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Terra (MODIS)

Challenges in Transforming Space Missions Into Service Oriented ArchitecturesDan Mandl NASA/GSFC

October 4, 2006

EO-1(ALI & Hyperion)

Aqua (MODIS)

MODIS Active Fire Map

Sensor Planning Services (SPS)

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Challenges for SOA Mission Architecturewith Sub- Services

Instant real-time connections and disconnections of services and sub-servicesCost-effective mission scalability – new services can be plugged in real-timePrevent obsolescence – old services unplugged and instantly substituted for new servicesCost-effective fault tolerance – user can discover and connect to alternate services

Distributed Multi-Protocol Message BusGMSECFor Ground

cFEFor Space

Interoperability and Meta-Language ServicesSensorML IRC UDDI MOIS

Support Sub- Services

IntegratedServices

InstrumentsSatellites/Sensors

Rovers GroundSensors

Internet SpaceWire, PowerPC 750

ServiceRegistry

SPS SOS

Users

WMS WPS WFSSAS WfCS

T&C P&S Orbit Att Load Bal

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EO-1 Sensor Web Targeting National Priority Wildfires

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Identify NIFC-tracked Wildfire Incidents

Aqua or TerraMODIS data

GSFC’sScience Goal Monitor

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Fire location confirmed and selected for imaging

EROS Data Center

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UMD Natural Hazards

Investigation Team

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3

3

Active Fires Detection Map

Roberts Fire

Roberts Fire

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Roberts FireUSFS Burned Area Emergency Response (BAER) team

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SGMCorrelate latest fire location information with MODIS imagery

SGM adds target to EO-1 ground & on-orbit planning & scheduling systems and tasks EO-1

L1 Data

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MODIS Rapid ResponseActive Fire Detections

EO-1 Advanced Land ImagerBurn Scar Image

On 11-2-03, the NASA Wildfire SensorWeb was employed to collect data on the burn scars resulting from the Simi Valley, Val Verde and Piru fires in Southern California. MODIS active fire detections for the duration of the event were used to target an acquisition by the ALI and Hyperion instruments onboardEO-1. Such data are employed by the USDA Forest Service for Burned Area Emergency Rehabilitation mapping. BAER maps are used to target high risk areas for erosion control treatments.

In this image, burned areas appear red while the unburned areas appear green. The blue burn perimeter vector is based on ground data.

Example of Rapid Delivery of Information for Decisions Using EO-1 Sensor Web

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Various EO-1 Sensor Web Experiments Conducted

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Key Capabilities Implemented to Enable EO-1 Sensor Webs & Support “Backend” of SPS

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CASPER Planner – response in 10s of minutes

SCL – response in seconds with rules, scripts

EO 1 Conventional Flight Softwarereflexive response

ASE Flight Software Architecture

Onboard Science

Band ExtractionObservationPlanner

Spacecraft Hardware

Raw Instrument Data

ImageOverflight

Times

High level S/C State Information

Plans of Activities(high level)

Sensor Telemetry

Commands (low level)S/C State

Control Signals (very low level)

ObservationGoals

L2 – Model-based Mode Identification &

ReconfigurationAutonomousSciencecraft

ConventionalSystems

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Original Operations Flow to Task Sensors & Access Science Data

GSFCUSGS

Engineer

MOPSS

CMS

ASIST

ScienceProcessing

telemetry

commands

FDSS

White Sands

stationin-views Mission

Planner

trackingdata

overflights

contactsrawsciencedata

targets, engineering requeststargets

weekly schedule

selected weekly schedule

daily activities

daily commands

processedsciencedata

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Revised Operations Flow To Task Sensors and Access Science Data Using Onboard Autonomy

WWW

GSFCUSGSJPL

ASPEN

FDSS

White Sands

ASIST

rawsciencedata

trackingdata

goals

telemetry

overflights

weekly goals

targets, engineering requests

targets

targets

daily goals

ScienceProcessing

EO-1

CASPER

ScienceProcessing

SCLactivities

commands

sciencedata

goals

stationin-views

contacts

processedsciencedata

Onboard EO-1

Note that engineer and mission planner removed

SPS

SOA Users

targets

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Vision: Sensor Web Enablement via a Service Oriented Architecture (SOA)

Land Remote Sensing Observation Data

Scientists

Earth Weather Data

Space Weather Data

Sensor Planning Services (SPS)

Sensor Alert Services (SAS)

Sensor Registry Services (SRS)

Sensor Observation Services (SOS)

Work Flow Chaining Services (WfCS)

Users do not task satellite Users focus on products they need

•Implicit /Transparent Satellite/Asset Tasking•Automated Just-In-Time Processing

•User-Driven Custom Processing•User Notification/Delivery

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Product Request – Step 1

1. Fire2. Water3. Ice…

Area Of Interest

+

User

DecisionSupportSystem

ebRIM

Discovery

UAV

MODIS

EO1SPS

Register

ASPENPlanner /Scheduler

Ground Station

CASPEROnboard Planner

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Product Processing – Step 2

1. Fire2. Water3. Ice…

Area Of Interest

+

User

DecisionSupportSystem ebRIM

Discovery

SensorObservationService

Level 0 &Level 1GST

Ground Station

CASPEROnboard Planner

WebProcessingService

WebCoverageService

BPEL Automation

WebFeatureService

Get 3 bandsFire ClassifierNYC AreaStorage L0 & L1Process

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Product Notification – Step 3

