AIST Program Sensor Web Meeting Summary of Results Working Group Middleware II Phil Paulsen April 3,...

AIST Program Sensor Web Meeting Summary of Results

Working Group Middleware II

Phil Paulsen

April 3, 2008

22 Sensor Web Meeting, Working Group Middleware II

April 3, 2008

Use Case Brainstorming Summary

1) Coastal Ocean Modeling, Data Assimilation and Prediction (Yi Chao) 2) Dynamic Soil Sampling (Wei Ye)3) Dynamic Plant Monitoring (Wei Ye)4) Water Quality Monitoring (Wei Ye)5) Lightning (Prasanta Bose)6) Wildfire Sensor Web (Dan Mandl)7) Seamlessly Download Data (Mohammed Atiquzzaman)8) Dynamically taskable sensors (Phil Paulsen) 9) Operationally Responsive Space Element Tasking (Phil Paulsen)10) Collaborative Science Resource Allocation (Phil Paulsen)11) North American Net Primary Production comparison using automated

workflow generation (Robert Morris)12) Data Mining and Automated Planning for Mobile Instrument Operation (Nikunj

Oza)13) Hurricane Workflows (Stuart Frye)


April 3, 2008

Fire Workflow Primary Use Case Overview

• Workflows, Dan Mandl, Sensor Coordination• Abstract steps needed to produce final data product from an ad hoc set of sensors

– Discovery

– Instantiation of model

– Workflow specification and generation

– Workflow execution

• Summary– Graphical composition of of reusable workflow elements (mashups)

• Highlights– Hides details of manipulating sensor web for user

– Reduces entry barrier making is more accessible

– Increases efficiency and reduces cost

– Increases science value


April 3, 2008

WorkflowsMandl/Frye


April 3, 2008

Workflow Use Case:Automated Product Generation

• Emergency• Discover available sensor

assets over Internet• Wizard assembles possible

workflows• Workflow engine controls

creation of multi-sensor products, processing and delivery to user desktop

Geo-Emergency

First responderTheme Based Tasking Request Theme: Loc: Priority:

Witch Fire (SoCal) Oct 23, 2007

Result: Efficient / timely use of assets

Wizard

Workflow Engine


April 3, 2008 6

Sensor Planning Service (SPS)

EO-1Satellite

Sensor Observation Service (SOS)

Cappelaere/Vightel

Level 0 Science Process

Tran, Chien/JPL

Tran, Chien/JPL

Alexander/GSFC Tran, Chien/JPL

Web Processing Service (WPS)

Tran, Chien/JPLLevel 1G or Level 0.5

Pixels and heat values

Web Coverage Service –Transformation

(WCS-T)

JPEG

Zhao/GMU

Community Map Builder client (on eo1.geobliki.com)

Web Map Service (WMS) JPEG

Map

Publish composite JPEG map with data overlay (map with fire locations)

Cappelaere/Vightel

EO-1 Fire Sensor Web Workflow• Potential savings

– Originally, USGS charged $2000 to task EO-1 and perform L0 and L1G data processing for customers ($1250 now)

– Potential cost reduced to under $100 since tasking EO-1, L0 and L1G data processing automated

Cappelaere/Vightel

Level 1G Process

Classify hot pixels

Level 0.5 Process

L. Di, Zhao/GMU

BPEL Workflow Engine

1

2

34

5


April 3, 2008

Asynchronous CommunicationAsynchronous

Communication

A WfCS Implementation

WfCSAtom PublicationMessage (Entry)

Clearwater 1.0

Murkywater 1.0

Muddywater 1.0

1. Workflows are uploaded and stored in WfCS database2. Workflows are versioned automatically and assigned

Definition numbers3. An Atom/XML message is sent to the WfCS with the

appropriate parameters to execute the corresponding Workflow/Definition

4. Asynchronous messaging can occur while a workflow is being executed, providing current status

5. A notification message can be sent upon completion

Near Immediate Responsewith Process ID URL

HTTP GET to Process URLReturns current status

Workflow Database

Process 1Process 2

…Process N

Process 1Process 2

…Process N

User/Other Service

Workflow = SensorML Process Chain


April 3, 2008 88Sensor Web Meeting, Working Group Middleware II

Coastal Ocean Use Case Overview

• Name, POC: Coastal Ocean Modelling, Data Assimilation and Prediction, Payman Arabshahi

• Goal: To improve ocean modeling in coastal regions by making sustained measurements with increased accuracy and spatial/temporal resolution.

• Summary: Provide ocean and climate change scientists with improved climate change model outputs (ROMS outputs) by including integrated in-situ and space based sensor data, thus increasing accuracy and spatial/temporal resolution of model outputs.

• Highlights: future contributions to Earth science– JASON-1 - measures the ocean surface topography (current)– QuickSCAT - measures wind speed and direction information over oceans (current)

• Part of AIST demonstration– OSTM - measures sea surface height (future)– Aquarius - measures global sea surface salinity (future)

• Missions in NRC Decadal Survey in the 2013-2016 time frame– SWOT- Measures ocean, lake and river water levels - Ka band wide swath radar, C band radar– XOVWM - measures sea surface wind vectors for weather and ocean ecosystems

Predictive Models

Virtual SpaceSupercomputing

Sensor Web SystemSpace, In-Situ

(Oceans)

DataAssimilation Adaptive

Sampling


April 3, 2008

OceanArabshahi


April 3, 2008

Plant Monitoring Use Case Overview

• Multimodal Plant Monitoring– POC: Wei Ye, Categorization: sensor management

• Goal: – Multimodal sensing of plants bloom in response to precipitation.

• Summary– Capture the dynamic response of plants to rainfalls

• Sap flow sensors, imaging sensor, weather station

– Dynamically adjust sampling rates of sensors when relevant environmental events are detected

• Day time (regular rates) and night time (power down), detected precipitation (high rates)

• Highlights– Event-triggered reconfiguration of in-situ environmental sensors


April 3, 2008

Wei YePlant Monitoring


April 3, 2008

Use Case Lessons Learned

• Identify “collective results” of looking at several use case– Communications system management– Sensor management– Work flow management

• Implications for next steps– The majority of the cases related to workflow management – this area appears to

be offer more opportunity for development

• Suggestions on how to promote use cases– Use the “value chain” analysis (more science? Better science? Cheaper

science?)– Emphasis on simplification through abstraction…– Use animation / DVD– Live demonstration

• Provide feedback to ESTO AIST team– The use case work should not wait another year – this should be an ongoing

area of interest


April 3, 2008

New Sensor Web Features, Needs

• Identify new features or benefits– Inclusion of a broader discussion of interoperability

• List any new AIST needs


April 3, 2008

Recommendations

• Suggestions for ESTO next steps– Continue to refine use cases

• Closer look at decadal survey relevance

– Perform value chain analysis

– Perform mashups of cross cutting use cases• Crosscutting PI teams

• Identify specific individuals for sensor web follow up

• How can AIST or info systems in general, influence planning for Decadal Survey missions– Bring John Garstka to the “big” meeting with the HQ mission managers

AIST Program Sensor Web Meeting Summary of Results Working Group Middleware II Phil Paulsen April 3,...

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