SEE-GRID-SCI
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
Grid Based Environment Application Development - GreenView
Danut Mihon, Victor Bacu, Teodor Stefanut, Dorian GorganTechnical University of Cluj-Napoca
{vasile.mihon, victor.bacu, teodor.stefanut, dorian.gorgan}@cs.utcluj.ro
SEE-GRID-SCI Dissemination 26 September 2009
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
GreenView objectives
It is an environmental application used for predicting and monitoring the temperature over a specific geographical area
In present it works only for CEE regionsExtend it’s functionality to other geographical areas
Calibrate satellite measurements Based on BIOME-BGC (BioGeochemical Cycles) model
Integrate other environmental applications as subcomponents of GreenViewEnviMon (RENAM)Soil Pollution by Heavy Metals (CENS NAS RA - Center for Ecological-Noosphere Studies of National Academy of Sciences of the Republic of Armenia)
The application provide a quick and easy access to it’s functionality based on a web interface
http://gisheo01.mediogrid.utcluj.ro:8095/interpolation_v2.1/http://wiki.egee-see.org/index.php/GreenView
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
Why we choose these technologies?
Server side algorithms are implemented using Java SDK 1.5
The user interface is created using Adobe Flex 3.3 technology and BlazeDS, that allow free access to remote technologies developed by Adobe.
Adobe Flex advantagesFree technologyAllows RIA developmentUses MXML components for GUI and action script for interactivityPredefined componentsAdd dynamic behaviorPlatform independentBuild the code into a SWF that runs in Flash Player
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
GreenView – Application Development Methodology
1. Algorithm identification and analysis2. Data model definition3. Identify atomic parts of the algorithms
– Parallel or serial processing– Implementation as services, procedures, separate applications
4. Algorithm implementation5. Description of processing using gProcess
– PDG Definition– iPDG specification– Execution
6. Create the application interface– Link the application interface to the GRID level
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
GreenView - Algorithm identification and analysis
Interpolation: eg. neighbor interpolation, bicubic interpolation, bilinear interpolation etc.Solution: Coarse to fine interpolation
The missing points will be computed using a distance weighted nonlinear interpolation that computes the value of a Vm point from four surrounding known values: V1, V2, V3 and V4.
Vi - one of the four surrounding pixels, Vi( ); di - the great circle distance between two points; dmax - the great circle distance between the furthest two pixels of the surrounding four pixels; R - average radius for a spherical approximation of the Earth (≈6371.01Km)
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
GreenView - Algorithm implementation
Execute operation on Grid infrastructure uses gProcesss platformThe entire GreenView application is divided into atomic components (jobs)Each job is executed on different nodes of the GridCreate a PDG (Process Description Graph) and an iPDG (instantieted PDG) that specify the resources to be used on execution timeThe execution ends when the job reaches DONE statusThe result is copied to the server, in a database
Example of a PDG for coarse to fine component
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
Conclusions on the experiments
On the Grid infrastructure the time execution of a job means
Time to search free nodes of the Grid
Time to send the required information
Time required to execute the job
Time required to retrieve the results from the Grid
The gap that appears in these charts is determined by
Time for searching free nodes on each site
The computation power of a node
The network traffic and bandwidth
Only the applications that require large processing data volume and the applications that are using the parallel computing power of the Grid infrastructure should be implemented as Grid applications
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
Coarse to fine interpolation – input/output example
Left image is the coarse one, with lower resolution
The result represents the same geographical area as the first one, but at a higher resolution.
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
Conclusions
GreenView is a useful tool for predicting and monitoring the temperatures over geographical areas
Even though it works, for now, only on CEE regions, the application can be extended globally
Could integrate another environment applications, such as forecast prediction
GreenView provides quick and easy access to it’s functionality through a web interface
SEE-GRID-SCI Dissemination - Timisoara 26 September 2009
Acknowledgments
This research is supported by SEE-GRID-SCI (SEE-GRID eInfrastructure for regional eScience) project, funded by the European Commission through the contract nr RI-211338.
Climate change data have been retrieved from the PRUDENCE data archive, funded by the EU through contract EVK2-CT2001-00132.
MODIS data have been produced and distributed by NASA through the EOS Data Gateway system.
Biome-BGC version 4.1.1 was provided by the Numerical Terradynamic Simulation Group (NTSG) at the University of Montana. NTSG assumes no responsibility for the proper use of Biome-BGC by others.