Treffer: Efficient Asynchronous Event Handling in the Real-Time Specification for Java.

The Real-Time Specification for Java (RTSJ) is becoming mature. It has been implemented, formed the basis for research and used in serious applications. Some strengths and weaknesses are emerging. One of the areas that requires further elaboration is asynchronous event handling (AEH). The primary goal for handlers in the RTSJ is to have a lightweight concurrency mechanism. Some implementation will, however, simply map a handler to a real-time thread and this results in undermining the original motivations and introduces performance penalties. However it is generally unclear how to map handlers to real-time threads effectively. Also the support for nonblocking handlers in the RTSJ is criticized as lacking in configurability as implementations are unable to take advantage of them. This article, therefore, examines the AEH techniques used in some popular RTSJ implementations and proposes two efficient AEH models for the RTSJ. We then define formal models of the RTSJ AEH implementations using the automata formalism provided by the UPPAAL model checking tool. Using the automata models, their properties are explored and verified. In the proposed models, blocking and nonblocking handlers are serviced by different algorithms. In this way, it is possible to assign a real-time thread to a handler at the right time in the right place while maintaining the fewest possible threads overall and to give a certain level of configurability to AEH. We also have implemented the proposed models on an existing RTSJ implementation, jRate and executed a set of performance tests that measure their respective dispatch and multiple-handler completion latencies. The results from the tests and the verifications indicate that the proposed models require fewer threads on average with better performance than other approaches. [ABSTRACT FROM AUTHOR]

Copyright of ACM Transactions on Embedded Computing Systems is the property of Association for Computing Machinery and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)