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Composing Time- and Event-driven Distributed Real-time Systems Gabor Madl ( gabe@ics.uci.edu ), Ph.D. Candidate, UC Irvine Advisor: Nikil Dutt ( dutt@ics.uci.edu ) Chancellor’s Professor, UC Irvine Pietr Mondrian, Composition No. 10, 1939-42 Hans Hofmann, The Gate, 1959-60

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composing time and event driven distributed real time systems

Composing Time- andEvent-driven DistributedReal-time Systems

Gabor Madl (gabe@ics.uci.edu),

Ph.D. Candidate, UC Irvine

Advisor: Nikil Dutt (dutt@ics.uci.edu)

Chancellor’s Professor, UC Irvine

Cyber-Physical System Challenges in the Automotive Domain, RTSS 2007

challenges in ngas

Pietr Mondrian, Composition No. 10, 1939-42

Hans Hofmann, The Gate, 1959-60

Kazimir Malevich, Black Square, 1915

Challenges Traditional Design Compose Functionalities Combine Analysis Model-based Analysis

Challenges in NGAS
  • How to safely increase functionality?
    • Primary concern is safety (at least it should be)
    • Secondary concern is cost (?)
    • Increase functionality while constraints above are preserved
    • How would a painter work under these conditions?
separate functionalities

Challenges Traditional Design Compose Functionalities Combine Analysis Model-based Analysis

Separate Functionalities
  • Dedicated hardware for each functionality
  • “Protect” components from each other
  • Design them independently
  • Are we sure that there is no interaction between critical and non-critical functionalities?
    • Leakage power: drains power even when the car is idle
    • Energy consumption: could become a bottleneck
    • How will critical functionalities perform in a resource-constrained environment?
  • Suboptimal utilization
    • More components are needed
    • Limited interaction with the environment
rethink design of ngas

Challenges Traditional Design Compose Functionalities Combine Analysis Model-based Analysis

Rethink Design of NGAS
  • We need to use more flexible design methodologies than the current practice
  • We need to learn to better utilize the potential of distributed real-time embedded (DRE) systems
    • More and more sensors and actuators
    • More interaction between components and their environment
  • We need to build on the strengths of existing design methodologies, but also encourage interaction
    • Cars could use information from the environment (i.e. weather information, GPS, other cars) to prepare for unforeseen circumstances, such as fog, freezing, accidents ahead etc.
    • Non-critical functionality could be used as “backup” to increase fault tolerance
compose functionalies

Challenges Traditional Design Compose Functionalities Combine Analysis Model-based Analysis

Compose Functionalies
  • Critical functionalities
    • Time-triggered systems
    • Focus on control (scheduling)
    • Execution times, periods, deadlines, priorities, etc.
    • Mathematical model for analysis (scheduling theory)
    • Simple analysis, costly implementation
  • Non-critical functionalities
    • Event-driven systems
    • Focus on the flow of data
    • Throughput, communication architecture, parallelization, etc.
    • Complex model, hard to predict all behaviors
    • Simple implementation, costly analysis
need to combine analysis methods

Challenges Traditional Design Compose Functionalities Combine Analysis Model-based Analysis

Need to Combine Analysis Methods
  • Static analysis methods
    • Often too abstract, resulting in conservative/inaccurate results
    • Cannot capture dynamic effects
  • Simulations
    • Can show the presence of an error, never its absence
    • Ad-hoc, hard to measure coverage
    • Limited design space exploration
  • Model checking
    • State space explosion problem
    • No partial results
    • Time consuming and costly
  • Each method has its advantage and disadvantage
model based design analysis

Challenges Traditional Design Compose Functionalities Combine Analysis Model-based Analysis

Model-based Design & Analysis
  • Model-based design provides the means for the early exploration of design alternatives
  • The design flow is driven by the DSM, a high-level specification that captures key properties
  • Mappings play a key role in abstraction
  • Formal models drive functional verification
  • We propose the combination of simulations and formal methods for the evaluation of designs
questions

Questions?

Links to relevant work:

http://dre.sourceforge.net

http://alderis.ics.uci.edu

http://www.ics.uci.edu/~gabe

Cyber-Physical System Challenges in the Automotive Domain, RTSS 2007