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Impact: Fault Tolerance and High Confidence Embedded Systems Design

Impact: Fault Tolerance and High Confidence Embedded Systems Design. Gabor Karsai Vanderbilt University, ISIS. Center impact (1): New Start Research Project. Multi-University Research Initiative:

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Impact: Fault Tolerance and High Confidence Embedded Systems Design

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  1. Impact: Fault Tolerance and High Confidence Embedded Systems Design Gabor Karsai Vanderbilt University, ISIS

  2. Center impact (1): New Start Research Project • Multi-University Research Initiative: • Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems • Participants: Berkeley, CMU, Stanford, VU • Objectives: • Development of a theory of deep composition of hybrid control systems with attributes of computational and communication platforms • Development of foundations for model-based software design for high-confidence, networked embedded systems applications. • Support of high-level reusability of tools in domain- specific tool chains • Web: https://wiki.isis.vanderbilt.edu/hcddes/ "Impact: HCDES/MICTES", Karsai

  3. Requirement Specification Control Design HW Arch. Design Software Architecture Component Design System Arch. Design SW Deployment Embedded Control System Design Flow "Impact: HCDES/MICTES", Karsai

  4. EVIDENCE Design Flow: Tools and Analysis Requirement Specification RA Control Design FD HwA Software Architecture HW Arch. Design Functional Mod/Sim HW Pwr/ Perf Est SwA System Arch. Design Component Design Arch Mod/Sim SY CD Code Gen.Verif. Latency/RT Analysis DPL Alloc./Sched. Analysis SW Deployment "Impact: HCDES/MICTES", Karsai

  5. Overall Undertaking • Development of component technologies in all areas (theory/design/tools) • Incrementally building a tool chain for a selected domain (UAV flight and mission control) • Demonstration of control software development with the tool chain • Experiments "Impact: HCDES/MICTES", Karsai

  6. SL/SF Control Design – A DSML View Objective: Define the control laws to meet requirementsPlatform: SL/SF-like modeling language, (Ptolemy 2; GME) Tools:SL/SF Model Builder+Simulator(Ptolemy 2) Requirements Simulink/StateFlow (DSMLSL/SF) Requirements – Functional Design Mapping (DSMLSL/SF) Requirement Specification Requirements - Functional Design Mapping "Impact: HCDES/MICTES", Karsai

  7. Comp/Comm Platform Model Robust Control Design Control Design: Approaches Goal: Design controller behavior satisfying all requirements • Embedded Systems Modeling and Deep Compositionality • Hierarchies of Robust Hybrid and Embedded Systems • Verification and Validation of Conservative Approximations • Adaptive Control Architectures for Uncertainty Handling • Quantization, finite word length, round-off errors • Modality • Limited resources, resource sharing • Concurrency models, scheduling • Limited communication bandwidth, networking Plant Model Controller Design • Mathematical model of the Plant • Design of a lin. or non-lin. controller satisfying stability/performance requirements • Simulations/refinement • Uncertain dynamics, unknown non-linearities • Fault effects, sensing errors • Fault adaptive control • Robust analysis, (SDP, LMI), • Simulations "Impact: HCDES/MICTES", Karsai

  8. Addition to the Design Flow Requirement Specification RA Control Design FD HwA Component Design HW Arch. Design Functional Mod/Sim HW Pwr/ Perf Est SwA Software Architecture System Arch. Design Arch Mod/Sim SY CD Code Gen.Verif. Latency/RT Analysis DPL Alloc./Sched. Analysis SW Deployment "Impact: HCDES/MICTES", Karsai

  9. SW Architecture Design Objective: Optimize the SW architecture by selecting a component model and by allocating functions to components.Platform: MoC-s Tools:GME, GReAT, DESERT, Ptolemy-2,… Simulink/StateFlow (DSMLSL/SF) Component Model SW Architecture Model (DSMLSL/SF,CM) SL/SF SwA Functional Architecture – SW Architecture Mapping "Impact: HCDES/MICTES", Karsai

