Distributed Complex Event Processing in Multiclouds

  • Vassilis StefanidisEmail author
  • Yiannis VerginadisEmail author
  • Ioannis PatiniotakisEmail author
  • Gregoris MentzasEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11116)


The last few years, the generation of vast amounts of heterogeneous data with different velocity and veracity and the requirement to process them, has significantly challenged the computational capacity and efficiency of the modern infrastructural resources. The propagation of Big Data among different processing and storage architectures, has amplified the need for adequate and cost-efficient infrastructures to host them. An overabundance of cloud service offerings is currently available and is being rapidly adopted by small and medium enterprises based on its many benefits to traditional computing models. However, at the same time the Big Data computing requirements pose new research challenges that question the adoption of single cloud provider resources. Nowadays, we discuss the emerging data-intensive applications that necessitate the wide adoption of multicloud deployment models, in order to use all the advantages of cloud computing. A key tool for managing such multicloud applications and guarantying their quality of service, even in extreme scenarios of workload fluctuations, are adequate distributed monitoring mechanisms. In this work, we discuss a distributed complex event processing architecture that follows automatically the big data application deployment in order to efficiently monitor its health status and detect reconfiguration opportunities. This proposal is examined against an illustrative scenario and is preliminary evaluated for revealing its performance results.


Distributed CEP Cloud monitoring Multiclouds Big data 



The research leading to these results has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 731664. The authors would like to thank the partners of the MELODIC project ( for their valuable advices and comments.


  1. 1.
    Zanoon, N., Al-Haj, A., Khwaldeh, S.: Cloud computing and big data is there a relation between the two: a study. Int. J. Appl. Eng. Res. 12(17), 6970–6982 (2017)Google Scholar
  2. 2.
    Hashema, I., Yaqoob, I., Anuar, N., Gani, A., Khan, S.: The rise of “big data” on cloud computing: review and open research issues. J. Inf. Syst. 47, 98–115 (2015)CrossRefGoogle Scholar
  3. 3.
    Martinez, G., Bote, M., Gómez-Sánchez, E., Cano-Parra, R.: Cloud computing and education. J. Comput. Educ. 80(C), 132–151 (2015)CrossRefGoogle Scholar
  4. 4.
    Amazon Web Services Homepage.
  5. 5.
  6. 6.
    IBM Cloud Solutions Homepage.
  7. 7.
    Rackspace Homepage.
  8. 8.
    Openstack Homepage.
  9. 9.
    VMware Homepage.
  10. 10.
    The Multi-Cloud Future: Challenges and Benefits Homepage.
  11. 11.
    Etzion, O., Niblett, P.: Event Processing in Action (20). Manning Publications Company, Greenwich (2010)CrossRefGoogle Scholar
  12. 12.
    Higashino, W.: Complex event processing as service in multi-clouds environments. Ph.D. thesis. Univerity of Western Ontario, Department of ECE, Canada (2016)Google Scholar
  13. 13.
    Cugola, G., Margara, Al.: Processing flows of information: from data stream to complex event processing. J. ACM Comput. Surv. (CSUR) 44(issue 3, article 15), 15:1–15:62 (2012)CrossRefGoogle Scholar
  14. 14.
    Boubeta-Puig, J., Ortiz, G., Medina-Bulo, I.: Approaching the Internet of Things through Integrating SOA and complex event processing. In: Sun, Z., Yearwood, J. (eds.) Handbook of Research on Demand-Driven Web Services: Theory, Technologies, and Applications, pp. 304–323. IGI Global, Hershey (2014). Scholar
  15. 15.
    Leitner, P., Inzinger, C., Hummer, W., Satzger, B., Dustdar, S.: Application-level performance monitoring of cloud services based on complex event processing paradigm. In: 5th IEEE International Conference on Service-Oriented Computing and Applications (SOCA) (2012)Google Scholar
  16. 16.
    Hirzel, M.: Partition and compose: parallel complex event processing. In: DEBS 2012 - Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems, Berlin, Germany, pp. 191–200. ACM (2012)Google Scholar
  17. 17.
    Ku, T., Long-Zhu, Y., Yuan-Hu, K.: A novel distributed complex event processing for RFID application. In: 2008 Third International Conference on Convergence and Hybrid Information Technology, Busan, South Korea (2008)Google Scholar
  18. 18.
    Paraiso, F., Hermosillo, G., Rouvoy, R., Seinturier, L.: A middleware platform to federate complex event processing. In: 2012 IEEE 16th International Enterprise Distributed Object Computing Conference (EDOC), Beijing, China, pp. 113–122 (2012)Google Scholar
  19. 19.
    Flouris, I., et al.: FERARI: a prototype for complex event processing over streaming multi-cloud platforms. In: DEBS 2016 Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems, Irvine, CA, USA, pp. 348–349 (2016)Google Scholar
  20. 20.
    Seinturier, L., Merle, P., Rouvoy, R., Romero, D., Schiavoni, V., Stefani, J.-B.: A component-based middleware platform for reconfigurable service-oriented architectures. J. Softw. Pract. Exp. (SPE) 42(5), 559–583 (2012)CrossRefGoogle Scholar
  21. 21.
    Schultz-Møller, N., Migliavacca, M., Pietzuch, P.: Distributed complex event processing with query rewriting. In: Proceedings of the Third ACM International Conference on Distributed Event-Based Systems, DEBS 2009, Nashville, Tennessee, USA (2009)Google Scholar
  22. 22.
    Mdhaffar, A., Halima, R., Jmaiel, M., Freisleben, B.: A dynamic complex event processing architecture for cloud monitoring and analysis. In: 2013 IEEE 5th International Conference on Cloud Computing Technology and Science, Bristol, UK (2013)Google Scholar
  23. 23.
    Leitner, P., Hummer, W., Satzger, B., Inzinger, C., Dustdar, S.: CloudScale- a novel middleware for building transparently scaling cloud applications. In: Proceedings of the 27th Annual ACM Symposium on Applied Computing, Trento, Italy, pp. 434–440. ACM (2012)Google Scholar
  24. 24.
    Zeginis, C., Kritikos, K., Plexoudakis, D.: Event pattern discovery for cross-layer adaptation of multi-cloud applications. Int. J. Syst. Serv.-Oriented Eng. 78–103 (2015)Google Scholar
  25. 25.
    Garcia de Prado, A., Ortiz, G., Boubeta-Puig, J.: CARED-SOA: a context-aware event-driven service oriented architecture. IEEE Access J. 5, 4646–4663 (2017)CrossRefGoogle Scholar
  26. 26.
    Garcia de Prado, A., Ortiz, G., Boubeta-Puig, J.: COLLECT: collaborative context-aware service oriented architecture for intelligent decision-making in the Internet of Things. J. Expert Syst. Appl. 85, 231–248 (2017)CrossRefGoogle Scholar
  27. 27.
    Mule Soft Homepage.
  28. 28.
    Rademakers, T., Dirksentt, J.: Open-Source ESBs in Action, 1st edn. Manning, Greenwich (2009)Google Scholar
  29. 29.
    Apache Active MQ Homepage.
  30. 30.
    Esper CEP engine Homepage.

Copyright information

© IFIP International Federation for Information Processing 2018

Authors and Affiliations

  1. 1.Institute of Communications and Computer SystemsNational Technical University of AthensZografouGreece

Personalised recommendations