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Asynchronous Signal Paradigm and AI for Soft Real Time Systems

Fulltext:


Authors:

Peter Funk, Janet Wennersten (Ericsson AB)

Publication Type:

Report


Abstract

Decomposition into communicating asynchronous entities is often chosen as solution for both telecommunications systems and for real time AI systems [Dodhaiwala et al. 89]. This in contrast to the trend to increase the abstraction level of real time programming by introducing features and paradigms from main stream time sharing systems with an operating system man-aging garbage collection, process scheduling, etc. For large complex concurrent real time systems which are signal centered, a main stream specification and implementation approach makes it difficult to meet requirements (response time, reliability, etc.). It is also difficult to analyze the overall behavior of the system. A real time language (called PLEX) combined with a real time operating system and processor, all based on an asynchronous signaling paradigm, has proven to be efficient [Hemdal 1998] for asynchronously communicating real time applications (large telecommunications systems with millions of lines of PLEX code are in operation). PLEX and Petri Nets show similarities and by specifying behavioral parts with Petri Nets [Jensen 1997] powerful analysis tools (liveness, deadlock, etc.) are available. In this paper we analyze the benefits emerging from combining PLEX with Petri Nets, enabling both an efficient implementation and analysis of behavior.

Bibtex

@techreport{Funk234,
author = {Peter Funk and Janet Wennersten (Ericsson AB)},
title = {Asynchronous Signal Paradigm and AI for Soft Real Time Systems},
month = {March},
year = {2000},
url = {http://www.es.mdh.se/publications/234-}
}