Clustering the Cloud - A Model for (Self-)Tuning of Cloud Data Management Systems

Siba Mohammad, Eike Schallehn, Sebastian Breß

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.

References

  1. Ahmad, F., Chakradhar, S. T., Raghunathan, A., and Vijaykumar, T. N. (2012). Tarazu: Optimizing MapReduce On Heterogeneous Clusters. SIGARCH, 40(1):61-74.
  2. Bostoen, T., Mullender, S., and Berbers, Y. (2012). Analysis of disk power management for data-center storage systems. In e-Energy, pages 2:1-2:10. ACM.
  3. Capriolo, E. (2011). Cassandra High Performance Cookbook. Packt Publishing.
  4. Chen, Y., Ganapathi, A. S., Griffith, R., and Katz, R. H. (2010). Towards understanding cloud performance tradeoffs using statistical workload analysis and replay. Technical report, EECS Department, University of California, Berkeley.
  5. Cooper, B. F., Silberstein, A., Tam, E., Ramakrishnan, R., and Sears, R. (2010). Benchmarking Cloud Serving Systems with YCSB. In SoCC, pages 143-154. ACM.
  6. Dahbur, K., Mohammad, B., and Tarakji, A. B. (2011). A survey of risks, threats and vulnerabilities in cloud
Download


Paper Citation


in Harvard Style

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


in Bibtex Style

@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},
}


in EndNote Style

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