Grid Portal Development for Sensing Data Retrieval and Processing Diego Arias, Mariana Mendoza, Fernando Cintron, Kennie Cruz, and Wilson Rivera Parallel.

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Presentation transcript:

Grid Portal Development for Sensing Data Retrieval and Processing Diego Arias, Mariana Mendoza, Fernando Cintron, Kennie Cruz, and Wilson Rivera Parallel and Distributed Computing Laboratory University of Puerto Rico at Mayaguez GCE06-SC06 – Tampa, FL November 12-13, 2006

Wilson Rivera, Parallel and Distributed Computing UPRM 2 Agenda  Introduction  CASA: Collaborative and Adaptive Sensing of the Atmosphere –NSF: EEC ; UMass, UPRM, OU, CSU  WALSAIP: Wide Area Large Scale Automated Information Processing –NSF: CISE-CNS ; UPRM  Remarks and conclusions

Wilson Rivera, Parallel and Distributed Computing UPRM 3 Introduction: The PDC Laboratory

Wilson Rivera, Parallel and Distributed Computing UPRM 4 Introduction: PDCLab Research Optimized e-Resource Administration Automated Composition Signal Processing Operators Adaptive Provisioning and Orchestration of Grid Services PDC Portal WALSAIP Portal Information Dispersal STB Portal CenSSIS Portal Semi-Analytical Inversion Model

Wilson Rivera, Parallel and Distributed Computing UPRM 5 Introduction: PDCLab Grid Testbed

Wilson Rivera, Parallel and Distributed Computing UPRM 6  CentOS 4.2  Globus Toolkit –OpenPBS –Torque –PosgreSQL –Apache Ant version –Java SDK version 1.5 –Jakarta Tomcat version Introduction: PDCLab Grid Testbed

Wilson Rivera, Parallel and Distributed Computing UPRM 7 Introduction: PDCLab Grid Testbed

Wilson Rivera, Parallel and Distributed Computing UPRM 8 Agenda IIntroduction CCASA: Collaborative and Adaptive Sensing of the Atmosphere –N–NSF: EEC ; UMass, UPRM, OU, CSU WWALSAIP: Wide Area Large Scale Automated Information Processing –N–NSF: CISE-CNS ; UPRM RRemarks and conclusions

Wilson Rivera, Parallel and Distributed Computing UPRM 9 CASA: Collaborative and Adaptive Sensing gap - earth curvature prevents 72% of the troposphere below 1 km from being observed.

Wilson Rivera, Parallel and Distributed Computing UPRM 10 Academic Institutions/Researchers Government Media Service/Request Data Service/Request Data CASA: Student Testbed (STB)

Wilson Rivera, Parallel and Distributed Computing UPRM 11 CASA: STB Grid Portal Interface

Wilson Rivera, Parallel and Distributed Computing UPRM 12 CASA: STB Grid Portal Interface

Wilson Rivera, Parallel and Distributed Computing UPRM 13 CASA: Information Dispersal Algorithm

Wilson Rivera, Parallel and Distributed Computing UPRM 14 CASA: Data Management Portlets

Wilson Rivera, Parallel and Distributed Computing UPRM 15 CASA: Weather Information Portlets

Wilson Rivera, Parallel and Distributed Computing UPRM 16 CASA: Job Submission

Wilson Rivera, Parallel and Distributed Computing UPRM 17 Agenda IIntroduction CCASA: Collaborative and Adaptive Sensing of the Atmosphere –N–NSF: EEC ; UMass, UPRM, OU, CSU WWALSAIP: Wide Area Large Scale Automated Information Processing –N–NSF: CISE-CNS ; UPRM RRemarks and conclusions

Wilson Rivera, Parallel and Distributed Computing UPRM 18 WALSAIP: Signal Based Information Processing System Physical Environment Physical Environment Observables Signals Data Sensors Effectors Signal Processing Information Processing Information Knowledge Processing Knowledge Decision System Intelligence

Wilson Rivera, Parallel and Distributed Computing UPRM 19 SAS: Sensor Array Structures DRS: Data Representation System CSPS: Computational Signal Processing System SDP: Signal Data Post-processing SCS: Signal Conditioning System RDS: Raw Data Server CDS: Computed Data Server IRS: Information Rendering System DRSSCSSAS RDSCDSCSPSSDP IRS Pre-processing Stage Post-processing Stage Processing Stage SAS INTERNET WALSAIP: Conceptual Framework Design

Net-Centric MIMO Services Net-Centric MIMO Services DRS SCSSAS CSPS SDP IRS SDP IRS DRS SCS SAS RDS DBMS RDS DBMS CDS DBMS CIP over a Cyberspace Infrastructure CSPS CIP: Computational and Information Processing

Net-Centric MIMO Services Net-Centric MIMO Services DRS SCSSAS CSPS SDP IRS SDP IRS DRS SCS SAS RDS DBMS RDS DBMS CDS DBMS CIP over a Cyberspace Infrastructure CSPS CIP: Computational and Information Processing

Net-Centric MIMO Services Net-Centric MIMO Services DRS SCSSAS CSPS SDP IRS SDP IRS DRS SCS SAS RDS DBMS RDS DBMS CDS DBMS CIP over a Cyberspace Infrastructure CSPS CIP: Computational and Information Processing

Net-Centric MIMO Services Net-Centric MIMO Services DRS SCSSAS CSPS SDP IRS SDP IRS DRS SCS SAS RDS DBMS RDS DBMS CDS DBMS CIP over a Cyberspace Infrastructure CSPS CIP: Computational and Information Processing

Wilson Rivera, Parallel and Distributed Computing UPRM 24 WALSAIP’s Jobos Bay NERR Environmental Surveillance and Monitoring Jobos Bay UPRM INTERNET RF-Link MEP-510 MEP-410 RS-232 Base Station MBR410 Local Host Data Base on Host Database Querying and Processing Engine Sensing-Data SensorNode1 SensorNode5 Cooked-data 1-Jun :02:00-humidity-data.txt 1-Jun :02:00-humidity-meta.txt Remote User

Wilson Rivera, Parallel and Distributed Computing UPRM 25 WALSAIP: Grid Portal Interface

Wilson Rivera, Parallel and Distributed Computing UPRM 26 WALSAIP: Grid Portal Interface

Wilson Rivera, Parallel and Distributed Computing UPRM 27 WALSAIP: Grid Portal Interface

Wilson Rivera, Parallel and Distributed Computing UPRM 28 Agenda IIntroduction CCASA: Collaborative and Adaptive Sensing of the Atmosphere –N–NSF: EEC ; UMass, UPRM, OU, CSU WWALSAIP: Wide Area Large Scale Automated Information Processing –N–NSF: CISE-CNS ; UPRM RRemarks and conclusions

Wilson Rivera, Parallel and Distributed Computing UPRM 29 Remarks and Conclusions  Grid portals for large scale applications –Sensing of the Atmosphere (CASA) –Environmental Surveillance and Monitoring (WALSAIP)  Grid services provided via portlets –Distributed data management –Information dispersal –Weather services –Multiple job submission –Service orchestration  Future work –Remote instrumentation via grid portals –Integration to community grid infrastructures (Teragrid, etc….)