On Methodology for the Verification of Reconfigurable Timed Net Condition/Event Systems

Hafidi, Yousra; Kahloul, Laïd; Khalgui, Mohamed; Li, Zhiwu; Alnowibet, Khalid Abdulaziz; Qu, Ting

doi:10.1109/tsmc.2018.2855209

Cited by 16 publications

(3 citation statements)

References 59 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Executing the TA models ensures that the model's verified behaviour is the program's runtime behaviour. Recent work includes a methodology for verifying reconfigurable timed net condition/event systems [84] and stochastic petri nets to verify reconfigurable manufacturing systems [167].…”

Section: Self-adaptive and Reconfigurable Systemsmentioning

confidence: 99%

Formal Specification and Verification of Autonomous Robotic Systems

et al. 2019

View full text Add to dashboard Cite

Autonomous robotic systems are complex, hybrid, and often safety-critical; this makes their formal specification and verification uniquely challenging. Though commonly used, testing and simulation alone are insufficient to ensure the correctness of, or provide sufficient evidence for the certification of, autonomous robotics. Formal methods for autonomous robotics has received some attention in the literature, but no resource provides a current overview. This paper systematically surveys the state-of-the-art in formal specification and verification for autonomous robotics. Specially, it identifies and categorises the challenges posed by, the formalisms aimed at, and the formal approaches for the specification and verification of autonomous robotics. Introduction, Methodology and Related WorkAn autonomous system is an artificially intelligent entity that makes decisions in response to input, independent of human interaction. Robotic systems are physical entities that interact with the physical world. Thus, we consider an autonomous robotic system as a machine that uses Artificial Intelligence (AI), has a physical presence in and interacts with the real world. They are complex, inherently hybrid, systems, combining both hardware and software; they often require close safety, legal, and ethical consideration. Autonomous robotics are increasingly being used in commonplace-scenarios, such as driverless cars [68], pilotless aircraft [176], and domestic assistants [174,60].While for many engineered systems, testing, either through real deployment or via simulation, is deemed sufficient; the unique challenges of autonomous robotics, their dependence on sophisticated software control and decision-making, and their increasing deployment in safety-critical scenarios, require a stronger form of verification. This leads us towards using formal methods, which are mathematically-based techniques for the specification and verification of software systems, to ensure the correctness of, and provide sufficient evidence for the certification of, robotic systems.We contribute an overview and analysis of the state-of-the-art in formal specification and verification of autonomous robotics. §1.1 outlines the scope, research questions and search criteria for our survey. §1.2 describes related work concerning formal methods for robotics and differentiates them from our work. We recognise the important role that middleware architectures and, non-and semi-formal techniques have in the development of reliable robotics and we briefly summarise some of these techniques in §2. The specification and verification challenges raised by autonomous robotic systems are discussed next: §3 describes the challenges of their context (the external challenges) and §4 describes the challenges of their organisation (the internal challenges). §5 discusses the formalisms used in the literature for specification and verification of autonomous robotics. §6 characterises the approaches to formal specification and verification of autonomous robotics found in the li...

show abstract

Section: Self-adaptive and Reconfigurable Systemsmentioning

confidence: 99%

Formal Specification and Verification of Autonomous Robotic Systems

et al. 2019

View full text Add to dashboard Cite

show abstract

“…The work reported in [131] includes the energy constraints in the formal modeling and verification of reconfigurable MPSoC architectures under real-time and QoS constraints. Finally, the work reported in [132] a new methodology for formal verification of RDECSs to ensure the correctness of these systems with a reduced cost. The modeling with R-TNCESs is enriched with all reconfiguration forms, and the verification involves an improvement method that avoids any redundancy and cancels unnecessary calculations.…”

Section: A Modeling With Reconfigurable Deterministic Petri Netsmentioning

confidence: 99%

On Reconfiguration Theory of Discrete-Event Systems: From Initial Specification Until Final Deployment

