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zbMATH Open
Article . 2005
Data sources: zbMATH Open
DBLP
Article . 2005
Data sources: DBLP
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Behaviour and Instantiation of High-Level Petri Net Processes

Behaviour and instantiation of high-level Petri net processes
Authors: Hartmut Ehrig;

Behaviour and Instantiation of High-Level Petri Net Processes

Abstract

Processes for high-level nets are often defined as processes of the low-level net Flat(n) which is obtained from N via the well-known flattening construction. This low-level notion of processes for high-level nets, however, is not really adequate, because the high-level structure is completely lost. For this reason we have introduced in a previous paper a new notion of high-level net processes for high-level nets which captures the high-level structure. The key notion is a high-level occurrence net K, which generalizes the well-known notion of occurrence nets from low-level to high-level nets. In contrast to the low-level case we consider high-level occurrence nets together with a set of initial markings of the input places. In this paper we show under which conditions the behavior of low-level occurrence nets and processes can be generalized to the high-level case. A key notion is the instantiation L of a high-level occurrence net K, where L is a low-level subnet of the flattening Flat(K) with isomorphic net structures of L and K. One of our main results characterizes under which conditions a high-level occurrence net - and hence a high-level net process - has unique and nonoverlapping instantiations and can be represented by the union of all its instantiations.

Related Organizations
Keywords

high-level occurrence net, Models and methods for concurrent and distributed computing (process algebras, bisimulation, transition nets, etc.)

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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!
4
Average
Top 10%
Average
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