Quantitative Analysis of Variation-Aware Internet of Things Designs Using Statistical Model Checking

Xu, Siyuan; Miao, Weikai; Kunz, Thomas; Wei, Tongquan; Chen, Mingsong

doi:10.1109/qrs.2016.39

Cited by 9 publications

(7 citation statements)

References 15 publications

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“…Table summarizes the main characteristics of the design/analysis methods found in related bibliography and compares them with the BIP design flow of Figure . Most approaches are model‐based, but only the BIP flow and a few other works() are grounded on languages with formal semantics.…”

Section: Discussionmentioning

confidence: 99%

“…The validation of quantitative specifications or the robustness analysis of systems is supported by some methods, but only the work of Cherrier et al and the BIP flow support the verification of qualitative properties, with the latter covering all categories. Moreover, most methods do not cover the entire design cycle (including code generation and deployment) with the notable exceptions of the works() and the BIP design flow. Some methods are limited to the analysis of WSN systems.…”

Section: Discussionmentioning

confidence: 99%

“…In terms of the tools that support the various forms of analysis, most of the approaches in Table provide or utilize various simulation frameworks with the notable exception of the BIP flow along and the works,() which support SMC and/or other formal analyses. Finally, a noteworthy number of the shown methods aim to the generation of code for REST services running on the Contiki OS or other operating system.…”

Section: Discussionmentioning

confidence: 99%

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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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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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

et al. 2018

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“…Moreover, most methods do not cover the entire design cycle (including code [139], [141], [143], [144] and the BIP design flow. Some methods are limited to the analysis of WSN systems.…”

Section: Comparison With Competitive Design Methodsmentioning

confidence: 99%

“…In terms of the tools that support the various forms of analysis, most of the approaches in Table 5.5 provide or utilize various simulation frameworks with the notable exception of the BIP flow along with [140], [141], [143], [144], which support statistical model checking and/or other formal analyses. Finally, a noteworthy number of the shown methods aim to the generation of code for REST services running on the Contiki OS or other operating system.…”

Section: Comparison With Competitive Design Methodsmentioning

confidence: 99%

Correct by construction model based design for systems and software

Stachtiari¹,

Στάχτιαρη²

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Η παρούσα διατριβή εισάγει τεχνικές για την αυστηρή και από κατασκευής ορθή σχεδίαση συστημάτων. Ειδικότερα, εστιάσαμε στο πώς μπορούμε να παράγουμε και να επικυρώνουμε ένα λειτουργικό μοντέλο της εφαρμογής που προκύπτει από ένα σύνολο απαιτήσεων ή από τον κώδικα της εφαρμογής. Αρχικά, ασχοληθήκαμε με την πρώιμη επικύρωση των απαιτήσεων και της σχεδίασης του συστήματος, ώστε να εξαλειφθεί η ανάγκη επαλήθευσης εκ των υστέρων και να περιοριστούν οι έλεγχοι επικύρωσης κατά τα τελευταία στάδια ανάπτυξης. Δεύτερον, εστιάσαμε στην αυτόματη δημιουργία λειτουργικών μοντέλων εφαρμογών από προγράμματα με εμφωλευμένη σύνταξη, διατηρώντας τη σημασιολογία των προγραμμάτων. Τέλος, προτείναμε μία ροή σχεδίασης που αποσκοπεί στη διατήρηση της συνέπειας μεταξύ του λειτουργικού μοντέλου και του κώδικα εφαρμογής μέσω της χρήσης μιας νέας γλώσσας ειδικού σκοπού, κατάλληλης για τη σχεδίαση συστημάτων περιορισμένων πόρων του διαδικτύου των αντικειμένων.

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Uncertainty representation in software models: a survey

et al. 2021

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This paper provides a comprehensive overview and analysis of research work on how uncertainty is currently represented in software models. The survey presents the definitions and current research status of different proposals for addressing uncertainty modeling, and introduces a classification framework that allows to compare and classify existing proposals, analyse their current status and identify new trends. In addition, we discuss possible future research directions, opportunities and challenges.A fundamental characteristic of software models is their ability to represent the relevant characteristics of the system under study, at the appropriate level of abstraction. Software models were initially conceived to design and develop general Information Technology (IT) systems, such as financial applications, enterprise databases or component-based systems, and have proven to be excellent artefacts for representing the basic structure and

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Quantitative Analysis of Variation-Aware Internet of Things Designs Using Statistical Model Checking

Cited by 9 publications

References 15 publications

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

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

Correct by construction model based design for systems and software

Uncertainty representation in software models: a survey

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