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Enhancing real-time CORBA via real-time Java features

Authors: A.S. Krishna; D.C. Schmidt; R. Klefstad;

Enhancing real-time CORBA via real-time Java features

Abstract

End-to-end middleware predictability is essential to support quality of service (QoS) capabilities needed by distributed real-time and embedded (DRE) applications. Real-time CORBA is a middleware standard that allows DRE applications to allocate, schedule, and control the QoS of CPU, memory, and networking resources. Existing real-time CORBA solutions are implemented in C++, which is generally more complicated and error-prone to program than Java. The real-time specification for Java (RTSJ) provides extensions that enable Java to be used for developing DRE systems. Real-time CORBA does not currently leverage key RTSJ features, such as scoped memory and real-time threads. Thus, integration of real-time CORBA and RTSJ is essential to ensure the predictability required for Java-based DRE applications. We provide the following contributions to the study of middleware for DRE applications. First we analyze the architecture of ZEN, our implementation of real-time CORBA, identifying sources for the application of RTSJ features. Second, we describe how RTSJ features, such as scoped memory and real-time threads, can be associated with key ORB components to enhance the predictability of DRE applications using realtime CORBA and the RTSJ. Third, we perform preliminary qualitative and quantitative analysis of predictability enhancements arising from our application of RTSJ features. Our results show that use of RTSJ features can considerably improve the predictability of DRE applications written using Real-time CORBA and real-time Java.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Average
Top 10%
Top 10%
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