Statistical model checking QoS properties of systems with SBIP

Nouri, Ayoub; Bensalem, Saddek; Bozga, Marius; Delahaye, Benoît; Jégourel, Cyrille; Legay, Axel

doi:10.1007/s10009-014-0313-6

Cited by 34 publications

(20 citation statements)

References 36 publications

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“…In this paper we present the SBIP framework which offers a stochastic realtime modelling formalism and a statistical model checking (SMC) engine for quantitative assessment of systems properties. The paper is an extended version of (Nouri et al, 2016a) that generalises the current stochastic modelling formalism (Nouri et al, 2015). We rely on the BIP (Behaviour, Interaction, Priority) framework (Basu et al, 2006) which allows for building heterogeneous and complex system models in a compositional fashion.…”

Section: Institute Of Engineering Univ Grenoble Alpesmentioning

confidence: 99%

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Performance evaluation of stochastic real-time systems with the SBIP framework

Nouri

Mediouni

Bozga

et al. 2018

IJCCBS

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The SBIP framework consists of a stochastic real-time componentbased modelling formalism and a statistical model checking engine. The former is built as a stochastic extension of the real-time BIP formalism and enables the construction of stochastic real-time systems in a compositional way. The statistical engine implements a set of statistical algorithms for the quantitative and qualitative assessment of probabilistic properties. The paper provides a thorough introduction to the SBIP formalism and the associated verification method. In a second part, it surveys several case studies about modelling and verification of real-life systems, including various network protocols and multimedia applications.

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Section: Institute Of Engineering Univ Grenoble Alpesmentioning

confidence: 99%

“…RT-BIP (Abdellatif et al, 2013) extended BIP with real-time features and has (dense) real-time semantics based on timed automata concepts (Alur and Dill, 1994). S-BIP (Nouri et al, 2015) extended BIP with stochastic features and has (discrete) stochastic semantics based on Markov chains.…”

Section: Stochastic Real-time Bipmentioning

confidence: 99%

Performance evaluation of stochastic real-time systems with the SBIP framework

Nouri

Mediouni

Bozga

et al. 2018

IJCCBS

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“…While expressivity is needed for mastering heterogeneity and complexity such the clock synchronization protocol running within a distributed heterogeneous communication system (HCS). SBIP the stochastic extension of the BIP formalism and toolset allows specifying systems with both non-deterministic and stochastic aspects [30]. However, from the user point of view, dealing with SBIP is as easy as dealing with BIP.…”

Section: Related Workmentioning

confidence: 99%

The Event-B Modelling with Operators-based Refinement of NoC-based Wireless Sensors Networks

Hariche

Belarbi

Chouarfia

et al. 2017

Preprint

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Abstract:The need for high performance, available and reliable embedded systems has made computing systems increasingly complex. Formal methods have the ability to produce critical systems for large industrial projects, and this by creating an original mathematical model that can be formally refined in levels until the final refinement which contains enough of details for an implementation. This work is a first step of VHDL code generation process, it represents how to elaborate formally an embedded system using Abstract data type in a form of theories (NoC, WNoC, colored graph, VHDL) and how to ensure in systematic way all the details and complexity of this system using operators of refinement (Create, Rename, Restrict, Enrich)that are recently proposed for the Event-B method. All the theories are deployed, discharged and used in Event-B models to represent and enhance the performance of this self-organization reliability solution for the wireless sensors network of NoC-based system. This paper summerize the fruit of using new proposed approach for the Event-B formal method that persist the NoC-based ditributed system instead of consuming more than 70% of realization time with any analytic method.

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“…Additionally, connectors can export ports for building hierarchies of connectors. The stochastic extension of BIP allows (1) to specify stochastic aspects of individual components and (2) to provide a purely stochastic semantics for the parallel composition of components through interactions and priorities. Syntactically, stochastic behaviour at the level of atomic BIP components is obtained by using probabilistic variables.…”

Section: Introductionmentioning

confidence: 99%

Model‐based design of IoT systems with the BIP component framework

et al. 2018

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The design of software for networked systems with nodes running an Internet of things operating system faces important challenges due to the heterogeneity of interacting things and the constraints stemming from the often limited amount of available resources. In this context, it is hard to build confidence that a design solution fulfills the application's requirements. This paper introduces a design flow for web service applications of the representational state transfer style that is based on a formal modeling language, the behaviour, interaction, priority (BIP) component framework. The proposed flow applies the principles of separation of concerns in a component-based design process that supports the modular design and reuse of model artifacts. The BIP tools for state-space exploration allow verifying qualitative properties for service responsiveness, ie, the timely handling of events. Moreover, essential quantitative properties are validated through statistical model checking of a stochastic BIP model. All properties are preserved in actual implementation by ensuring that the deployed code is consistent with the validated model. We illustrate the design of a representational state transfer sense-compute-control application for a Wireless Personal Area Network architecture with nodes running the Contiki operating system. The results validate qualitative and quantitative properties for the system and include the study of error behaviours.

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Statistical model checking QoS properties of systems with SBIP

Cited by 34 publications

References 36 publications

Performance evaluation of stochastic real-time systems with the SBIP framework

Performance evaluation of stochastic real-time systems with the SBIP framework

The Event-B Modelling with Operators-based Refinement of NoC-based Wireless Sensors Networks

Model‐based design of IoT systems with the BIP component framework

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