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http://arxiv.org/pdf/1112.0427...
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https://dx.doi.org/10.48550/ar...
Article . 2011
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A generalized Kahn Principle for abstract asynchronous networks

Authors: Samson Abramsky;

A generalized Kahn Principle for abstract asynchronous networks

Abstract

Our general motivation is to answer the question: "What is a model of concurrent computation?". As a preliminary exercise, we study dataflow networks. We develop a very general notion of model for asynchronous networks. The "Kahn Principle", which states that a network built from functional nodes is the least fixpoint of a system of equations associated with the network, has become a benchmark for the formal study of dataflow networks. We formulate a generalized version of the Kahn Principle, which applies to a large class of non-deterministic systems, in the setting of abstract asynchronous networks; and prove that the Kahn Principle holds under certain natural assumptions on the model. We also show that a class of models, which represent networks that compute over arbitrary event structures, generalizing dataflow networks which compute over streams, satisfy these assumptions.

25 pages. Published in the Proceedings of the Symposium on Mathematical Foundations of Programming Language Semantics, Springer Lecture Notes in Computer Science vol. 442, pp. 1--21

Country
United Kingdom
Keywords

FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Quantum Physics, FOS: Mathematics, FOS: Physical sciences, Mathematics - Category Theory, Category Theory (math.CT), Quantum Physics (quant-ph), Logic in Computer Science (cs.LO)

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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!
10
Average
Top 10%
Top 10%
Green