Khalgui

Mosbahi

2019

IEEE Access

Self Cite

View full text Add to dashboard Cite

This paper presents an overview on different research activities that we did in the recent decade for developing reconfigurable discrete-event systems (RDESs) from initial high-level specification according to user requirements until final low-level deployment in target hardware components. A reconfiguration is any run-time scenario that adapts the system's behavior to any evolution in the related environment by adding or removing services or also configuring their parameters, i.e., their frequency, execution time, or also their location in the considered hardware architecture. Since the development of distributed RDESs under functional and extra-functional constraints is required by experts, we propose a complete methodology that deals first with their initial design with a new general profile named R-UML extending unified modeling language (UML) or also with new specific technology-oriented profiles, the validation of the related models with a new language R-OCL extending object constraint language (OCL), before their transformation to formal formalisms, such as Petri nets, timed automata, or B method for simulation or also formal verification of different properties. The checked models are transformed into OS reconfigurable tasks in the operational level, before applying a co-design methodology under functional, real-time, memory, and energy constraints for minimizing redundancies in tasks and for optimizing the composition of software and hardware parts together. We describe technology-oriented solutions for the scheduling of distributed RDESs by parameterizing tasks and their exchanged messages between multi-speed networked processors. We finish with the real low-level deployment on target hardware devices before applying useful software and hardware tests for checking the delivered system quality. These contributions, published in different journal and conference papers, are applied to different applications in medicine, wireless sensor networks, transportation systems, manufacturing industry, smart grids and microgrids, embedded technologies, and so on. We find significant gains in terms of the system reactivity and flexibility under related constraints. INDEX TERMS Discrete-event system, modeling and verification, design and validation, implementation and scheduling, real-time and energy aware scheduling, test and simulation, co-design and deployment, application. I. INTRODUCTION Automatic flexibility becomes a required criterion for dynamic system adaptability to any possible evolution in related environment. A reconfigurable system is considered in this paper as a discrete-event system (RDES) that adapts its behavior to recover faults or also improve required performance at run-time. It is a set of wired/wireless networked devices that run independent/dependent control software tasks exchanging messages on the network [1], [2]. These tasks and consequently the related messages should be executed under functional, memory, real-time, and energy constraints described in user requirements [3]-[5]. A reconfi...

show abstract

“…WSNs become more and more attractive by their integration in a real world of interconnected objects through ina https://orcid.org/0000-0001-9237-8083 b https://orcid.org/0000-0001-6311-3588 c https://orcid.org/0000-0001-5160-9412 ternet (Zeinab and Elmustafa, 2017) (Hafidi. et al, 2019) (Hafidi et al, 2018). The performance of WSNs is affected by limiting processing and memory, limiting energy, losing packet, delay, and real-time data (Talebi et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

QCOF: New RPL Extension for QoS and Congestion-Aware in Low Power and Lossy Network

Aissa

Grichi

Khalgui

et al. 2019

Proceedings of the 14th International Conference on Software Technologies

Self Cite

View full text Add to dashboard Cite

Low power and lossy networks (LLNs) require a routing protocol under real-time and energy constraints, congestion aware and packet priority. Thus, Routing Protocol for Low power and lossy network (RPL) is recommended by Internet Engineering Task force (IETF) for LLN applications. In RPL, nodes select their optimal paths towards their preferred parents after meeting routing metrics that are injected in the objective function (OF). However, RPL did not impose any routing metric and left it open for implementation. In this paper, we propose a new RPL objective function which is based on the quality of service (QoS) and congestion-aware. In the case paths fail, we define new RPL control messages for enriching the network by adding more routing nodes. Extensive simulations show that QCOF achieves significant improvement in comparison with the existing objective functions, and appropriately satisfies real-time applications under QoS and network congestion.

show abstract

On Methodology for the Verification of Reconfigurable Timed Net Condition/Event Systems

Cited by 16 publications

References 59 publications

Formal Specification and Verification of Autonomous Robotic Systems

Formal Specification and Verification of Autonomous Robotic Systems

On Reconfiguration Theory of Discrete-Event Systems: From Initial Specification Until Final Deployment

QCOF: New RPL Extension for QoS and Congestion-Aware in Low Power and Lossy Network

Contact Info

Product

Resources

About