26,612 research outputs found

    Expressing and enforcing user-defined constraints of AADL models

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    The Architecture Analysis and Design Language AADL allows one to model complete systems, but also to define specific extensions through property sets and library of models. Yet, it does not define an explicit mechanism to enforce some semantics or consistency checks to ensure property sets are correctly used. In this paper, we present REAL (Requirements and Enforcements Analysis Language) as an integrated solution to this issue. REAL is defined as an AADL annex language. It adds the possibility to express constraints as theorems based on set theory to enforce implicit semantics of property sets or AADL models. We illustrate the use of the language on case studies we developed with industrial partners

    Verifying service continuity in a satellite reconfiguration procedure: application to a satellite

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    The paper discusses the use of the TURTLE UML profile to model and verify service continuity during dynamic reconfiguration of embedded software, and space-based telecommunication software in particular. TURTLE extends UML class diagrams with composition operators, and activity diagrams with temporal operators. Translating TURTLE to the formal description technique RT-LOTOS gives the profile a formal semantics and makes it possible to reuse verification techniques implemented by the RTL, the RT-LOTOS toolkit developed at LAAS-CNRS. The paper proposes a modeling and formal validation methodology based on TURTLE and RTL, and discusses its application to a payload software application in charge of an embedded packet switch. The paper demonstrates the benefits of using TURTLE to prove service continuity for dynamic reconfiguration of embedded software

    Reducing Timing Interferences in Real-Time Applications Running on Multicore Architectures

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    We introduce a unified wcet analysis and scheduling framework for real-time applications deployed on multicore architectures. Our method does not follow a particular programming model, meaning that any piece of existing code (in particular legacy) can be re-used, and aims at reducing automatically the worst-case number of timing interferences between tasks. Our method is based on the notion of Time Interest Points (tips), which are instructions that can generate and/or suffer from timing interferences. We show how such points can be extracted from the binary code of applications and selected prior to performing the wcet analysis. We then represent real-time tasks as sequences of time intervals separated by tips, and schedule those tasks so that the overall makespan (including the potential timing penalties incurred by interferences) is minimized. This scheduling phase is performed using an Integer Linear Programming (ilp) solver. Preliminary results on state-of-the-art benchmarks show promising results and pave the way for future extensions of the model and optimizations

    Schedulability analysis of timed CSP models using the PAT model checker

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    Timed CSP can be used to model and analyse real-time and concurrent behaviour of embedded control systems. Practical CSP implementations combine the CSP model of a real-time control system with prioritized scheduling to achieve efficient and orderly use of limited resources. Schedulability analysis of a timed CSP model of a system with respect to a scheduling scheme and a particular execution platform is important to ensure that the system design satisfies its timing requirements. In this paper, we propose a framework to analyse schedulability of CSP-based designs for non-preemptive fixed-priority multiprocessor scheduling. The framework is based on the PAT model checker and the analysis is done with dense-time model checking on timed CSP models. We also provide a schedulability analysis workflow to construct and analyse, using the proposed framework, a timed CSP model with scheduling from an initial untimed CSP model without scheduling. We demonstrate our schedulability analysis workflow on a case study of control software design for a mobile robot. The proposed approach provides non-pessimistic schedulability results

    Modelling and Simulation of Asynchronous Real-Time Systems using Timed Rebeca

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    In this paper we propose an extension of the Rebeca language that can be used to model distributed and asynchronous systems with timing constraints. We provide the formal semantics of the language using Structural Operational Semantics, and show its expressiveness by means of examples. We developed a tool for automated translation from timed Rebeca to the Erlang language, which provides a first implementation of timed Rebeca. We can use the tool to set the parameters of timed Rebeca models, which represent the environment and component variables, and use McErlang to run multiple simulations for different settings. Timed Rebeca restricts the modeller to a pure asynchronous actor-based paradigm, where the structure of the model represents the service oriented architecture, while the computational model matches the network infrastructure. Simulation is shown to be an effective analysis support, specially where model checking faces almost immediate state explosion in an asynchronous setting.Comment: In Proceedings FOCLASA 2011, arXiv:1107.584

    Verifying Weakly-Hard Real-Time Properties of Traffic Streams in Switched Networks

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    In this paper, we introduce the first verification method which is able to provide weakly-hard real-time guarantees for tasks and task chains in systems with multiple resources under partitioned scheduling with fixed priorities. Existing weakly-hard real-time verification techniques are restricted today to systems with a single resource. A weakly-hard real-time guarantee specifies an upper bound on the maximum number m of deadline misses of a task in a sequence of k consecutive executions. Such a guarantee is useful if a task can experience a bounded number of deadline misses without impacting the system mission. We present our verification method in the context of switched networks with traffic streams between nodes, and demonstrate its practical applicability in an automotive case study

    Recovering Multiple Nonnegative Time Series From a Few Temporal Aggregates

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    Motivated by electricity consumption metering, we extend existing nonnegative matrix factorization (NMF) algorithms to use linear measurements as observations, instead of matrix entries. The objective is to estimate multiple time series at a fine temporal scale from temporal aggregates measured on each individual series. Furthermore, our algorithm is extended to take into account individual autocorrelation to provide better estimation, using a recent convex relaxation of quadratically constrained quadratic program. Extensive experiments on synthetic and real-world electricity consumption datasets illustrate the effectiveness of our matrix recovery algorithms
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