Probabilistic analysis of causal message ordering

Li-Hsing Yen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Causal message ordering (CMO) demands that messages directed to the same destinations must be delivered in an order consistent with their potential causality. In this paper, we present a modular decomposition of CMO, and evaluate the probability of breaking CMO by assuming two probabilistic models on message delays: exponential distribution and uniform distribution. These models represent the contexts where message delays are unpredictable and, respectively, unbounded and bounded. Our analysis results help in understanding the necessity of CMO schemes, and suggest a probabilistic approach to CMO: deferred sending. The effect of deferred sending is analyzed.

Original languageEnglish
Title of host publicationProceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages409-413
Number of pages5
ISBN (Electronic)0769509304, 9780769509303
DOIs
StatePublished - 12 Dec 2000
Event7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000 - Cheju Island, Korea, Republic of
Duration: 12 Dec 200014 Dec 2000

Publication series

NameProceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000

Conference

Conference7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000
Country/TerritoryKorea, Republic of
CityCheju Island
Period12/12/0014/12/00

Keywords

  • Computer science
  • Concurrent computing
  • Context modeling
  • Delay
  • Electric breakdown
  • Exponential distribution
  • Marine vehicles
  • Mobile communication
  • Mobile computing
  • Multimedia systems

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