# Presentation: 134206

## Challenges in Transforming Space Missions Into Service Oriented ArchitecturesDan Mandl NASA/GSFCOctober 4, 2006

**Terra (MODIS)**

***Challenges in Transforming Space Missions Into Service Oriented Architectures******Dan Mandl NASA/GSFC******October 4, 2006***

**EO-1**
**(ALI & Hyperion)**

**Aqua (MODIS)**

**MODIS Active Fire Map**

- Sensor Planning Services (SPS)

**Notes:**
This is the famous “Earthrise” picture from Apollo

## Challenges for SOA Mission Architecturewith Sub- Services

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

**Distributed Multi-Protocol Message Bus**

**GMSEC**
**For Ground**

**cFE**
**For Space**

**Interoperability and Meta-Language Services**

**SensorML**

**IRC                  UDDI         MOIS**

**Support Sub- Services**

**Integrated**
**Services**

**Instruments**

**Satellites/**
**Sensors**

**Rovers**

**Ground**
**Sensors**

**Internet**

**SpaceWire, PowerPC 750**

**Service**
**Registry**

**SPS**

**SOS**

**Users**

**WMS**

**WPS**

**WFS**

**SAS**

**WfCS**

**T&C**

**P&S**

**Orbit**

**Att**

**Load Bal**

## EO-1 Sensor Web Targeting National Priority Wildfires

**1**

**Identify NIFC-tracked Wildfire Incidents**

**Aqua or Terra**
**MODIS data**

***GSFC’s***
***Science Goal Monitor***

**2**

**Fire location confirmed and selected for imaging**

**4**

- UMD Natural Hazards Investigation Team

- 5

**3**

**3**

**Active Fires Detection Map**

***Roberts Fire***

***Roberts Fire***

**1**

***Roberts Fire***
**USFS Burned Area Emergency Response (BAER) team**

- 6

***SGM***

**Correlate 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

**Notes:**
SGM accesses NIFC and the active fire map to determine present fire location
Web accessible Integrated NIFC Database
Terra and Aqua S/C MODIS data (produced by MODIS rapid Fire Workstation - UMCP)
SGM then initiates the p&S systems for targeting these systems (some on board  w/CASPER and MOPS does another piece etc etc)
Target ALI and Hyperion on the fire of interest
Can be done quickly - as soon as one orbit
Within 24-48 hours BAER tem gets info. To do rehabilitation.

Before this SW experiment nominal turn around was 2 weeks.

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

- MODIS Rapid Response
- Active Fire Detections

- EO-1 Advanced Land Imager
- Burn 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 onboard
- EO-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**

**Various EO-1 Sensor Web Experiments Conducted**

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

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

## ASE Flight Software Architecture

**SCL – response in seconds with rules, scripts**

**EO 1 Conventional Flight Software****reflexive response**

**Onboard Science**

**Band Extraction**

**Observation****Planner**

**Spacecraft Hardware**

- Raw Instrument Data

- Image

- Overflight 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 & ****Reconfiguration**

**Autonomous****Sciencecraft**

**Conventional**
**Systems**

**Notes:**
Traditional three layer architecture
Agent software above the dotted line
L2 model-based diagnosis from NASA Ames
SCL provides robust task execution – responds within 1s
CASPER mission replanning
Upper right – science event detection, tracking, summarization
Upper left – only part not automated onboard spacecraft – orbit determination, uses GPS constellation

## Original Operations Flow to Task Sensors & Access Science Data

**GSFC**

**USGS**

**Engineer**

**MOPSS**

**CMS**

**ASIST**

**Science**
**Processing**

**telemetry**

**commands**

**FDSS**

**White Sands**

**station**
**in-views**

**Mission**
**Planner**

**tracking**
**data**

**overflights**

**contacts**

**raw**
**science**
**data**

**targets, engineering requests**

**targets**

**weekly schedule**

**selected weekly schedule**

**daily activities**

**daily commands**

**processed**
**science**
**data**

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

**WWW**

**GSFC**

**USGS**

**JPL**

**ASPEN**

**FDSS**

**White Sands**

**ASIST**

**raw**
**science**
**data**

**tracking**
**data**

**goals**

**telemetry**

**overflights**

**weekly goals**

**targets, engineering requests**

**targets**

**targets**

**daily goals**

**Science**
**Processing**

**EO-1**

**CASPER**

**Science**
**Processing**

**SCL**

**activities**

**commands**

**science**
**data**

**goals**

**station**
**in-views**

**contacts**

**processed**
**science**
**data**

**Onboard EO-1**

**Note that engineer and**
** ****mission planner removed**

-    SPS

**SOA Users**

**targets**

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

**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

## Product Request – Step 1

**Product Request – Step 1**

- 1. Fire
- 2. Water
- 3. Ice...

