Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

Sign In to gain access to subscriptions and/or personal tools.
SIMULATION
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Wang, A.-I A.
Right arrow Articles by Reiher, P.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Using Permuted States and Validated Simulation to Analyze Conflict Rates in Optimistic Replication

An-I Andy Wang

Computer Science Department Florida State University, Tallahassee, FL, USA awang{at}cs.fsu.edu

Geoff Kuenning

Computer Science Department Harvey Mudd College, Claremont, CA, USA

Peter Reiher

Computer Science Department University of California, Los Angeles, CA, USA

Optimistic replication provides high data availability in the presence of network outages. Although widely deployed, this relaXed consistency model introduces concurrent updates, whose behavior is poorly understood due to the vast state space.

This paper introduces the notion of permuted states to eliminate system states that are redundant and unreachable, which can constitute the majority of states (4069 out of 4096 for four replicas). With the aid of permuted states, we are for the first time able to construct analytical models beyond the two-replica case. By eXamining the analysis for 2 to 4 replicas, we can demystify the process of forming identical conflicts—the most common conflict type at high replication factors. Additionally, we have automated and optimized the generation of permuted states, which allows us to eXplore higher replication factors (up to 10 replicas) using hybrid techniques. It also allows us to validate our results with eXisting simulations based on actual replication mechanisms, which previously were analytically validated with only one pair of replicas.

Finally, we have discovered that update locality and bimodal access patterns are the primary factors contributing to the formation of identical conflicts.

Key Words: permuted states • optimistic replication • conflict rates

SIMULATION, Vol. 83, No. 8, 551-569 (2007)
DOI: 10.1177/0037549707085073


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?