1. Composing Time- and Event-driven Distributed Real-time Systems
Gabor Madl
Ph.D. Candidate, UC Irvine
Advisor: Nikil Dutt
Chancellor’s Professor, UC Irvine
Cyber-Physical System Challenges in the Automotive Domain, RTSS 2007
November 11, 2018

2. Challenges in NGAS November 11, 2018
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?
Pietr Mondrian, Composition No. 10,
Hans Hofmann, The Gate,
Kazimir Malevich, Black Square, 1915
November 11, 2018

3. 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
November 11, 2018

4. Rethink Design of NGAS November 11, 2018
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
November 11, 2018

5. 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
November 11, 2018

6. 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
November 11, 2018

7. 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
November 11, 2018

8. Questions? November 11, 2018 Links to relevant work:
Cyber-Physical System Challenges in the Automotive Domain, RTSS 2007
November 11, 2018