1. Fire2. Water3. Ice…

Area Of Interest

+

User

DecisionSupportSystem ebRIM

Discovery

SensorObservationService

Level 0 &Level 1GST

Ground Station

CASPEROnboard Planner

WebProcessingService

WebCoverageService

BPEL Automation

WebFeatureService

Get 3 bandsFire ClassifierNYC AreaStorage L0 & L1Process

SensorAlertService

Content Syndication

Data Feed

Email/IM Notification

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Product Retrieval/Display – Step 4

1. Fire2. Water3. Ice…

User

DecisionSupportSystem ebRIM

Discovery

SensorObservationService

Level 0 &Level 1GST

Ground Station

CASPEROnboard Planner

WebProcessingService

WebCoverageService

BPEL Automation

WebFeatureService

Get 3 bandsFire ClassifierNYC AreaStorage L0 & L1Process

Query/Retrieval

SensorWeb EnabledData Node

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Another View of SOA Multi-Mission Architecture

GMSECDecision Support

System

Distributed Multi-Protocol Message Bus

(SWE) Data Node

EO1

SupportServicesSupportServicesSupportServices

Users

(SWE) Data NodeRover

(SWE) Data NodeInstruments

IRC

(SWE) Data NodeGround Remote

Sensors

(SWE) Data NodeTERRA

(SWE) Data Node

AQUA

ebRIMRegistry

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Example of work on Sub-service - SBIR-1 Work on SOA Planning and Scheduling

Universal P&S System (UPASS) built by Emergent Space Technologies • Utilizes Professional Open-Source JBoss J2EE Application Server• Distributed clustered environment has a high-reliability, high-availability SOA

with load balancing, automatic failovers, and no single points of failure• API allows developers to build plug-in objects and develop custom services

and interfaces that interact with standard UPASS services• GMSEC translator allows all services to be accessed from the GMSEC bus

UPASS Architecture

Relational Database/Object Persistence

P&S Engine

UPASS Services

UPASS GUI

P&S Algorithm

X

P&S Algorithm

X

P&S Algorithm

X

UPASS API

Task Type

X

Resource Type

X

Task Type

X

Task Type

X

Resource Type

X

Resource Type

X

External Services and

Interfaces

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SOA Enterprise - Web 2.0

NASA DHS

DOD

Interoperable UserCommunities(OWS-4 Demo)

Data NodesData Nodes

USCG

NORTHCOMCivil Air Patrol

EO1

Terra

Aqua… CBP

Sea Nodes

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Funded Efforts

Two recent 3 year awards from AIST ESTO call for proposal• An Inter-operable Sensor Architecture to Facilitate Sensor Webs in Pursuit of

GEOSS• Key topic – Interoperability and demonstration of service oriented architecture

for space missions and sensor webs• PI: Dan Mandl - 3 year effort

• Using Intelligent Agents to Form a Sensor Web for Autonomous Mission Operations • Key topic distributed mission control• Extend effort depicted on slide 16 in which ST-5 components turned into

mobile agents for use onboard spacecrafts with GMSEC/CFS• PI: Ken Witt/ISR Co-I Dan Mandl/GSFC – 3 year effort

Goddard Institute for Systems, Software and Technology Research (GISSTR) contract effort being applied by Institute of Scientific Research (ISR) to:• Building GMSEC compliance tester for new components• Help to synergize other ESTO awards with above mentioned awards• Integrate Real-time Object Modeling Environment (ROME) (another service

developed on ST-5) in collaboration with Capitol College into TRMM, GLAST and MMS

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Funded Efforts

West Virginia Challenge Grant (set-aside) to be applied to develop Sensor Modeling Language (SensorML) schemas for follow-on SOA efforts• SensorML schemas will describe sensor capabilities and once

put in online registries, will enable discovering of those capabilities on the Internet

Open Geospatial Consortium (OGC) ongoing testbed effort OGC Web Services 4 (OWS-4) June 2006- December 2006Universal Planning and Scheduling System (UPASS) SBIR-1 (Emergent Space Technologies)• Submitted SBIR-2 proposal

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Conclusion

This approach can reduce cost for missions by• Use of automation• Reducing system obsolescence• Providing cost-effective scalability• Providing cost-effective fault tolerance

This approach increases data availability to users • Just-In-Time Processing• Custom Data Production (No Scientist in the Loop)• Data Feed Syndication (Leverage Existing Standards)

• Aggregation PossibleThis approach is user focused• Support new classes of Users

• Non-scientific (DHS, DOD…)This approach provides interoperability with other communities• Support For Disaster Relief / Emergency Response• Increase Return on Existing Data • More Science Opportunities