Component-Based Design and Analysis of Embedded Systems with UPPAAL PORT

Håkansson, John; Carlson, Jan; Monot, Aurelien; Pettersson, Paul; Slutej, Davor

doi:10.1007/978-3-540-88387-6_23

Cited by 17 publications

(8 citation statements)

References 13 publications

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“…Instead of generating a timed automata model of the entire system, compositional reasoning could be used to prove global system properties out of individual subsystems, or subsystem clus- ters properties. Another approach will envision developing specialized model checking optimizations, which exploit the topology of the ProSys architecture, similar to the work on UPPAAL PORT [5]. The overall approach should also be further validated by case studies involving real industrial systems.…”

Section: Discussionmentioning

confidence: 99%

Integrating Behavioral Descriptions into a Component Model for Embedded Systems

Vulgarakis

Sentilles

Carlson

et al. 2010

2010 36th EUROMICRO Conference on Software Engineering and Advanced Applications

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Section: Discussionmentioning

confidence: 99%

Integrating Behavioral Descriptions into a Component Model for Embedded Systems

Vulgarakis

Sentilles

Carlson

et al. 2010

2010 36th EUROMICRO Conference on Software Engineering and Advanced Applications

Self Cite

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“…In the approach, the architectural model of the BBW system is done in EAST-ADL modeling language [11], which is an Architecture Description Language (ADL) for automotive systems. The internal behavior of each component in the architecture is modeled using Timed Automata (TA) [12,13] designed in Uppaal Port tool [14,15]. A TA model describing the behavior of the ABS component of the BBW system is shown in Figure 4.…”

Section: Testing Methodologymentioning

confidence: 99%

Runtime verification of state machines and defect localization applying model-based testing

Saadatmand

Scholle

Leung

et al. 2014

Proceedings of the WICSA 2014 Companion Volume

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In this paper we introduce a method for runtime verification of the behavior of a system against state machines models in order to identify inconsistencies between the two. This is achieved by tracking states and transitions at runtime and comparing with the expected behavior of the system captured in the form of state machine models. The goal is to increase our confidence that the order of states at runtime matches what is specified by the models. The method also provides for defect localization by identifying that in the transition between which states a deviation from the expected behavior has occurred. The necessity and importance of the method lies in the fact that in model-based development, models are also used to perform analysis. Therefore, if there is any discrepancy between the behavior of the system at runtime and the models, then the result of model-based analyses which are performed may also be invalid and not applicable for the system anymore. For this purpose, in our method we create executable test cases from state machine models to test the runtime behavior of the system.

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“…In this context, it is desired to maintain the basic functionalities of existing protocols, while providing augmentations and additive features in a holistic and coordinated manner through the dynamic incorporation of different optimization methodologies. For these reasons, and based on the results of the component-based approach developed in software engineering [81], hereinafter, we discuss the design benefits of a component-based network architecture, where the principles of cross-layer design are offered in a modularized approach. Component-based design emphasizes the separation of concerns in respect of the wide-ranging functionality available throughout a given system.…”

Section: Joint Cross-layer and Component-based Resource Management (Cmentioning

confidence: 99%

Cross-Layer Based Resource Management Frameworks for Mobile Cognitive Radio Networks

Karyotis

Anifantis

Papavassiliou

2014

Resource Management in Mobile Computing Environments

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Abstract.Resource management has been one of the most important aspects of Mobile Cognitive Radio Networks (MCRNs) since their inception. It engulfs fundamental network operations such as spectrum management, bandwidth allocation, channel access, data routing, transmission power assignment and energy management. All such mechanisms are necessary for achieving the delay/throughput requirements desired by modern network services and users. Compared to traditional wireless mobile networks, the MCRN environment poses additional challenges and complicated requirements to the above functions and resource management in general, which eventually lead to an urgent need for reconsideration of the employed wireless protocol stack. The objective in MCRNs would be to apply more efficient protocol hierarchies and achieve better management of the common available resources for both secondary and primary users, at the minimum possible cost and by leaving the minimum possible resource footprint, as required for all modern communications systems. The cross-layer design approach has been proven extremely useful towards this direction, especially for network types such as sensor, mesh and cognitive radios. It allowed exploiting the most appropriate network mechanisms, while bypassing monolithic and outdated requirements when possible. In this chapter, we focus exactly on this aspect of protocol architectures and network management, and present state-of-the-art cross-layer based resource management approaches for MCRNs. Initially, we present three important resource management frameworks, and then we provide directions for developing generic and adaptive resource management protocol architectures for MCRNs, based on cross-layer and component-based design principles emerging from the previously presented approaches. This is the first attempt to highlight the suitability of combining cross-layer with componentbased network design, and this work will also sketch qualitatively the potential benefits of such approach. Finally, some practical considerations for the proposed architecture, along with directions for future research conclude the chapter.

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Component-Based Design and Analysis of Embedded Systems with UPPAAL PORT

Cited by 17 publications

References 13 publications

Integrating Behavioral Descriptions into a Component Model for Embedded Systems

Integrating Behavioral Descriptions into a Component Model for Embedded Systems

Runtime verification of state machines and defect localization applying model-based testing

Cross-Layer Based Resource Management Frameworks for Mobile Cognitive Radio Networks

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