Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Conferences, Workshops, Symposiums, and Seminars
  4. Performance Analysis of a Consensus Algorithm Combining Stochastic Activity Networks and Measurements
 
conference paper

Performance Analysis of a Consensus Algorithm Combining Stochastic Activity Networks and Measurements

Coccoli, A.
•
Urbán, P.
•
Bondavalli, A.
Show more
2002
Proceedings of the International Conference on Dependable Systems and Networks (DSN)

A. Coccoli, P. Urban, A. Bondavalli, and A. Schiper. Performance analysis of a consensus algorithm combining Stochastic Activity Networks and measurements. In Proc. Int'l Conf. on Dependable Systems and Networks (DSN), pages 551-560, Washington, DC, USA, June 2002. Protocols which solve agreement problems are essential building blocks for fault tolerant distributed applications. While many protocols have been published, little has been done to analyze their performance. This paper represents a starting point for such studies, by focusing on the consensus problem, a problem related to most other agreement problems. The paper analyzes the latency of a consensus algorithm designed for the asynchronous model with failure detectors, by combining experiments on a cluster of PCs and simulation using Stochastic Activity Networks. We evaluated the latency in runs (1) with no failures nor failure suspicions, (2) with failures but no wrong suspicions and (3) with no failures but with (wrong) failure suspicions. We validated the adequacy and the usability of the Stochastic Activity Network model by comparing experimental results with those obtained from the model. This has led us to identify limitations of the model and the measurements, and suggests new directions for evaluating the performance of agreement protocols. Keywords: quantitative analysis, distributed consensus, failure detectors, Stochastic Activity Networks, measurements

  • Files
  • Details
  • Metrics
Loading...
Thumbnail Image
Name

CUB+02.pdf

Access type

openaccess

Size

189.91 KB

Format

Adobe PDF

Checksum (MD5)

209856282253a244a349807f5f775121

Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés