Being able to model contention for software resources (e.g., a critical section or database lock) is paramount to building performance models that capture all aspects of the delay encountered by a process as it executes. Several methods have been offered for dealing with software contention and with message blocking in client-server systems. We present in this paper a simple, straightforward, easy to understand and implement, approach to modeling software contention using queuing networks. The approach consists of a two-level iterative process. Two queuing networks are considered: one represents software resources and the other hardware resources. Multiclass models are allowed and both open and closed queuing networks can be used at the software layer. Any solution technique----exact or approximate--can be used at any of the levels. This technique falls in the general nature of fixed-point approximate models and is similar in nature to other approaches. The main difference lies in its simplicity.
End of preview. The entire article is 7 pages. To view the full-text, please rent this article to continue.
/lp/association-for-computing-machinery/simple-analytic-modeling-of-software-contention-kosc0FkLMQ
Welcome to DeepDyve! Rent Premier Research Articles and Save Up to 90%
Simple analytic modeling of software contention
Menascé, Daniel A.
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 29 (4)
Association for Computing Machinery – Mar 1, 2002
More Info
More Like This Article
View All dataSource[]=actageo&dataSource[]=aspet&dataSource[]=aaos&dataSource[]=aacc&dataSource[]=aacr&dataSource[]=aea&dataSource[]=aip&dataSource[]=ajnr&dataSource[]=ams&dataSource[]=aps_physical&dataSource[]=appi_book&dataSource[]=appi_journal&dataSource[]=apha&dataSource[]=asip&dataSource[]=asm&dataSource[]=asn&dataSource[]=aspb&dataSource[]=avs&dataSource[]=annual_reviews&dataSource[]=arxiv&dataSource[]=acm&dataSource[]=berghahn&dataSource[]=cabi&dataSource[]=clinical_trials&dataSource[]=dailymed&dataSource[]=degruyter&dataSource[]=du_press&dataSource[]=esa&dataSource[]=eu_press&dataSource[]=elsevier&dataSource[]=emerald&dataSource[]=ejtr&dataSource[]=emea&dataSource[]=epo&dataSource[]=faseb&dataSource[]=gsa&dataSource[]=health_affairs&dataSource[]=hindawi&dataSource[]=imanager&dataSource[]=imedpub&dataSource[]=informa_healthcare&dataSource[]=informs&dataSource[]=iop&dataSource[]=iucr&dataSource[]=iospress&dataSource[]=jbjs&dataSource[]=leftcoast&dataSource[]=lu_press&dataSource[]=mesharpe&dataSource[]=mary_ann_liebert&dataSource[]=medline&dataSource[]=mit_press&dataSource[]=nature&dataSource[]=oxford&dataSource[]=pier_professional&dataSource[]=pnas&dataSource[]=portlandpress&dataSource[]=psyc_articles&dataSource[]=psyc_books&dataSource[]=psyc_critiques&dataSource[]=plos_journal&dataSource[]=pubmed_central&dataSource[]=rsna&dataSource[]=rockefeller&dataSource[]=rcn&dataSource[]=ria&dataSource[]=rsc&dataSource[]=sage&dataSource[]=spie&dataSource[]=springer_journal&dataSource[]=springer&dataSource[]=taylor_francis&dataSource[]=aps&dataSource[]=the_scientist&dataSource[]=uc_press&dataSource[]=uspto_abstract&dataSource[]=wiley&dataSource[]=pct
© 2012 DeepDyve, Inc. All rights reserved.
Terms of Service | Privacy Policy
