Advertisement

Cost and QoS Optimization of Cloud-Based Content Distribution Networks Using Evolutionary Algorithms

  • Santiago IturriagaEmail author
  • Gerardo Goñi
  • Sergio Nesmachnow
  • Bernabé Dorronsoro
  • Andrei Tchernykh
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 979)

Abstract

This work addresses the multi-objective resource provisioning problem for building cloud-based CDNs. The optimization objectives are the minimization of VM, network and storage cost, and the maximization of the QoS for the end-user. A brokering model is proposed such that a single cloud-based CDN is able to host multiple content providers applying a resource sharing strategy. Following this model, an offline multiobjective evolutionary approach is applied to optimize resource provisioning while a greedy heuristic is proposed for addressing online routing of content. Experimental results indicate the proposed approach may reduce total costs by up to 10.6% while maintaining high QoS values.

Keywords

Cloud CDN Optimization 

References

  1. 1.
    Beume, N., Naujoks, B., Emmerich, M.: SMS-EMOA: multiobjective selection based on dominated hypervolume. Eur. J. Oper. Res. 181(3), 1653–1669 (2007)CrossRefGoogle Scholar
  2. 2.
    Busari, M., Williamson, C.: ProWGen: a synthetic workload generation tool for simulation evaluation of web proxy caches. Comput. Networks 38(6), 779–794 (2002)CrossRefGoogle Scholar
  3. 3.
    Chen, F., Guo, K., Lin, J., Porta, T.L.: Intra-cloud lightning: building CDNs in the cloud. In: Proceedings of IEEE INFOCOM, pp. 433–441 (2012)Google Scholar
  4. 4.
    Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons Inc., New York (2001)zbMATHGoogle Scholar
  5. 5.
    Eshelman, L.: The CHC adaptive search algorithm: how to have safe search when engaging in nontraditional genetic recombination. In: Foundations of Genetics Algorithms, pp. 265–283. Morgan Kaufmann, San Mateo (1991)Google Scholar
  6. 6.
    Gao, G., Zhang, W., Wen, Y., Wang, Z., Zhu, W.: Towards cost-efficient video transcoding in media cloud: insights learned from user viewing patterns. IEEE Trans. Multimed. 17(8), 1286–1296 (2015)CrossRefGoogle Scholar
  7. 7.
    Hu, M., Luo, J., Wang, Y., Veeravalli, B.: Practical resource provisioning and caching with dynamic resilience for cloud-based content distribution networks. IEEE Trans. Parallel Distrib. Syst. 25(8), 2169–2179 (2014)CrossRefGoogle Scholar
  8. 8.
    Jokhio, F., Ashraf, A., Lafond, S., Lilius, J.: A computation and storage trade-off strategy for cost-efficient video transcoding in the cloud. In: Proceedings of the 39th Euromicro Conference Series on Software Engineering and Advanced Applications, pp. 365–372 (2013)Google Scholar
  9. 9.
    Nebro, A., Alba, E., Molina, G., Chicano, F., Luna, F., Durillo, J.: Optimal antenna placement using a new multi-objective CHC algorithm. In: Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation, New York, USA, pp. 876–883 (2007)Google Scholar
  10. 10.
    Papagianni, C., Leivadeas, A., Papavassiliou, S.: A cloud-oriented content delivery network paradigm: modeling and assessment. IEEE Trans. Dependable Secure Comput. 10(5), 287–300 (2013)CrossRefGoogle Scholar
  11. 11.
    Weaver, K.F., Morales, V., Dunn, S.L., Godde, K., Weaver, P.F.: Mann-whitney u and wilcoxon signed-rank. In: An Introduction to Statistical Analysis in Research: With Applications in the Biological and Life Sciences, chap. 7, pp. 297–352. Wiley Online Library (2017)Google Scholar
  12. 12.
    Xiao, W., Bao, W., Zhu, X., Wang, C., Chen, L., Yang, L.T.: Dynamic request redirection and resource provisioning for cloud-based video services under heterogeneous environment. IEEE Trans. Parallel Distrib. Syst. 27(7), 1954–1967 (2016)CrossRefGoogle Scholar
  13. 13.
    Zhang, J., Huang, H., Wang, X.: Resource provision algorithms in cloud computing: a survey. J. Network Comput. Appl. 64, 23–42 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Santiago Iturriaga
    • 1
    Email author
  • Gerardo Goñi
    • 1
  • Sergio Nesmachnow
    • 1
  • Bernabé Dorronsoro
    • 2
  • Andrei Tchernykh
    • 3
  1. 1.Universidad de la RepúblicaMontevideoUruguay
  2. 2.Universidad de CádizCádizSpain
  3. 3.Centro de Investigación Científica y de Educación Superior de EnsenadaEnsenadaMexico

Personalised recommendations