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Authors: Masoumeh Tajvidi ; Michael J. Maher and Daryl Essam

Affiliation: School of Engineering and Information Technology and UNSW, Australia

Keyword(s): Cloud Computing, Resource Provisioning, Two-stage Stochastic Programming.

Abstract: Cloud computing offers a customer the possibility of the availability of large computational resources, while paying only for the resources used. However, because of uncertainty in the customers future demand and the future market price for the computational resources, obtaining these resources in a cost-effective and robust way is a difficult problem. The variety of pricing plans is a further complication. In this paper we solve this problem using two-stage stochastic programming, for the first time considering all three available pricing plans, i.e. on-demand, reservation, and spot pricing. Through our experimental implementation, we find that our model can lower the total operational cost by up to 1.5 percent compared to other solutions.

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Paper citation in several formats:
Tajvidi, M., Maher, M. J. and Essam, D. (2017). Uncertainty-aware Optimization of Resource Provisioning, a Cloud End-user Perspective. In Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER; ISBN 978-989-758-243-1; ISSN 2184-5042, SciTePress, pages 321-328. DOI: 10.5220/0006234103210328

@conference{closer17,
author={Masoumeh Tajvidi and Michael J. Maher and Daryl Essam},
title={Uncertainty-aware Optimization of Resource Provisioning, a Cloud End-user Perspective},
booktitle={Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER},
year={2017},
pages={321-328},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006234103210328},
isbn={978-989-758-243-1},
issn={2184-5042},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Cloud Computing and Services Science - CLOSER
TI - Uncertainty-aware Optimization of Resource Provisioning, a Cloud End-user Perspective
SN - 978-989-758-243-1
IS - 2184-5042
AU - Tajvidi, M.
AU - Maher, M.
AU - Essam, D.
PY - 2017
SP - 321
EP - 328
DO - 10.5220/0006234103210328
PB - SciTePress

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