Abstract
Many safety-critical systems are required to have their correctness validated prior to deployment. Such validation is typically performed using models of the run-time behaviour that the system is expected to exhibit and experience during run-time. However, these systems
may be subject to different requirements under different circumstances; also, there may be multiple stakeholders involved, each with a somewhat different perspective
on correctness. We examine the use of a multi-model framework based on assumptions (Pre and Rely conditions) and obligations (Post and Guarantee conditions) to represent the workload and resource related needs of complex AI system components such as DNN classifiers.
We identify three kinds of multi-models that are of particular interest: Independent, Integrated and Hierarchical.
All the individual models comprising an independent multi-model must remain valid at all times during run-time;
at least one of the models comprising an integrated multi-model must always be valid.
With hierarchical multi-models all models are initially valid but the component's behaviour may gracefully degrade through a series of models with successively weaker assumptions and commitments (we show that Mixed-Criticality Systems, widely studied in the real-time computing community, are particularly well-suited for representation via hierarchical multi-models). We explain how this modelling framework is intended to be used, and present algorithms for determining the worst-case timing behaviour of systems that are specified using multi-models.
may be subject to different requirements under different circumstances; also, there may be multiple stakeholders involved, each with a somewhat different perspective
on correctness. We examine the use of a multi-model framework based on assumptions (Pre and Rely conditions) and obligations (Post and Guarantee conditions) to represent the workload and resource related needs of complex AI system components such as DNN classifiers.
We identify three kinds of multi-models that are of particular interest: Independent, Integrated and Hierarchical.
All the individual models comprising an independent multi-model must remain valid at all times during run-time;
at least one of the models comprising an integrated multi-model must always be valid.
With hierarchical multi-models all models are initially valid but the component's behaviour may gracefully degrade through a series of models with successively weaker assumptions and commitments (we show that Mixed-Criticality Systems, widely studied in the real-time computing community, are particularly well-suited for representation via hierarchical multi-models). We explain how this modelling framework is intended to be used, and present algorithms for determining the worst-case timing behaviour of systems that are specified using multi-models.
| Original language | English |
|---|---|
| Title of host publication | 31st International Conference on Real-Time Networks and Systems, proceedings |
| Publisher | ACM |
| Pages | 155–165 |
| Number of pages | 11 |
| ISBN (Print) | 9781450399838 |
| DOIs | |
| Publication status | Published - 6 Jun 2023 |
| Event | 31st International Conference on Real-Time Networks and Systems - Duration: 6 Jun 2023 → 8 Jun 2023 |
Conference
| Conference | 31st International Conference on Real-Time Networks and Systems |
|---|---|
| Abbreviated title | RTNS 2023 |
| Period | 6/06/23 → 8/06/23 |
Bibliographical note
This is an author-produced version of the published paper. Uploaded in accordance with the University’s Research Publications and Open Access policy.Keywords
- Real-time analysis
- Mixed Criticality