zoom-out FeatureInfo mode Measure distance mode Clear Distance Drag and Drop mode Refresh to initial map

  13. Overlaid Outage Area - I • Basic Steps: • Select Energy Power AND Natural Gas Data and Update Layer List rendered on the map • Click on “Overlay Outage” button • See the outage area on the map

  14. Overlaid Outage Area - II • Basic Steps: • Select Energy Power Data and Update Layer List rendered on the map • Click on “Overlay Outage” button • Use zoom-in mapping tool below to get same outage area in more detail • See the outage area on the map

  15. Getting Info about specific EP Data by clicking on the map • Basic Steps: • Select Energy Power Data and Update Layer List rendered on the map • Select (i) from the mapping tools below. • Click on any feature data on the map. • See the information for selected feature in pop-up window

  16. Google Hybrid Map and Feature Information call to WMS Natural Gas Layer Electric Power Layer

  17. NaradaBrokering: Message Transport for Distributed Services • NB is a distributed messaging software system. • http://www.naradabrokering.org • NB system virtualizes transport links between components. • Supports TCP/IP, parallel TCP/IP, UDP, SSL. • See e.g. http://grids.ucs.indiana.edu/ptliupages/publications/AllHands2005NB-Paper.pdf for trans-Atlantic parallel tcp/ip timings.

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