M4CLOUD - GENERIC APPLICATION LEVEL MONITORING FOR RESOURCE-SHARED CLOUD ENVIRONMENTS

Toni Mastelic, Vincent C. Emeakaroha, Michael Maurer, Ivona Brandic

2012

Abstract

Cloud computing is a promising concept for the implementation of scalable on-demand computing infrastructures, where resources are provided in a self-managing manner based on predefined customers requirements. A Service Level Agreement (SLA), which is established between a Cloud provider and a customer, specifies these requirements. It includes terms like required memory consumption, bandwidth or service availability. The SLA also defines penalties for SLA violations when the Cloud provider fails to provide the agreed amount of resources or quality of service. A current challenge in Cloud environments is to detect any possible SLA violation and to timely react upon it to avoid paying penalties, as well as reduce unnecessary resource consumption by managing resources more efficiently. In resource-shared Cloud environments, where there might be multiple VMs on a single physical machine and multiple applications on a single VM, Cloud providers require mechanisms for monitoring resource and QoS metrics for each customer application separately. Currently, there is a lack of generic classification of application level metrics. In this paper, we introduce a novel approach for classifying and monitoring application level metrics in a resource-shared Cloud environment. We present the design and implementation of the generic application level monitoring system. Finally, we evaluate our approach and implementation, and provide a proof of concept and functionality.

References

  1. Alhamad, M., Dillon, T., and Chang, E. (2010). Conceptual SLA framework for cloud computing. In 4th IEEE International Conference on Digital Ecosystems and Technologies (DEST). IEEE.
  2. Brandic, I. (2009). Towards Self-Manageable cloud services. In Computer Software and Applications Conference, 2009. COMPSAC 7809. 33rd Annual IEEE International, volume 2. IEEE.
  3. Cao, Q., Wei, Z., and Gong, W. (2009). An optimized algorithm for task scheduling based on activity based costing in cloud computing. In 3rd International Conference on Bioinformatics and Biomedical Engineering , 2009. ICBBE. IEEE.
  4. Chamness, M. (2000). Performance tuning for the JDBC API. http://alumnus.caltech.edu/ chamness/JDBC Tuning.pdf.
  5. Cheng, X., Shi, Y., and Li, Q. (2009). A multi-tenant oriented performance monitoring, detecting and scheduling architecture based on SLA. In Joint Conferences on Pervasive Computing (JCPC). IEEE.
  6. Duy, T. V. T., Sato, Y., and Inoguchi, Y. (2010). Performance evaluation of a green scheduling algorithm for energy savings in cloud computing. In IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW). IEEE.
  7. Emeakaroha, V. C., Brandic, I., Maurer, M., and Breskovic, I. (2011a). SLA-Aware application deployment and resource allocation in clouds. In Computer Software and Applications Conference Workshops (COMPSACW), IEEE 35th Annual. IEEE.
  8. Emeakaroha, V. C., Brandic, I., Maurer, M., and Dustdar, S. (2010). Low level metrics to high level SLAs - LoM2HiS framework: Bridging the gap between monitored metrics and SLA parameters in cloud environments. In International Conference on High Performance Computing and Simulation (HPCS). IEEE.
  9. Emeakaroha, V. C., Netto, M. A. S., Calheiros, R. N., Brandic, I., Buyya, R., and De Rose, C. A. F. (2011b). Towards autonomic detection of SLA violations in cloud infrastructures. Future Generation Computer Systems.
  10. FoSII (2011). FOSII - foundations of Self-Governing ICT infrastructures. http://www.infosys.tuwien.ac.at/linksites/FOSII/.
  11. Hyperic (2010). SIGAR - system information gatherer and reporter. http://support.hyperic.com/display/SIGAR/Home.
  12. Hyperic (2011). Hyperic hq - documentation. http://support.hyperic.com/display/DOC/Installation+ Requirements.
  13. Lee, J. and Hur, S. J. (2011). Level 2 SaaS platform and platform management framework. In 13th International Conference on Advanced Communication Technology (ICACT). IEEE.
  14. Linfo (2011). The linux information project: PID definition. http://www.linfo.org/pid.html.
  15. Ludwig, H., Keller, A., Dan, A., King, R. P., and Franck, R. (2003). Web service level agreement ( WSLA ) language specification. Specification, IBM Corporation, USA.
  16. Maurer, M., Brandic, I., and Sakellariou, R. (2011). Enacting SLAs in clouds using rules. In Proceedings of the 17th international conference on Parallel processing - Volume Part I. Springer-Verlag.
  17. Mehta, A., Menaria, M., Dangi, S., and Rao, S. (2011). Energy conservation in cloud infrastructures. In Systems Conference (SysCon). IEEE.
  18. MSDN (2011). Windows development center: Processes and threads. http://msdn.microsoft.com/enus/library/windows/desktop/ms684841(v=VS.85).aspx.
  19. Norton, T. R. and Solutions, S. (1999). End-To-End Response-Time: where to measure? CMGCONFERENCE.
  20. Patel, P., Ranabahu, A., and Sheth, A. (2009). Service level agreement in cloud computing. Technical report, Knoesis Center, Wright State University, USA.
  21. Rak, M., Venticinque, S., Mhr, T., Echevarria, G., and Esnal, G. (2011). Cloud application monitoring: The mOSAIC approach. In IEEE Third International Conference on Cloud Computing Technology and Science (CloudCom). IEEE.
  22. Shao, J. and Wang, Q. (2011). A performance guarantee approach for cloud applications based on monitoring. In Computer Software and Applications Conference Workshops (COMPSACW), IEEE 35th Annual. IEEE.
  23. Shao, J., Wei, H., Wang, Q., and Mei, H. (2010). A runtime model based monitoring approach for cloud. In 3rd International Conference on Cloud Computing (CLOUD). IEEE.
Download


Paper Citation


in Harvard Style

Mastelic T., C. Emeakaroha V., Maurer M. and Brandic I. (2012). M4CLOUD - GENERIC APPLICATION LEVEL MONITORING FOR RESOURCE-SHARED CLOUD ENVIRONMENTS . In Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER, ISBN 978-989-8565-05-1, pages 522-532. DOI: 10.5220/0003928805220532


in Bibtex Style

@conference{closer12,
author={Toni Mastelic and Vincent C. Emeakaroha and Michael Maurer and Ivona Brandic},
title={M4CLOUD - GENERIC APPLICATION LEVEL MONITORING FOR RESOURCE-SHARED CLOUD ENVIRONMENTS},
booktitle={Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,},
year={2012},
pages={522-532},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003928805220532},
isbn={978-989-8565-05-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Cloud Computing and Services Science - Volume 1: CLOSER,
TI - M4CLOUD - GENERIC APPLICATION LEVEL MONITORING FOR RESOURCE-SHARED CLOUD ENVIRONMENTS
SN - 978-989-8565-05-1
AU - Mastelic T.
AU - C. Emeakaroha V.
AU - Maurer M.
AU - Brandic I.
PY - 2012
SP - 522
EP - 532
DO - 10.5220/0003928805220532