Conventional computation models restrict to particular data structures to represent states of a computation, e.g. natural numbers, sequences, stacks, etc. Gurevich's Abstract State Machines (ASMs) take a more liberal position: any first-order structure may serve as a state. In [7] Gurevich characterizes the expressive power of sequential ASMs: he defines the class of sequential algorithms by means of only a few, amazingly general requirements and proves this class to be equivalent to sequential ASMs. In this paper we generalize Gurevich's result to distributed algorithms: we define a class of distributed algorithms by likewise general requirements and show that this class is covered by a distributed computation model based on sequential ASMs. © 2009 Springer-Verlag.
CITATION STYLE
Glausch, A., & Reisig, W. (2009). An ASM-characterization of a class of distributed algorithms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5115 LNCS, pp. 50–64). https://doi.org/10.1007/978-3-642-11447-2_4
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