Probabilistic analysis of causal message ordering

Li-Hsing Yen

doi:10.1109/RTCSA.2000.896420

Probabilistic analysis of causal message ordering

Li-Hsing Yen^*

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-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 language	English
Title of host publication	Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	409-413
Number of pages	5
ISBN (Electronic)	0769509304, 9780769509303
DOIs	https://doi.org/10.1109/RTCSA.2000.896420
State	Published - 12 Dec 2000
Event	7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000 - Cheju Island, Korea, Republic of Duration: 12 Dec 2000 → 14 Dec 2000

Publication series

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

Conference

Conference	7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000
Country/Territory	Korea, Republic of
City	Cheju Island
Period	12/12/00 → 14/12/00

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 14 Life Below Water

Keywords

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

Access to Document

10.1109/RTCSA.2000.896420

Cite this

Yen, L.-H. (2000). Probabilistic analysis of causal message ordering. In Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000 (pp. 409-413). Article 896420 (Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/RTCSA.2000.896420

@inproceedings{80e353e3a401446280eb9808792aa74d,

title = "Probabilistic analysis of causal message ordering",

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.",

keywords = "Computer science, Concurrent computing, Context modeling, Delay, Electric breakdown, Exponential distribution, Marine vehicles, Mobile communication, Mobile computing, Multimedia systems",

author = "Li-Hsing Yen",

year = "2000",

month = dec,

day = "12",

doi = "10.1109/RTCSA.2000.896420",

language = "English",

series = "Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "409--413",

booktitle = "Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000",

address = "美國",

note = "7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000 ; Conference date: 12-12-2000 Through 14-12-2000",

}

Yen, L-H 2000, Probabilistic analysis of causal message ordering. in Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000., 896420, Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000, Institute of Electrical and Electronics Engineers Inc., pp. 409-413, 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000, Cheju Island, Korea, Republic of, 12/12/00. https://doi.org/10.1109/RTCSA.2000.896420

Probabilistic analysis of causal message ordering. / Yen, Li-Hsing.
Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000. Institute of Electrical and Electronics Engineers Inc., 2000. p. 409-413 896420 (Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Yen, Li-Hsing

PY - 2000/12/12

Y1 - 2000/12/12

N2 - 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.

AB - 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.

KW - Computer science

KW - Concurrent computing

KW - Context modeling

KW - Delay

KW - Electric breakdown

KW - Exponential distribution

KW - Marine vehicles

KW - Mobile communication

KW - Mobile computing

KW - Multimedia systems

UR - https://www.scopus.com/pages/publications/84953284058

U2 - 10.1109/RTCSA.2000.896420

DO - 10.1109/RTCSA.2000.896420

M3 - Conference contribution

AN - SCOPUS:84953284058

T3 - Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000

SP - 409

EP - 413

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

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000

Y2 - 12 December 2000 through 14 December 2000

ER -

Yen LH. Probabilistic analysis of causal message ordering. In Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000. Institute of Electrical and Electronics Engineers Inc. 2000. p. 409-413. 896420. (Proceedings - 7th International Conference on Real-Time Computing Systems and Applications, RTCSA 2000). doi: 10.1109/RTCSA.2000.896420

Probabilistic analysis of causal message ordering

Abstract

Publication series

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UN SDGs

Keywords

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