Energy-Aware Load Balancing And Application Scaling For The Cloud Ecosystem
Keywords
application scaling; energy proportional systems; idle servers; Load balancing; server consolidation
Abstract
In this paper, we introduce an energy-aware operation model used for load balancing and application scaling on a cloud. The basic philosophy of our approach is defining an energy-optimal operation regime and attempting to maximize the number of servers operating in this regime. Idle and lightly-loaded servers are switched to one of the sleep states to save energy. The load balancing and scaling algorithms also exploit some of the most desirable features of server consolidation mechanisms discussed in the literature.
Publication Date
1-1-2017
Publication Title
IEEE Transactions on Cloud Computing
Volume
5
Issue
1
Number of Pages
15-27
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/TCC.2015.2396059
Copyright Status
Unknown
Socpus ID
85027697403 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85027697403
STARS Citation
Paya, Ashkan and Marinescu, Dan C., "Energy-Aware Load Balancing And Application Scaling For The Cloud Ecosystem" (2017). Scopus Export 2015-2019. 5297.
https://stars.library.ucf.edu/scopus2015/5297