We propose a scheme which attempts to optimally balance the load on the servers of a clustered web farm. Solving this performance problem is crucial to achieving minimal average response time for customer requests, and thus ultimately to achieving maximal customer throughput. This short paper gives an overview of three new mathematical contributions. First, we describe a goal setting algorithm to determine the load on each server which minimizes the average customer request response time given the possibly overlapping cluster assignments of sites to servers and the current customer request load for each site. The cluster assignments, which of necessity can only be changed relatively infrequently, have a major effect on the optimal response time in the goal setting component. So, second, we describe a static algorithm which determines good assignments of sites to servers. Third, and finally, we describe a dynamic algorithm which handles the real-time server load balancing, reacting to the fluctuating customer request load in order to come as close as possible to achieving the idealized optimal average response time. We examine the performance of the overall load balancing scheme via simulation experiments.
End of preview. The entire article is 3 pages. To view the full-text, please rent this article to continue.
/lp/association-for-computing-machinery/load-balancing-for-clustered-web-farms-gzMC0kHush
Welcome to DeepDyve! Rent Premier Research Articles and Save Up to 90%
Load balancing for clustered web farms
Wolf, Joel L.; Yu, Philip S.
Follow ACM SIGMETRICS Performance Evaluation Review
, Volume 28 (4)
Association for Computing Machinery – Mar 1, 2001
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
