Skip to main content
SpringerLink
Log in

A CBR Approach to Allocate Computational Resources Within a Cloud Platform

  • Conference paper
  • First Online:
Intelligent Distributed Computing IX

Part of the book series: Studies in Computational Intelligence ((SCI,volume 616))

Abstract

Cloud Computing paradigm continues growing very quickly. The underlying computational infrastructure has to cope with this increase on the demand and the high number of end-users. To do so, platforms usually use mathematical models to allocate the computational resource among the offered services to the end-user. Although these mathematical models are valid and they are widely extended, they can be improved by means of use intelligent techniques. Thus, this study proposes an innovative approach based on an agent-based system that integrated a case-based reasoning system. This system is able to dynamically allocate resources over a Cloud Computing platform.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    http://www.mongodb.org.

  2. 2.

    http://bisite.usal.es.

References

  1. Alhamad, M.; Dillon, T.S., Chang, E.: Conceptual SLA framework for cloud computing (2010)

    Google Scholar 

  2. Armbrust, M., et al.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)

    Google Scholar 

  3. Beloglazov, A. Abawajy, J. Buyya, R.: Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener. Comput. Syst. 28(5), 755–768 (2012)

    Google Scholar 

  4. Braubach, L., Jander, K. Pokahr, A.: A middleware for managing non-functional requirements in cloud PaaS. In: IEEE International Conference on Cloud and Autonomic Computing (ICCAC), pp. 83–92 (2014)

    Google Scholar 

  5. Buyya, R., Beloglazov, A., Abawajy, J.: Energy-efficient management of data center resources for cloud computing: a vision, architectural elements, and open challenges. Preprint arXiv:1006.0308 (2010)

  6. Cao, B.-Q., Li, B. Xia, Q.-M.: A service-oriented QoS-assured and multi-agent cloud computing architecture. In: Cloud Computing, pp. 644–649. Springer, Berlin (2009)

    Google Scholar 

  7. Che, J., et al.: A synthetical performance evaluation of OpenVZ, Xen and KVM. In: IEEE 2010 Asia-Pacific Services Computing Conference, pp. 587–594. IEEE (2010)

    Google Scholar 

  8. Chen, W., et al.: A novel hardware assisted full virtualization technique. In: The 9th International Conference for Young Computer Scientists, pp. 1292–1297. IEEE (2008)

    Google Scholar 

  9. Chiu, D.: Elasticity in the cloud. Crossroads 16(3), 3–4 (2010)

    Google Scholar 

  10. Corchado, J.M., et al.: Replanning mechanism for deliberative agents in dynamic changing environments. Comput. Intell. 24(2), 77–107 (2008)

    Google Scholar 

  11. Corchado, J.M., Laza, R.: Constructing deliberative agents with case‐based reasoning technology. Int. J. Intell. Syst. 18(12), 1227–1241 (2003)

    Google Scholar 

  12. Fisher, P., Pant, R., Edberg, J.: Cloud Computing: Assessing Azure, Amazon EC2, Google App Engine and Hadoop for it Decision Making and Developer Career Growth. Apress, New York (2010)

    Google Scholar 

  13. Hutchins, D.:Just in time. Gower Publishing Ltd., London (1999)

    Google Scholar 

  14. Kang, J. Sim, K.M.: Cloudle: an ontology-enhanced cloud service search engine. In: Web Information Systems Engineering–WISE 2010 Workshops. Springer, Berlin, Heidelberg, pp. 416–427 (2011)

    Google Scholar 

  15. Kusic, D., et al.: Power and performance management of virtualized computing environments via lookahead control. Cluster Comput. 12(1), 1–15 (2009)

    Google Scholar 

  16. Liu, F., et al.: NIST Cloud Computing Reference Architecture, vol. 500, p. 292. NIST Special Publication (2011)

    Google Scholar 

  17. Luo, J.-Z., et al.: Cloud computing: architecture and key technologies. J. China Inst. Commun. 32(7), 3–21 (2011)

    Google Scholar 

  18. van Nguyen H., Dang Tran, F. Menaud, J.-M.: Autonomic virtual resource management for service hosting platforms. In: Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing, pp. 1–8. IEEE Computer Society (2009)