  10. Safe Composition Platform Meta Generator Component Models (MoC) Metamodeling Metamodeling Generator Metamodeling Semantic Anchoring Software Architecture Verification Goal: design software architecture using well understood composition platforms that allow verification of properties using analysis or “correct-by-construction” property guarantees. Model Translators Synthesis Tools Model Translators Control/Functional Architecture Software Architecture Analysis Models - Simulators Analysis Models - Simulators • Embedded Software Composition Platforms • Heterogeneous MoC-s • Actor Models • Ptolemy-II based runtime support • Formally specified semantics • Compositional semantics for heterogeneous systems "Impact: HCDES/MICTES", Karsai

  11. Addition to the Design Flow Requirement Specification RA Control Design FD HwA Component Design HW Arch. Design Functional Mod/Sim HW Pwr/ Perf Est SwA Software Architecture System Arch. Design Arch Mod/Sim SY CD Code Gen.Verif. Latency/RT Analysis DPL Alloc./Sched. Analysis SW Deployment "Impact: HCDES/MICTES", Karsai

  12. SW Component Design Objective: Design and implement SW for components satisfying behavior defined by control laws.Platform: Component Implementation Languages (Java, C++, Other..) Tools: Generators (RT-Workshop; GReAT), Compilers, WCET Analyzers Simulink/StateFlow (DSMLSL/SF) Component Implementation Lng. SW Components SL/SF CM Functional blocks – SW Component Mapping "Impact: HCDES/MICTES", Karsai

  13. Metamodeling DS Generator Meta Generator Generator Metamodeling Metamodeling Software Component Verification Goal: prove that the component software behaves as intended under all foreseeable operating conditions. Semantic Anchoring Component Behavior Model Component Implementation Code Analysis • Model Integrated Computing • Metamodeling • Model-based code generation • Meta-model-based tesing of code generators • Automated Source Code Verification and Testing • Model-based test generation • Advanced static analysis • Model refinement • Model verification • Model compilation or hand coding • Static analysis • Test-based verification "Impact: HCDES/MICTES", Karsai

  14. RTOS System Configuration Design Objective: Design System configuration that meets cost/reliability/power requirements.Platform: Comm-links; RTOS, Comp. Middleware Tools:GME, RTOS, Comp. Middleware tools HW Architecture (DSMLHW) RTOS Model (DSMLRTOS) System Model (DSMLSYSTEM) HwA System Modeling: HW-Comm-RTOS mapping "Impact: HCDES/MICTES", Karsai

  15. SW Deployment Objective: Optimize System architecture by allocating SW components to RTOS Tasks and Communication Channels.Platform: Composition Model Tools: GME, DESERT, Timing Analysis,… SW Architecture (DSMLSL/SF,CM) System Model SW Deployment Model (DSMLSL/SF,CM) Arch. Model System Model SW Deployment: SW Components – System Mapping "Impact: HCDES/MICTES", Karsai

  16. Approach & Technical Challenges Guaranteed behavior of distributed control software using the following approaches: (1) extension of robust controller design to selected implementation error categories (2) providing “certificate of correctness” for the controller implementation (3) development of semantic foundation for tool chain composition (4) introducing safe computation models that provide behavior guarantees "Impact: HCDES/MICTES", Karsai

  17. Expected Deliverables • Composable tool architecture • New generation of Open Tool Integration Framework • Prototype Tool Chain • Testing and Experimental Validation • Software fully built and validated by tools • Avionics for small UAVs • Mission Management • COP for C2 "Impact: HCDES/MICTES", Karsai

  18. Computing Platforms:Design/Verification Tools, Embedded Devices "Impact: HCDES/MICTES", Karsai

  19. Transition Approach • Tools are disseminated through the ESCHER Repository (Open Source) • Government: AFRL connections • AFRL/IF, AFRL/VACC, AFRL/VACA, AFRL/CSD • CerTA Project (Boeing/UCB) • Future Combat Systems Program (Boeing/VU) "Impact: HCDES/MICTES", Karsai

  20. Center Impact (2): Collaborative Research with NASA/ARC Model-Integrated Computing Tools for Exploration Systems (MICTES) Goal: Assured Development of Flight Control Software for Spacecraft Applications • Front-end Modeling: Simulink/Stateflow • Code generation using a GReAT-based model transformation tool • CG output includes annotated code (verification conditions) • Model checker/theorem prover is used to prove code properties (ARC) • Expected result: Integrated code generator/code verifier tool for Simulink/Stateflow-based Embedded Software Development "Impact: HCDES/MICTES", Karsai

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