1 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)

2 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 OrbitAtt Load Bal

3 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 EROS Data Center 4 UMD Natural Hazards Investigation Team Active Fires Detection Map Roberts Fire 1 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

4 MODIS Rapid Response Active Fire Detections EO-1 Advanced Land Imager Burn Scar Image On , 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

5 Various EO-1 Sensor Web Experiments Conducted

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

7 CASPER Planner – response in 10s of minutes SCL – response in seconds with rules, scripts EO 1 Conventional Flight Software reflexive response ASE Flight Software Architecture 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) Observation Goals L2 – Model-based Mode Identification & Reconfiguration Autonomous Sciencecraft Conventional Systems

8 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

9 Revised Operations Flow To Task Sensors and Access Science Data Using Onboard Autonomy WWW GSFC USGSJPL ASPEN FDSS White Sands ASIST raw science data tracking data goals telemetry overflights weekly goals targets, engineering requests 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

10 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

11 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

12 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 bandsFire Classifier NYC Area Storage L0 & L1 Process

13 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 bandsFire Classifier NYC Area Storage L0 & L1 Process Sensor Alert Service Content Syndication Data Feed /IM Notification

14 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 bandsFire Classifier NYC Area Storage L0 & L1 Process Query/ Retrieval Sensor Web Enabled Data Node

15 Another View of SOA Multi-Mission Architecture GMSEC Decision 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 ebRIM Registry

16 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 UPASS API Task Type X Resource Type X Task Type X Resource Type X External Services and Interfaces

17 SOA Enterprise - Web 2.0 NASADHS DOD Interoperable User Communities (OWS-4 Demo) Data Nodes USCG NORTHCOM Civil Air Patrol EO1 Terra Aqua… CBP Sea Nodes

18 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

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

20 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