Optimal Resource Rental Planning for Elastic Applications in Cloud Market

This paper studies the optimization problem of minimizing resource rental cost for running elastic applications in cloud while meeting application service requirements. Such a problem arises when excessive generated data incurs significant monetary cost on transfer and inventory in cloud. The goal o...

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Published in:2012 IEEE 26th International Parallel and Distributed Processing Symposium pp. 808 - 819
Main Authors: Han Zhao, Miao Pan, Xinxin Liu, Xiaolin Li, Yuguang Fang
Format: Conference Proceeding
Language:English
Published: IEEE 01.05.2012
Subjects:
Amazon EC2
Cloud computing
Computational modeling
Data models
Optimization
Planning
Resource Rental Planning
Spot Instance
Stochastic Optimization
Stochastic processes
Uncertainty
ISBN:1467309753, 9781467309752
ISSN:1530-2075
Online Access:Get full text
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Abstract This paper studies the optimization problem of minimizing resource rental cost for running elastic applications in cloud while meeting application service requirements. Such a problem arises when excessive generated data incurs significant monetary cost on transfer and inventory in cloud. The goal of planning is to make resource rental decisions in response to varying application progress in the most cost-effective way. To address this problem, we first develop a Deterministic Resource Rental Planning (DRRP) model, using a mixed integer linear program, to generate optimal rental decisions given fixed cost parameters. Next, we systematically analyze the predictability of the time-varying spot instance prices in Amazon EC2 and find that the best achievable prediction is insufficient to provide a close approximation to the actual prices. This fact motivates us to propose a Stochastic Resource Rental Planning (SRRP) model that explicitly considers the price uncertainty in rental decision making. Using empirical spot price data sets and realistic cost parameters, we conduct simulations over a wide range of experimental scenarios. Results show that DRRP achieves as much as 50% cost reduction compared to the no-planning scheme. Moreover, SRRP consistently outperforms its DRRP counterpart in terms of cost saving, which demonstrates that SRRP is highly adaptive to the unpredictable nature of spot price in cloud resource market.
AbstractList This paper studies the optimization problem of minimizing resource rental cost for running elastic applications in cloud while meeting application service requirements. Such a problem arises when excessive generated data incurs significant monetary cost on transfer and inventory in cloud. The goal of planning is to make resource rental decisions in response to varying application progress in the most cost-effective way. To address this problem, we first develop a Deterministic Resource Rental Planning (DRRP) model, using a mixed integer linear program, to generate optimal rental decisions given fixed cost parameters. Next, we systematically analyze the predictability of the time-varying spot instance prices in Amazon EC2 and find that the best achievable prediction is insufficient to provide a close approximation to the actual prices. This fact motivates us to propose a Stochastic Resource Rental Planning (SRRP) model that explicitly considers the price uncertainty in rental decision making. Using empirical spot price data sets and realistic cost parameters, we conduct simulations over a wide range of experimental scenarios. Results show that DRRP achieves as much as 50% cost reduction compared to the no-planning scheme. Moreover, SRRP consistently outperforms its DRRP counterpart in terms of cost saving, which demonstrates that SRRP is highly adaptive to the unpredictable nature of spot price in cloud resource market.
Author Xinxin Liu
Xiaolin Li
Han Zhao
Miao Pan
Yuguang Fang
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  surname: Han Zhao
  fullname: Han Zhao
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  surname: Miao Pan
  fullname: Miao Pan
  organization: Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA
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  surname: Xinxin Liu
  fullname: Xinxin Liu
  organization: Dept. of Comput. & Inf. Sci. & Eng., Univ. of Florida, Gainesville, FL, USA
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  surname: Xiaolin Li
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  surname: Yuguang Fang
  fullname: Yuguang Fang
  organization: Dept. of Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA
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Snippet This paper studies the optimization problem of minimizing resource rental cost for running elastic applications in cloud while meeting application service...
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StartPage 808
SubjectTerms Amazon EC2
Cloud computing
Computational modeling
Data models
Optimization
Planning
Resource Rental Planning
Spot Instance
Stochastic Optimization
Stochastic processes
Uncertainty
Title Optimal Resource Rental Planning for Elastic Applications in Cloud Market
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