An Efficient Data Dissemination Approach for Cloud Monitoring

  • Xingjian Lu
  • Jianwei Yin
  • Ying Li
  • Shuiguang Deng
  • Mingfa Zhu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7636)


Cloud computing brings dynamic resource scalability, pay-per-use billing model and simplified developing platforms, however, the monitoring of cloud today is still confronted with the flexibility, scalability, efficiency and performance problems, especially when the scale of cloud platform is being constantly expanding recent years. In this paper, we first present an efficient and intelligent monitoring architecture for cloud platform based on Data Distribution Service(DDS) and Complex Event Processing(CEP), in order to cope with these challenging issues. Then we mainly focus on the monitoring data dissemination, give more details on how DDS is used in this architecture and propose a comprehensive data delivery algorithm to achieve better accuracy and efficiency.


Cloud Monitoring Data Distribution Service Complex Event Processing 


  1. 1.
    Delgado, N., Gates, A., Roach, S.: A taxonomy and catalog of runtime software-fault monitoring tools. IEEE Transactions on Software Engineering, 859–872 (December 2004)Google Scholar
  2. 2.
    Huang, H., Wang, L.: P&P: a Combined Push-Pull Model for Resource Monitoring in Cloud Computing Environment. In: IEEE 3rd International Conference on Cloud Computing (2010)Google Scholar
  3. 3.
    White Paper from ManageEngine. Four Keys for Monitoring Cloud Services (March 2010),
  4. 4.
    Shao, J., Wei, H., Wang, Q., Mei, H.: A Runtime Model Based Monitoring Approach for Cloud. In: IEEE 3rd International Conference on Cloud Computing (2010)Google Scholar
  5. 5.
    Object Management Group. Data Distribution Service (DDS) Brief (2011)Google Scholar
  6. 6.
    Wu, E., Diao, Y., Rizvi, S.: High-Performance Complex Event Processing over Streams. In: SIGMOD 2006, Chicago, Illinois, USA, June 27-29 (2006)Google Scholar
  7. 7.
    Ryll, M., Ratchev, S.: Application of the Data Distribution Service for Flexible Manufacturing Automation. Proceedings of World Academy of Sciency, Engineering and Technology 31 (July 2008)Google Scholar
  8. 8.
    Si-Tu, F.: Event-based Monitoring and Management of the Distributed System, M.Sc. Dissertation, Shanghai Jiao Tong University, Shanghai, P.R. China (2009)Google Scholar
  9. 9.
    Baldoni, R., Bonomi, S., Lodi, G., Querzoni, L.: Data Dissemination supporting collaborative complex event processing: characteristics and open issues. In: DD4LCCI 2010, Valencia, Spain (2010)Google Scholar
  10. 10.
    Bry, F., Eckert, M., Etzion, O., Riecke, J., Paschke, A.: Event Processing Languages. Tutorial in DEBS 2009 (2009)Google Scholar
  11. 11.
    Google App Engine. Google Inc.,
  12. 12.
    Cloudstatus. Hyperic Inc.,
  13. 13.
    Han, H., Kim, S., Jung, H., Yeom, H.Y., Yoon, C., Park, J., Lee, Y.: A restful approach to the management of cloud infrastructure. In: Proc. IEEE International Conference on Cloud Computing, CLOUD 2009, September 21-25 (2009)Google Scholar
  14. 14.
    Chung, W.-C., Chang, R.-S.: Chang A new mechanism for resource monitoring in Grid computing. Future Generation Computer Systems 25, 1–7 (2009)CrossRefGoogle Scholar
  15. 15.
    Krishna, A.S., Schmidt, D.C., Klefstad, R., Corsaro, A.: Real-time CORBA Middleware. In: Mahmoud, Q. (ed.) Middleware for Communications. Wiley and Sons, New York (2003)Google Scholar
  16. 16.
    Abu-Ghazaleh, N., Lewis, M.J., Govindaraju, M.: Differential Serialization for Optimized SOAP Performance. In: Proceedings of HPDC-13: IEEE International Symposium on High Performance Distributed Computing, Honolulu, Hawaii, pp. 55–64Google Scholar
  17. 17.
    Hapner, M., Burridge, R., Sharma, R., Fialli, J., Stout, K.: Java Message Service. Sun Microsystems Inc., Santa Clara (2002)Google Scholar
  18. 18.
    Xiong, M., Parsons, J., Edmondson, J., Nguyen, H., Schmidt, D.C.: Evaluating the Performance of Publish/Subscribe Platforms for Information Management in Distributed Real-time and Embedded SystemsGoogle Scholar
  19. 19.
    Poul, N., Migliavacca, M., Pietzuch, P.: Distributed Complex Event Processing with Query Rewriting. In: DEBS 2009, Nashville, TN, USA, July 6-9 (2009)Google Scholar
  20. 20.
    Volz, M., Koldehofe, B., Rothermel, K.: Supporting Strong Reliability for Distributed Complex Event Processing Systems. In: Proceedings of 13th IEEE International Conference on High Performance Computing and Communications (HPCC 2011), Banff, Alberta, Canada, pp. 477–486 (September 2011)Google Scholar
  21. 21.
    Wu, E., Diao, Y., Rizvi, S.: High-Performance Complex Event Processing over Streams. In: SIGMOD 2006, Chicago, Illinois, USA, June 27-29 (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Xingjian Lu
    • 1
  • Jianwei Yin
    • 1
  • Ying Li
    • 1
  • Shuiguang Deng
    • 1
  • Mingfa Zhu
    • 1
  1. 1.College of Computer Science and TechnologyZhejiang UniversityHangzhouChina

Personalised recommendations