Integration of Simulation Results into Information Systems

1. Integration of Simulation Results into Information Systems Gio Wiederhold April 2002

2. Information Integration Information Integration provides new Information for improved Decision Making when it • presents more data • Risk: much may be irrelevant • captures new relationships • Often requires expert inter-domain knowledge • includes current sensor data • Data reflect the past only • includes predictions about future courses ******* A new, potentially major topic *******

3. Decision-making (DM) Analyze Alternatives • Current Capabilities • Future Expectations Process tasks: • List resources • Enumerate alternatives • Prune alternative • Compare alternatives now future

4. Prediction Requires Tools Ó E-mail this book, Alfred Knopf, 1997

5. o o o o o o Future information systems Combine data from the past, with current data, knowledge, and predictions into the future Assessment of the values of alternative possible outcomes

6. DM support is disjoint does not interoperate Databases Planning Science Simulation extensions to move to networked support are also disjoint Distribution

7. past now future time Intuition + x17 @qbfera ffga 67 .78 jjkl,a nsnd nn 23.5a Data integration Databases distributed, heterogeneous Current state of DM Support organized support disjointed support • Spreadsheets • Planning of allocations • Other simulations • various point assessments

8. past now future time Information Systems should alsoProject into the Futures Support of decision-making requires dealing with the futures, as well the past • Databases deal well with the past • Sensors can provide current status • Spreadsheets, simulations deal with the likely futures Information systems should be able to combine all three

9. A new Resource for Information Application Layer Mediation Layer Foundation Layer decision-makers at workstations value-added services data and simulation resources

10. past now future time Msg systems, sensors Databases, accessed via SQL or XML, CORBA compliant wrappers Simulations, accessed via SimQL and compliant wrappers Interfaces enable integration:SimQL to access Simulations

11. wrapper wrapper wrapper wrapper Engineering Weather (short-, long-term) Spreadsheets Stanford experiment, supported by DARPA & NISTPhase 1 Architectures Logistics Application Manufacturing Application SimQL access SimQL access SimQL access SQL access Test Data

12. Simulation results Simulation parameters Place of SimQL in Objective-based Planning Higher Level Objectives, Intel, OB, ROE, Commanders Guidance & Intent, Etc. Campaign Status 1 Execution Feedback Determine Status 2 Develop * Objectives Phased Sequenced Objectives *: w/Measures 3 Phase & * Sequence Objectives Prioritized Sequenced Tasks 4 Assign Task / Activity Assessment Plan 5 Develop Assessment Plan SimQL Access to Simulations Determine Required Resources Req’mts Resource Constraints 7 Assess and/or Rehearse Plan from JFACC PIP Plan Assessment Feedback

13. Types of simulation services 1. Continously executing: weather prediction • SimQL result reports best match samples 2. Execution specific to query: what-if assessment • may require HPC power for adequate response 3. Past simulations collect results in a base: materials • performs inter- or extra-polations to match query parameters 4. Combinations, i.e., 2. + 3.: top layer simulation using stored partial lower level results: weapon performance in new setting 5. Human-in-the-loop(mediated by an agent program): SAFs Note • A simulation service program can be written in any language • A simulation service must be compliant to the interface spec.

14. Enabling Interoperation • Simulations should • serve clients via SimQL by • Sharing a Model (research q.) • A query language over the model • a SimQL interface enables • independence of • application development • simulation technology develop’t • reuse of infrastructure • Objective • build information systems combining DBMS, Simulations • even with less performance, • inability to handle all problems, • but enough of them . . . Databases • serve clients via SQL by Sharing a Model (The Schema) A query language over the model the SQL interface enables • independence of application development DBMS technology development reuse of infrastructure Today • most new systems use a DBMS for data storage even with less performance, inability to handle all problems, but enough of them well enough.

15. Internet requirements • Ubiquitous access to simulations of a wide variety of types • Rapid response to parameter changes • often High-Performance computation is needed • distributed simulations with synchronization • Rapid Service Composition • High bandwidth among simulations • Acces to multiple services in parallel

16. point-in-time for situational assessment Even the present needs SimQL last recorded observations simple simulations to extrapolate data past now future time • Is the delivery truck in X? • Is the right stuff on the truck? • Will the crew be at X? • Will the forces be ready to accept delivery? Not all data are current:

17. 0.2 0.3 0.6 0.1 0.07 0.03 0.5 0.5 0.3 0.5 0.2 0.1 time 0.2 0.1 0.1 0.4 prob Use of Simulation Results Simulation results can be composed for alternative Courses-of-actions Composition should include computation and recomputation of likelihoods Likelihoods change as now moves forwards and eliminates earlier alternatives.

18. prob value 0.3 0.1 0.4 0.5 and subsequent periods 100 600 1100 500 200 200 -420 0 -820 -400 1000 2000 5000 1000 0 -6000 -3000 Values 0.1 Next period alternatives 0.1 1200 66 134 -1220 0.2 0.3 0.3 0.2 0.6 0.1 1266 -1086 0.07 0.2 0.13 0.4 past now future time The branches can be labeled with probabilities, then assessed using the outcome with values

19. ? ? 1266 ? time Msgs sensors Spreadsheets, other simulations, Databases, . . . Integrating data & planning support will make our data reusable and much more valuable A Pruned Bush Re-assess as time marches forward ! 1000 2000 5000 1000 0 100 600 1100 500 200 200 0 1200 66 past now future

20. New DecMk research questions • How to move seamlessly from the past to the future? • How can multiple futures be managed (indexed)? • How can multiple futures be compared, selected? • How should joint uncertainty be computed? • How can the NOW point be moved automatically?

21. wrapper wrapper Engineering Weather Spreadsheets Current State of SimQL research GUI collect language requirements Test Application wrapper

22. SimQL research questions • How little of the model needs to be exposed? • How can defaults be set rationally? • How should expected execution cost be reported? • How should uncertainty be reported? • Are there differences among application areas that require different language structures? • Are there differences among application areas that require different language features? • How will the language interface support effective partitioning and distribution?

23. Moving to a Service Paradigm • Server is an independent contractor, defines service • Client selects service, and specifies parameters • Server’s success depends on value provided • Some form of payment received for services x,y Databases are a current example. Simulations have the same potential.

24. Summary of SimQL A new service for Decision Making: • follows database paradigm • ( by about 25 years ) • coherence in prediction • displacement of ad-hoc practices • seamless information integration • single paradigm for decision makers • simulation industry infrastructure • investment has a potential market • should follows database industry model: Interfaces promote new industries