1 / 10

Real-time Analysis of Resource-Constrained Distributed Systems by Simulation-Guided Model Checking

This research explores the challenges of analyzing resource-constrained distributed systems using simulation-guided model checking. It proposes a model-based approach for the design and analysis of embedded systems, with a focus on domain-specific modeling and simulation-guided model checking. The research also introduces the DREAM framework for architectural exploration and provides an open-source tool for automatic timed automata model generation.

jsumner
Download Presentation

Real-time Analysis of Resource-Constrained Distributed Systems by Simulation-Guided Model Checking

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Real-time Analysis of Resource-Constrained Distributed Systems by Simulation-Guided Model Checking Gabor Madl (gabe@ics.uci.edu), Ph.D. Candidate, UC Irvine Advisor: Nikil Dutt (dutt@ics.uci.edu) Chancellor’s Professor, UC Irvine RTSS 2007 Ph.D. Forum

  2. Challenges Model-based Analysis Simulation-guided Model Checking DREAM Framework Analysis of Embedded Systems • Distributed real-time embedded (DRE) systems are often reactive and event-driven • Better latency than in synchronous/time-triggered systems • Easier to implement, no need for global synchronization • Computations are driven by events – complex model • Asynchrony, concurrency, race conditions • Hard to predict all behaviors • Have to satisfy multiple constraints • Real-time, energy consumption, reliability, fault-tolerance • Functional verification, real-time analysis, performance estimation are key challenges • Task execution times, delays, parallelism, throughput

  3. Challenges Model-based Analysis Simulation-guided Model Checking DREAM Framework Continuous-time Analysis • In DRE systems classic scheduling methods may result in scheduling anomalies • Hard to analyze real-time properties • In practical event-driven systems, exhaustive analysis is often infeasible due to the state space explosion problem • We need methods that can capture continuous-time execution intervals, and event-based triggering

  4. Challenges Model-based Analysis Simulation-guided Model Checking DREAM Framework 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

  5. Challenges Model-based Analysis Simulation-guided Model Checking DREAM Framework Model-based Design & Analysis • We propose a model-based approach for the design & analysis of embedded systems • The design flow is driven by the DSM, a high-level specification that captures key properties • The DSM is mapped to a formal executable model to allow verification and evaluation • Formal models drive functional verification • We propose the combination of simulations and formal methods for the evaluation of designs

  6. Challenges Model-based Analysis Simulation-guided Model Checking DREAM Framework Domain-Specific Modeling • We utilize meta-modeling to specify modeling languages • The modeling language is used for the specification and early exploration of design alternatives • Designers work on models that are based on their domains of expertise, they do not have to become experts in formal methods as well • We focus on two domains • DRE systems • Multi-processor System-on-Chip (MPSoC) designs

  7. Challenges Model-based Analysis Simulation-guided Model CheckingDREAM Framework Simulation-Guided Model Checking • Parameters for components obtained by simulations • Utilize model checking and discrete event simulations on symbolic models to increase coverage

  8. Model checking for the functional verification of protocols Simulation-guided performance estimation of MPSoCs Use results as parameters for higher-level models Compose methods to improve accuracy, scalability Better understanding of interactions between components Challenges Model-based Analysis Simulation-guided Model CheckingDREAM Framework Architectural Exploration

  9. ALDERIS model GME tool Verimag IF model checker ALDERIS model XML representation UPPAAL model checker Challenges Model-based Analysis Simulation-guided Model Checking DREAM Framework DREAM Analysis Framework Open-source DREAM Tool Automatic timed automata model generation for the UPPAAL and Verimag IF tools Simulation-guided model checking Performance Estimation using DES Random testing Schedulability optimizations http://dre.sourceforge.net

  10. Questions? Links to relevant work: http://dre.sourceforge.net http://alderis.ics.uci.edu http://www.ics.uci.edu/~gabe RTSS 2007 Ph.D. Forum

More Related