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Interactive Petri Nets

Authors: GuanJun Liu; Changjun Jiang; MengChu Zhou; PengCheng Xiong;

Interactive Petri Nets

Abstract

Such concurrent systems as Web services and workflow systems can be viewed as a composition of a set of subsystems. Subsystems interact with each other through a set of message channels in order to perform a task. This work defines a class of Petri nets called interactive Petri nets (IPNs) to model these systems. IPNs can be used to analyze their behavior, find potential problems, and then improve their designs. Compatibility is an important concept for a composed system and reflects the possibility of correct/proper interaction among its subsystems. In order to characterize different cooperative abilities in practice, compatibility and weak compatibility are defined for IPNs. Some relationships among (weak) compatibility, liveness, reversibility, and boundedness are revealed. Based on them, this work proves that the (weak) compatibility problem is co-NP-hard. A taxonomy is also presented for IPNs in order to explore whether some subclasses can be analyzed efficiently. Based on it, we can identify several IPN subclasses, some of which can be analyzed in polynomial time.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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Found an issue? Give us feedback
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!
47
Top 10%
Top 10%
Top 10%
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