An Ontology-Based Approach for Automatic Cloud Service Monitoring and Management

  • Kirit J. Modi
  • Debabrata Paul Chowdhury
  • Sanjay Garg
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 645)

Abstract

Cloud computing provides an efficient, on-demand, and scalable environment for the benefit of end users by offering cloud services as per service level agreement (SLA) on which both user and cloud service providers are mutually agreed. As the number of cloud users is increasing day by day, sometimes cloud service providers unable to offer service as per SLA, which results in SLA violation. To detect SLA violation and to fulfill the user requirements from the service provider, cloud services should be monitored. Cloud service monitoring plays a critical role for both the customers and service providers as monitoring status helps service provider to improve their services; at the same time, it also helps the customers to know whether they are receiving the promised QoS or not as per the SLA. Most existing cloud service monitoring frameworks are developed toward service provider side. This raises the question of correctness and fairness of monitoring mechanism; on the other hand, if monitoring is applied at user side, then it would become overhead to the clients. To manage such issues, an ontology-based Automatic Cloud Services Monitoring and Management (ACSMM) approach is proposed, where cloud service monitoring and management would be performed at the cloud broker, which is an intermediate entity between the user and service provider. In this approach, when SLA violation is detected, it sends an alert to both clients and service providers and generates the status report. Based on this status report, broker automatically reschedules the tasks to reduce further SLA violation.

Keywords

Cloud service monitoring Service Level Agreement Cloud service Ontology Rescheduling 

References

  1. 1.
    Yashpalsinh, J., Modi, K.: Cloud computing-concepts, architecture and challenges. computing, electronics and electrical technologies (ICCEET), In: International Conference on. IEEE (2012)Google Scholar
  2. 2.
    Joshi, K., Yesha, Y., Finin, T.: Automating cloud services life cycle through semantic technologies. Serv Comput. IEEE Trans. 7(1), 109–122 (2014)CrossRefGoogle Scholar
  3. 3.
    Frey, S., Reich, C., Lüthje, C.: Key performance indicators for cloud computing SLAs. In: The Fifth International Conference on Emerging Network Intelligence, Emerging (2013)Google Scholar
  4. 4.
    Ludwig, H., Keller, A., Dan, A., King, R., Franck, R.: Web Service Level Agreement (WSLA) Language Specification. IBM Corporation, pp. 815–824 (2003)Google Scholar
  5. 5.
    Aljoumah, E., Al-Mousawi, F., Ahmad, I., Al-Shammri, M., Al-Jady, Z.: SLA in Cloud Computing Architectures: A Comprehensive Study. Int. J. Grid Distributed Comput. 8(5), 7–32 (2015)CrossRefGoogle Scholar
  6. 6.
    Zia, et al.: A framework for user feedback based cloud service monitoring. Complex, Intelligent and Software Intensive Systems (CISIS). In: 2012 Sixth International Conference on. IEEE (2012)Google Scholar
  7. 7.
    Khandelwal, H., Kompella, R., Ramasubramanian, R.: Cloud monitoring framework. Purdue UniversityGoogle Scholar
  8. 8.
    Sahai, A., Machiraju, V., Sayal, M., Jin, L., Casati, F.: Automated SLA monitoring for web services, pp. 28–41. Management Technologies for E-Commerce and E-Business Applications. Springer, Berlin Heidelberg (2002)MATHGoogle Scholar
  9. 9.
    Mohamed, S., Yousif, A., Bakri, M.: SLA Violation detection mechanism for cloud computing. Int. J. Comput. Appl. 133(6), 8–11 (2016)Google Scholar
  10. 10.
    Vaitheki, K., Urmela, S.: A SLA violation reduction technique in Cloud by Resource Rescheduling Algorithm (RRA). Int. J. Comput. Appl. Eng. Technol. 217–224 (2014)Google Scholar
  11. 11.
    Singh, S., Chana, I., Buyya, R.: STAR: SLA-aware autonomic management of cloud resources. IEEE Transactions on Cloud Computing (2017)Google Scholar
  12. 12.
    Redl, C., Breskovic, I., Brandic, I., Dustdar, S.: Automatic SLA matching and provider selection in grid and cloud computing markets. In: Proceedings of the 2012 ACM/IEEE 13th International Conference on Grid Computing. IEEE Computer Society (2012)Google Scholar
  13. 13.
    Calheiros, R., Ranjan, R., Beloglazov, A., Rose, C., Buyya, R.: CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithm. Soft. Pract. Exp. 41(1), 23–50 (2011)Google Scholar
  14. 14.
    Alhamazani, K., Ranjan, R., Rabbhi, F., Wamg, L., Mitra, K.: Cloud monitoring for optimizing the QoS of hosted applications. In: IEEE 4th International Conference on IEEE (2012)Google Scholar
  15. 15.
    Emeakaroha, V., Netto, M., Cleheiros, R., Brandic, I., Buyya, R., Rose, C.: Towards autonomic detection of SLA violations in Cloud infrastructures. Fut. Gen. Comput. Syst. 28(7), 1017–1029 (2002)CrossRefGoogle Scholar
  16. 16.
    Aceto, G., Botta, A., Donato, W., Pescape, A.: Cloud monitoring: a survey. Comput. Netw. 57.9, 57(9), 2093–2115 (2013)Google Scholar
  17. 17.
    Alhamazani K., Ranjan, R., Mitra, K., Rabhi, S., Khan, S., Guabtni, A.: An overview of the commercial cloud monitoring tools: research dimensions, design issues, and state-of-the-art. Computing, 97(4), 357–377 (2015)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  • Kirit J. Modi
    • 1
  • Debabrata Paul Chowdhury
    • 1
  • Sanjay Garg
    • 2
  1. 1.U V Patel College of EngineeringGanpat UniversityGujaratIndia
  2. 2.Nirma UniversityGujaratIndia

Personalised recommendations