**Area Of Interest**

- +

**User**

**Decision**
**Support**
**System**

- ebRIM

**Discovery**

**UAV**

**MODIS**

**EO1**
**SPS**

**Register**

**ASPEN**
**Planner /**
**Scheduler**

**Ground**
** ****Station**

**CASPER**
**Onboard Planner**

## Product Processing – Step 2

**Product Processing – Step 2**

- 1. Fire
- 2. Water
- 3. Ice...

**Area Of Interest**

- +

**User**

**Decision**
**Support**
**System**

- ebRIM

**Discovery**

**Sensor**
**Observation**
**Service**

**Level 0 &**
**Level 1**
**GST**

**Ground**
** ****Station**

**CASPER**
**Onboard Planner**

**Web**
**Processing**
**Service**

**Web**
**Coverage**
**Service**

- BPEL Automation

**Web**
**Feature**
**Service**

**Get 3 bands**

**Fire Classifier**

**NYC Area**

**Storage**

**L0 & L1**
**Process**

## Product Notification – Step 3

**Product Notification – Step 3**

- 1. Fire
- 2. Water
- 3. Ice...

**Area Of Interest**

- +

**User**

**Decision**
**Support**
**System**

- ebRIM

**Discovery**

**Sensor**
**Observation**
**Service**

**Level 0 &**
**Level 1**
**GST**

**Ground**
** ****Station**

**CASPER**
**Onboard Planner**

**Web**
**Processing**
**Service**

**Web**
**Coverage**
**Service**

- BPEL Automation

**Web**
**Feature**
**Service**

**Get 3 bands**

**Fire Classifier**

**NYC Area**

**Storage**

**L0 & L1**
**Process**

**Sensor**
**Alert**
**Service**

**Content Syndication**
**Data Feed**

**Email/IM Notification**

## Product Retrieval/Display – Step 4

**Product Retrieval/Display – Step 4**

- 1. Fire
- 2. Water
- 3. Ice...

**User**

**Decision**
**Support**
**System**

- ebRIM

**Discovery**

**Sensor**
**Observation**
**Service**

**Level 0 &**
**Level 1**
**GST**

**Ground**
** ****Station**

**CASPER**
**Onboard Planner**

**Web**
**Processing**
**Service**

**Web**
**Coverage**
**Service**

- BPEL Automation

**Web**
**Feature**
**Service**

**Get 3 bands**

**Fire Classifier**

**NYC Area**

**Storage**

**L0 & L1**
**Process**

**Query/**
**Retrieval**

**Sensor**
**Web Enabled**
**Data Node**

## Another View of SOA Multi-Mission Architecture

- GMSECDecision Support
-  System

**Distributed Multi-Protocol Message Bus**

- (SWE)
- Data Node
- EO1

- Support
- Services

- Support
- Services

- Support
- Services

**Users**

- (SWE) Data
-  Node
- Rover

- (SWE) Data Node
- Instruments
- IRC

- (SWE) Data Node
- Ground Remote
- Sensors

- (SWE)
- Data Node
- TERRA

- (SWE)
- Data Node
- AQUA

- ebRIMRegistry

## 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

## SOA Enterprise - Web 2.0

- NASA

- DHS

- DOD

- Interoperable User
- Communities
- (OWS-4 Demo)

- Data Nodes

- Data Nodes

- USCG

- NORTHCOM

- Civil Air Patrol

- EO1

- Terra

- Aqua...

- CBP

- Sea Nodes

## 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

## 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 2006
- Universal Planning and Scheduling System (UPASS) SBIR-1 (Emergent Space Technologies)
- Submitted SBIR-2 proposal

## 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 Possible
- This 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