Skip to main content


eCommons@Cornell >
College of Engineering >
Computer Science >
Computer Science Technical Reports >

Please use this identifier to cite or link to this item:
Title: Failure Detection and Consensus in the Crash-Recovery Model
Authors: Aguilera, Marcos Kawazoe
Chen, Wei
Toueg, Sam
Keywords: computer science
technical report
Issue Date: Jun-1998
Publisher: Cornell University
Abstract: We study the problems of failure detection and consensus in asynchronous systems in which processes may crash and recover, and links may lose messages. We first propose new failure detectors that are particularly suitable to the crash-recovery model. We next determine under what conditions stable storage is necessary to solve consensus in this model. Using the new failure detectors, we give two consensus algorithms that match these conditions: one requires stable storage and the other does not. Both algorithms tolerate link failures and are particularly efficient in the runs that are most likely in practice --- those with no failures or failure detector mistakes. In such runs, consensus is achieved within 3d time and with 4n messages, where d is the maximum message delay and n is the number of processes in the system.
Appears in Collections:Computer Science Technical Reports

Files in This Item:

File Description SizeFormat
98-1676.pdf398.35 kBAdobe PDFView/Open
98-1676.ps516.89 kBPostscriptView/Open

Refworks Export

Items in eCommons are protected by copyright, with all rights reserved, unless otherwise indicated.


© 2014 Cornell University Library Contact Us