DocumentCode
18036
Title
Dynamic Cloud Instance Acquisition via IaaS Cloud Brokerage
Author
Wei Wang ; Di Niu ; Ben Liang ; Baochun Li
Author_Institution
Dept. of Electr. & Comput. Eng., Univ. of Toronto, Toronto, ON, Canada
Volume
26
Issue
6
fYear
2015
fDate
June 1 2015
Firstpage
1580
Lastpage
1593
Abstract
Infrastructure-as-a-Service clouds offer diverse pricing options, including on-demand and reserved instances with various discounts to attract different cloud users. A practical problem facing cloud users is how to minimize their costs by choosing among different pricing options based on their own demands. In this paper, we propose a new cloud brokerage service that reserves a large pool of instances from cloud providers and serves users with price discounts. The broker optimally exploits both pricing benefits of longterm instance reservations and multiplexing gains. We propose dynamic strategies for the broker to make instance reservations with the objective of minimizing its service cost. These strategies leverage dynamic programming and approximation algorithms to rapidly handle large volumes of demand. Our extensive simulations driven by large-scale Google cluster-usage traces have shown that significant price discounts can be realized via the broker.
Keywords
approximation theory; cloud computing; dynamic programming; pricing; IaaS cloud brokerage; approximation algorithms; cloud brokerage service; cost management; dynamic cloud instance acquisition; dynamic programming; infrastructure-as-a-service cloud; large-scale Google cluster-usage; multiplexing gains; pricing option; Algorithm design and analysis; Approximation algorithms; Approximation methods; Clustering algorithms; Dynamic programming; Heuristic algorithms; Pricing; Cloud computing; approximation algorithm; cloud brokerage; cost management; instance reservation;
fLanguage
English
Journal_Title
Parallel and Distributed Systems, IEEE Transactions on
Publisher
ieee
ISSN
1045-9219
Type
jour
DOI
10.1109/TPDS.2014.2326409
Filename
6819811
Link To Document