Calibrating an embedded protocol on an asynchronous system

Yukiko Yamauchi, Doina Bein, Toshimitsu Masuzawa, Linda Morales, I. Hal Sudborough

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Embedding is a method to obtain new distributed protocols for other topologies from existing protocols designed for specific topologies. But the fault tolerance of the original protocol is rarely preserved in the protocol embedded in the target topology, called embedded protocol. Specifically, transient faults can affect intermediate processes along the path in the target topology that corresponds to a link in the original topology. In this paper, we propose to analyze and model the communication of the embedded protocol as unreliable communication along the links of the original protocol. We propose a particular type of unreliable channel called almost reliable channel and we show an implementation of these channels for embedding a protocol into another topology.

Original languageEnglish
Title of host publicationIntelligent Distributed Computing, Systems and Applications
Subtitle of host publicationProceedings of the 2nd International Symposium on Intelligent Distributed Computing - IDC 2008, Catania, Italy, 2008
EditorsCostin Badica, Dumitru Dan Burdescu, Giuseppe Mangioni, Vincenza Carchiolo
Pages227-236
Number of pages10
DOIs
Publication statusPublished - Sep 22 2008
Externally publishedYes

Publication series

NameStudies in Computational Intelligence
Volume162
ISSN (Print)1860-949X

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Cite this

Yamauchi, Y., Bein, D., Masuzawa, T., Morales, L., & Sudborough, I. H. (2008). Calibrating an embedded protocol on an asynchronous system. In C. Badica, D. D. Burdescu, G. Mangioni, & V. Carchiolo (Eds.), Intelligent Distributed Computing, Systems and Applications: Proceedings of the 2nd International Symposium on Intelligent Distributed Computing - IDC 2008, Catania, Italy, 2008 (pp. 227-236). (Studies in Computational Intelligence; Vol. 162). https://doi.org/10.1007/978-3-540-85257-5_23