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Authors: Siba Mohammad ; Eike Schallehn and Sebastian Breß

Affiliation: Otto-von-Guericke-University, Germany

ISBN: 978-989-8565-52-5

Keyword(s): Cloud Data Management, Tradeoff, Optimization, Tuning, Self-tuning, Logical Cluster.

Related Ontology Subjects/Areas/Topics: Cloud Computing ; Cloud Computing Enabling Technology ; Cloud Optimization and Automation ; Dynamic Capacity and Performance Management

Abstract: Popularity and complexity of cloud data management systems are increasing rapidly. Thus providing sophisticated features becomes more important. The focus of this paper is on (self-)tuning where we contribute the following: (1) we illustrate why (self-)tuning for cloud data management is necessary but yet a much more complex task than for traditional data management, and (2) propose an model to solve some of the outlined problems by clustering nodes in zones across data management layers for applications with similar requirements.

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Paper citation in several formats:
Mohammad, S.; Schallehn, E. and Breß, S. (2013). Clustering the Cloud - A Model for (Self-)Tuning of Cloud Data Management Systems.In Proceedings of the 3rd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-8565-52-5, pages 520-524. DOI: 10.5220/0004403405200524

@conference{closer13,
author={Siba Mohammad. and Eike Schallehn. and Sebastian Breß.},
title={Clustering the Cloud - A Model for (Self-)Tuning of Cloud Data Management Systems},
booktitle={Proceedings of the 3rd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2013},
pages={520-524},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004403405200524},
isbn={978-989-8565-52-5},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - Clustering the Cloud - A Model for (Self-)Tuning of Cloud Data Management Systems
SN - 978-989-8565-52-5
AU - Mohammad, S.
AU - Schallehn, E.
AU - Breß, S.
PY - 2013
SP - 520
EP - 524
DO - 10.5220/0004403405200524

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