ADAPTING CLOUD-BASED APPLICATIONS THROUGH A COORDINATED AND OPTIMIZED RESOURCE ALLOCATION APPROACH

Patrizia Scandurra, Claudia Raibulet, Pasqualina Potena, Raffaela Mirandola, Rafael Capilla

2012

Abstract

Cloud computing is getting an enormous popularity for software companies as a way to save and optimize the cost of large hardware and software infrastructure organizations demand. Also, the cooperation between cloud layers constitutes a timely research challenge as allocation and optimization of (often virtualized) resources is many times done in isolation or with poor interaction. In this paper we propose a framework that adapts a cloud-based software application by providing an enhanced assembly of resources using the Pareto-optimal solution to optimize the resource allocation with tight cooperation between the cloud layers.

References

  1. Alrifai, M. and Risse, T. (2009). Combining global optimization with local selection for efficient qos-aware service composition. In WWW, pages 881-890.
  2. Baker, T., Taleb-Bendiab, A., Randles, M., and Karam, Y. (2010). Support for adaptive cloud-based applications via intention modelling. In Proc. of 3rd International Symposium on Web Services.
  3. Bucchiarone, A., Cappiello, C., Nitto, E. D., Kazhamiakin, R., Mazza, V., and Pistore, M. (2010). Design for adaptation of service-based applications: Main issues and requirements. In ICSOC/ServiceWave 2009 Workshops, LNCS, pages 467-476.
  4. Censor, Y. (1977). Pareto Optimality in Multiobjective Problems. Appl. Math. Optimiz., 4:41-59.
  5. Cheng, B. H. C. et al. (2009). Software engineering for selfadaptive systems: A research roadmap. In Software Engineering for Self-Adaptive Systems, pages 1-26.
  6. Dai, Y.-S., Yang, B., Dongarra, J., and Zhang, G. (2009). Cloud service reliability: Modeling and analysis. Proc. of 15th Pacific Rim Inter. Symp. on Depend. Comp.
  7. Jung, G., Hiltunen, M. A., Joshi, K. R., Schlichting, R. D., and Pu, C. (2010). Mistral: Dynamically managing power, performance, and adaptation cost in cloud infrastructures. Distributed Computing Systems, International Conference on, 0:62-73.
  8. Li, J., Chinneck, J., Woodside, M., Litoiu, M., and Iszlai, G. (2009). Performance model driven qos guarantees and optimization in clouds. In Proc. of the ICSE Workshop on Software Engineering Challenges of Cloud Computing, CLOUD 7809, pages 15-22.
  9. Litoiu, M., Woodside, M., Wong, J., Ng, J., and Iszlai, G. (2010). A business driven cloud optimization architecture. In Proceedings of the 2010 ACM Symposium on Applied Computing, SAC 7810, pages 380-385. ACM.
  10. Marler, R. and Arora, J. (2004). Survey of multi-objective optimization methods for engineering. Structural and Multidisciplinary Optimization, 26:369-395.
  11. Mell, P. and Grance, T. (September 2011). The NIST definition of cloud computing. http://csrc.nist.gov/publications/nistpubs/800- 145/SP800-145.pdf.
  12. Nurmi, D., Wolski, R., Grzegorczyk, C., Obertelli, G., Soman, S., Youseff, L., and Zagorodnov, D. (2009). The eucalyptus open-source cloud-computing system. In Cappello, F., Wang, C.-L., and Buyya, R., editors, CCGRID, pages 124-131. IEEE Computer Society.
  13. Papakos, P., Capra, L., and Rosenblum, D. S. (2010). Volare: context-aware adaptive cloud service discovery for mobile systems. In Proceedings of the 9th International Workshop on Adaptive and Reflective Middleware, ARM 7810, pages 32-38.
  14. SCA (2007). OSOA. Service Component Architecture (SCA) www.osoa.org.
  15. SCAspec (2007). SCA Assembly Model Specification, Version 1.00, March 15 2007.
  16. Tsai, W.-T., Sun, X., and Balasooriya, J. (2010). Serviceoriented cloud computing architecture. Information Technology: New Generations, Third International Conference on, pages 684-689.
  17. Tuscany (2010). Apache Tuscany. http://tuscany. apache.org/.
  18. Xu, M., Cui, L., Wang, H., and Bi, Y. (2009). A multiple qos constrained scheduling strategy of multiple workflows for cloud computing. Parallel and Distributed Processing with Applications, International Symposium on, 0:629-634.
  19. Yau, S. and An, H. (2009). Adaptive resource allocation for service-based systems. In Internetware 7809: Proceedings of the First Asia-Pacific Symposium on Internetware.
  20. Zou, G., Chen, Y., Yang, Y., Huang, R., and Xu, Y. (2010). Ai planning and combinatorial optimization for web service composition in cloud computing. In Proc. International Conference on Cloud Computing and Virtualization (CCV-10).
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Paper Citation


in Harvard Style

Scandurra P., Raibulet C., Potena P., Mirandola R. and Capilla R. (2012). ADAPTING CLOUD-BASED APPLICATIONS THROUGH A COORDINATED AND OPTIMIZED RESOURCE ALLOCATION APPROACH . In Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-8565-05-1, pages 355-364. DOI: 10.5220/0003919903550364


in Bibtex Style

@conference{closer12,
author={Patrizia Scandurra and Claudia Raibulet and Pasqualina Potena and Raffaela Mirandola and Rafael Capilla},
title={ADAPTING CLOUD-BASED APPLICATIONS THROUGH A COORDINATED AND OPTIMIZED RESOURCE ALLOCATION APPROACH},
booktitle={Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2012},
pages={355-364},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003919903550364},
isbn={978-989-8565-05-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - ADAPTING CLOUD-BASED APPLICATIONS THROUGH A COORDINATED AND OPTIMIZED RESOURCE ALLOCATION APPROACH
SN - 978-989-8565-05-1
AU - Scandurra P.
AU - Raibulet C.
AU - Potena P.
AU - Mirandola R.
AU - Capilla R.
PY - 2012
SP - 355
EP - 364
DO - 10.5220/0003919903550364