A Unified Model-Based Framework for the Simplified Execution of Static and Dynamic Assertion-Based Verification

Anwar, Muhammad Waseem; Rashid, Muhammad; Azam, Farooque; Naeem, Aamir; Kashif, Muhammad; Butt, Wasi Haider

doi:10.1109/access.2020.2999544

Cited by 37 publications

(13 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A special mention should be done on Assertion Based Verification techniques, which include formal verification methods where designs are verified against certain assertions. In [15] a unified framework for executing static and dynamic verification [16] for embedded systems design is presented. One common static verification method is Timed Automata Models [17] which allow determining whether or not temporal requirements are met.…”

Section: A Related Workmentioning

confidence: 99%

Response-Time Analysis of Multipath Flows in Hierarchically-Scheduled Time-Partitioned Distributed Real-Time Systems

et al. 2020

View full text Add to dashboard Cite

Modern industrial cyberphisical systems exhibit increasingly complex execution patterns like multipath endto-end flows, that force the real-time community to extend the schedulability analysis methods to include these patterns. Only then it is possible to ensure that applications meet their deadlines even in the worstcase scenario. As a driving motivation, we present a real industrial application with safety requirements, that needs to be re-factored in order to leverage the features of new execution paradigms such as time partitioning. In this context we develop a new response-time analysis technique that provides the capacity of obtaining the worst-case response time of multipath flows in time-partitioned hierarchical schedulers and also in general fixed-priority (FP) real-time systems. We show that the results obtained with the new analysis reduce the pessimism of the currently used holistic analysis approach. INDEX TERMS Schedulability analysis, time partitioning, hierarchical scheduling, distributed systems, safety, industrial application.

show abstract

Section: A Related Workmentioning

confidence: 99%

Response-Time Analysis of Multipath Flows in Hierarchically-Scheduled Time-Partitioned Distributed Real-Time Systems

et al. 2020

View full text Add to dashboard Cite

show abstract

“…The work in this article is significant to the existing body of research knowledge in two different ways: (a) From an application developer's perspective, the proposed work provides two major benefits: simplicity and reusability [21,22]. The simplicity is achieved by providing a model-based solution at higher abstraction level.…”

Section: Plos Onementioning

confidence: 99%

A model-driven framework for data-driven applications in serverless cloud computing

et al. 2020

Self Cite

View full text Add to dashboard Cite

In a serverless cloud computing environment, the cloud provider dynamically manages the allocation of resources whereas the developers purely focus on their applications. The datadriven applications in serverless cloud computing mainly address the web as well as other distributed scenarios, and therefore, it is essential to offer a consistent user experience across different connection types. In order to address the issues of data-driven application in a real-time distributed environment, the use of GraphQL (Graph Query Language) is getting more and more popularity in state-of-the-art cloud computing approaches. However, the existing solutions target the low level implementation of GraphQL, for the development of a complex data-driven application, which may lead to several errors and involve a significant amount of development efforts due to various users' requirements in real-time. Therefore, it is critical to simplify the development process of data-driven applications in a serverless cloud computing environment. Consequently, this research introduces UMLPDA (Unified Modeling Language Profile for Data-driven Applications), which adopts the concepts of UML-based Model-driven Architectures to model the frontend as well as the backend requirements for data-driven applications developed at a higher abstraction level. Particularly, a modeling approach is proposed to resolve the development complexities such as data communication and synchronization. Subsequently, a complete open source transformation engine is developed using a Model-to-Text approach to automatically generate the frontend as well as backend low level implementations of Angular2 and GraphQL respectively. The validation of proposed work is performed with three different case studies, deployed on Amazon Web Services platform. The results show that the proposed framework enables to develop the data-driven applications with simplicity.

show abstract

“…MAF is developed by utilizing the concepts of Model Driven Architecture (MDA) as it provides a higher level of abstraction with automated end-to-end implementation [48]. MDA simplifies the development process and reduces the complexity in terms of time and cost [14]. The two key concepts of MDA are; modeling and model transformation.…”

Section: Model-driven Alarms Framework (Maf)mentioning

confidence: 99%

A Model-Driven Alarms Framework (MAF) With Mobile Clients Support for Wide-Ranging Industrial Control Systems

et al. 2020

Self Cite

View full text Add to dashboard Cite

An efficient and robust alarms management is an extremely desirable feature to prevent critical failures in modern Industrial Control Systems. Generally, alarm systems are categorized into two major components; i.e., Alarm Server and Alarm Client. Alarm server is responsible to process alarms on real time values, while alarm clients display the generated alarms. With the advent of modern technologies, like, Internet of Thing (IoT), the need for mobile alarm clients has significantly been increased, as alarms need to be displayed on different gadgets instead of traditional big screens. Owing to significance of alarms in the industry, several state-of-the-art approaches have been introduced, suggesting various improvements. However, such approaches are only meant for specific industry and cannot be applied across-the-board. Furthermore, full support for mobile clients is not available. On the other hand, certain industrial software products like, SIMATIC WinCC, Genesis64 provide complete alarm solution including mobile client features, as well. However, such solutions are proprietary with higher costs, i.e., pay per tag model. Considering such limitations, this article proposes a novel Model-driven Alarms Framework (MAF) with mobile clients (Android and iOS) support. Particularly, MAF comprises an Alarm Profile for Industrial Control Systems (APICS) for the modeling of server, mobile clients and configuration requirements of alarms with remarkable simplicity. Furthermore, a complete open source Alarms Profile Transformation Engine (APTE) has been implemented to automatically generate alarm server (Kotlin), native Android (Kotlin) and iOS (Swift) alarm clients from APICS-compliant models. The feasibility of proposed framework is demonstrated through two case studies (flour mill and home automation). The results prove that MAF not only provides complete alarm server solution to generate bulk of alarms simultaneously, but also supports android and iOS alarm clients for efficient visualization. Besides that, MAF is easy to use, cost-effective and can be applied in wide-ranging industrial applications.

show abstract

A Unified Model-Based Framework for the Simplified Execution of Static and Dynamic Assertion-Based Verification

Cited by 37 publications

References 28 publications

Response-Time Analysis of Multipath Flows in Hierarchically-Scheduled Time-Partitioned Distributed Real-Time Systems

Response-Time Analysis of Multipath Flows in Hierarchically-Scheduled Time-Partitioned Distributed Real-Time Systems

A model-driven framework for data-driven applications in serverless cloud computing

A Model-Driven Alarms Framework (MAF) With Mobile Clients Support for Wide-Ranging Industrial Control Systems

Contact Info

Product

Resources

About