Analyzing eventual leader election protocols for dynamic systems by probabilistic model checking

Gu, Jiayi, Zhou, Yu, Wu, Weigang and Chen, Taolue (2015) Analyzing eventual leader election protocols for dynamic systems by probabilistic model checking. Cloud Computing and Security: First International Conference, ICCCS 2015, Nanjing, China, August 13-15, 2015. Revised Selected Papers. In: First International Conference on Cloud Computing and Security (ICCCS 2015), 13-15 Aug 2015, Nanjing, China. ISBN 9783319270500. ISSN 0302-9743 [Conference or Workshop Item] (doi:10.1007/978-3-319-27051-7_17)

[img] PDF - Final accepted version (with author's formatting)
Restricted to Repository staff and depositor only

Download (1MB)

Abstract

Leader election protocols have been intensively studied in distributed computing, mostly in the static setting. However, it remains a challenge to design and analyze these protocols in the dynamic setting, due to its high uncertainty, where typical properties include the average steps of electing a leader eventually, the scalability etc. In this paper, we propose a novel model-based approach for analyzing leader election protocols of dynamic systems based on probabilistic model checking. In particular, we employ a leading probabilistic model checker, PRISM, to simulate representative protocol executions. We also relax the assumptions of the original model to cover unreliable channels which requires the introduction of probability to our model. The experiments confirm the feasibility of our approach.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published as a chapter in: Cloud Computing and Security,Volume 9483 of the series Lecture Notes in Computer Science, pp 192-205
Research Areas: A. > School of Science and Technology > Computer Science > Foundations of Computing group
Item ID: 19202
Depositing User: Taolue Chen
Date Deposited: 12 Apr 2016 10:04
Last Modified: 24 Jun 2021 14:43
URI: https://eprints.mdx.ac.uk/id/eprint/19202

Actions (login required)

View Item View Item

Statistics

Downloads
Activity Overview
27Downloads
334Hits

Additional statistics are available via IRStats2.