Applying model-driven development to distributed real-time and embedded avionics systems

Balasubramanian, Krishnakumar; Krishna, Arvind S.; Turkay, Emre; Balasubramanian, Jaiganesh; Parsons, Jeff; Gokhale, Aniruddha; Schmidt, Douglas C.

doi:10.1504/ijes.2006.014851

Cited by 19 publications

(13 citation statements)

References 21 publications

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“…Our algorithms also use the following auxiliary functions: (1) f acets(c), which returns the set of facets defined in component c, (2) receptacles(c), which returns the set of receptacles defined in component c, (3) publishers(c), which returns the set of publishers, i.e., event sources defined in component c, and (4) consumers(c), which returns the set of consumers, i.e., event sinks defined in component c. The details of these (and other) auxiliary functions are described in [7].…”

Section: Assumptions and Challenges In Component Fusionmentioning

confidence: 99%

Physical Assembly Mapper: A Model-Driven Optimization Tool for QoS-Enabled Component Middleware

Balasubramanian

Schmidt

2008

2008 IEEE Real-Time and Embedded Technology and Applications Symposium

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This paper provides four contributions to the study of optimization techniques for component-based distributed realtime and embedded (DRE) systems. First, we describe key challenges of designing component-based DRE systems and identify key sources of overhead in a typical componentbased DRE system from the domain of shipboard computing. Second, we describe a class of optimization techniques applicable to the deployment of component-based DRE systems. Third, we describe the Physical Assembly Mapper (PAM), which is a model-driven optimization tool that implements these techniques to reduce footprint. Fourth, we evaluate the benefits of these optimization techniques empirically and analyze the results. Our results indicate that the deployment-time optimization techniques in PAM provides significant benefits, such as 45% improvement in footprint, when compared to conventional component middleware technologies.

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Section: Assumptions and Challenges In Component Fusionmentioning

confidence: 99%

Physical Assembly Mapper: A Model-Driven Optimization Tool for QoS-Enabled Component Middleware

Balasubramanian

Schmidt

2008

2008 IEEE Real-Time and Embedded Technology and Applications Symposium

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“…Many platform-specific as well as platform-independent component structural modeling languages, such as Embedded Systems Modeling Language(ESML) [9] for embedded systems, J2EEML [17] for Enterprise Java Beans, and Platform Independent Component Modeling Language (PICML) [2] for Light-weight CORBA Component Model [12] (LwCCM) exist today that capture various composition semantics. In this paper we have focused on languages developed using GME since CQML is also developed using GME.…”

Section: Identifying Invariant Properties Of Componentbased Structuramentioning

confidence: 99%

“…Recent successes with DSM tools in this area include the Embedded Systems Modeling Language (ESML) [9] for avionics mission computing, SysWeaver [5] for embedded systems, and our earlier work on the Platform Independent Component Modeling Language (PICML) [2] for a range of distributed, real-time systems. These DSM tools provide support for component-based software engineering (CBSE) [3] wherein systems can be modeled by composing multiple different components, each encapsulating a reusable unit of functionality.…”

Section: Introductionmentioning

confidence: 99%

Towards a QoS Modeling and Modularization Framework for Component-based Systems

Tambe

Dabholkar

Gokhale

et al. 2008

2008 12th Enterprise Distributed Object Computing Conference Workshops

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Current domain-specific modeling (DSM) frameworks for designing component-based systems provide modeling support for system's structural as well as non-functional or quality of service (QoS) concerns. However, the focus of such frameworks on system's non-functional concerns is an after-thought and their support is at best adhoc. Further, such frameworks lack strong decoupling between the modeling of the system's structural composition and their QoS requirements. This lack of QoS modularization limits (1) reusability of such frameworks, (2) ease of their maintenance when new non-functional characteristics are added, and (3) independent evolution of the modeling frameworks along both the structural and non-functional dimensions. This paper describes Component QoS Modeling Language (CQML), which is a reusable, extensible, and platform-independent QoS modeling language that provides strong separation between the structural and nonfunctional dimensions. CQML supports independent evolution of structural metamodel of composition modeling languages as well as QoS metamodel. To evaluate, we superimpose CQML on a purely structural modeling language and automatically generate, configure, and deploy componentbased fault-monitoring infrastructure using aspect-oriented modeling (AOM) techniques.

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“…Therefore, it can be considered as a model-driven software development approach. CoSMIC (Component Synthesis using Model-Integrated Computing) (Gokhale et al, 2003;Balasubramanian et al, 2005) is another development environment which follows the paradigm of MDD. It is a collection of domain-specific modelling languages and generative tools for the development, configuration, deployment, and validation of distributed component-based real-time systems.…”

Section: Development Environmentsmentioning

confidence: 99%