DocumentCode :
652890
Title :
Dynamic Cloud Resource Reservation via Cloud Brokerage
Author :
Wei Wang ; Di Niu ; Baochun Li ; Ben Liang
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Toronto, Toronto, ON, Canada
fYear :
2013
fDate :
8-11 July 2013
Firstpage :
400
Lastpage :
409
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 long-term 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 approximate 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; approximate algorithms; cloud brokerage service; cloud providers; dynamic cloud resource reservation; dynamic programming; infrastructure-as-a-service clouds; large-scale Google cluster-usage traces; pricing options; Aggregates; Approximation algorithms; Dynamic programming; Equations; Heuristic algorithms; Prediction algorithms; Pricing; Cloud Brokerage; Cloud Computing; Cloud Resource Reservation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Distributed Computing Systems (ICDCS), 2013 IEEE 33rd International Conference on
Conference_Location :
Philadelphia, PA
ISSN :
1063-6927
Type :
conf
DOI :
10.1109/ICDCS.2013.20
Filename :
6681609
Link To Document :
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