    Google Scholar 

  19. Raghavendra, R., et al.: No power struggles: coordinated multi-level power management for the data center. In: ACM SIGARCH Computer Architecture News, pp. 48–59. ACM, (2008)

    Google Scholar 

  20. Sim, K.M.: Agent-based cloud computing. IEEE Trans. Serv. Comput. 5(4), 564–577 (2012)

    Google Scholar 

  21. Talia, D.: Cloud computing and software agents: towards cloud intelligent services. In: WOA 2011, pp. 2–6

    Google Scholar 

  22. Talia, D.: Clouds meet agents: toward intelligent cloud services. IEEE Internet Comput. 16(2), 78–81 (2012)

    Google Scholar 

  23. Van Hien N., Tran, F.D., Menaud, J.-M.: SLA-aware virtual resource management for cloud infrastructures. In: Ninth IEEE International Conference on Computer and Information Technology, CIT’09, pp. 357–362. IEEE (2009)

    Google Scholar 

  24. Venticinque, S., et al.: A cloud agency for SLA negotiation and management. In:Euro-Par 2010 Parallel Processing Workshops, pp. 587–594. Springer, Berlin, Heidelberg (2011)

    Google Scholar 

  25. Von Laszewski, G., et al.: Comparison of multiple cloud frameworks. In: 2012 IEEE 5th International Conference on Cloud Computing (CLOUD), pp. 734–741. IEEE (2012)

    Google Scholar 

  26. Wang, L., et al.: Cloud computing: a perspective study. New Gener. Comput. 28(2), 137–146 (2010)

    Google Scholar 

  27. Wei, G., et al.: A game-theoretic method of fair resource allocation for cloud computing services. J. Supercomput. 54(2), 252–269 (2010)

    Google Scholar 

  28. Wen, X., et al.: Comparison of open-source cloud management platforms: OpenStack and OpenNebula. In: 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), pp. 2457–2461. IEEE (2012)

    Google Scholar 

  29. Wooldridge, M., Jennings., N.R.: Intelligent agents: theory and practice. Knowl. Eng. Rev. 10, (02), 115–152 (1995)

    Google Scholar 

  30. You, X., et al.: RAS-M: resource allocation strategy based on market mechanism in cloud computing. In: Fourth ChinaGrid Annual Conference, ChinaGrid’09, pp. 256–263. IEEE (2009)

    Google Scholar 

  31. Zhang, Q., Cheng, L., Boutaba, R.: Cloud computing: state-of-the-art and research challenges. J. Internet Serv. Appl. 1(1), 7–18 (2010)

    Google Scholar 

Download references

Acknowledgments

This work has been supported by the MICINN project TIN2012-36586-C03-03.

Author information

Authors and Affiliations

  1. Department of Computer Science and Automation Control, University of Salamanca, Plaza de la Merced s/n, 37008, Salamanca, Spain

    Fernando De la Prieta & Juan M. Corchado

  2. Department of Artificial Intelligence, Technical, University of Madrid, Bloque 2, Despacho 2101, Campus Montegancedo, Boadilla del Monte, Madrid, 28660, Spain

    Javier Bajo

Authors
  1. Fernando De la Prieta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Javier Bajo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Juan M. Corchado
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fernando De la Prieta .

Editor information

Editors and Affiliations

  1. Departamento de Informática/Centro ALGORITMI, Escola de Engenharia, Universidade do Minho, Braga, Portugal

    Paulo Novais

  2. Computer Science Department, Universidad Autónoma De Madrid, Madrid, Spain

    David Camacho

  3. Departamento de Informática/Centro ALGORITMI, Escola de Engenharia, Universidade do Minho, Braga, Portugal

    Cesar Analide

  4. LIP6, University Pierre and Marie Curie 4, Paris Codex 05, France

    Amal El Fallah Seghrouchni

  5. Software Engineering Department, Faculty of Automatics, Computers and Electronics, University of Craiova, Craiova, Romania

    Costin Badica

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

De la Prieta, F., Bajo, J., Corchado, J.M. (2016). A CBR Approach to Allocate Computational Resources Within a Cloud Platform. In: Novais, P., Camacho, D., Analide, C., El Fallah Seghrouchni, A., Badica, C. (eds) Intelligent Distributed Computing IX. Studies in Computational Intelligence, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-25017-5_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-25017-5_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25015-1

  • Online ISBN: 978-3-319-25017-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation