Skip to main content

Research on the Resource Monitoring Model Under Cloud Computing Environment

  • Conference paper
Book cover Web Information Systems and Mining (WISM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6318))

Included in the following conference series:

Abstract

Resource monitoring is an important part of resource management under the cloud computing environment, which provides a better reference for resource allocation, task scheduling and load balancing. Because of the commercial applications target of billing the user for the use of resources , the high virtualization, scalability and transparency of the cloud computing environment’s resources, the existing resource monitoring methods of both distributed computing and grid computing can not satisfy the cloud computing environment completely. So, according to the characteristics of cloud computing platforms, we present a novel resource monitoring model appropriately adapted to cloud computing environment, which combines VMM (Virtual Machine Monitor) and the C/C++ called by Java to obtain the information of the resource status. Both theoretical analysis and experiments results show that the model can be used to collect resource monitoring information on nodes and VM (virtual machine), which not only meets the requirements of cloud computing platform features but also has a good property of effectiveness.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Guo, B., Wang, P., Chen, G.: Cloud computing model based on MPI. Computer Engering 12(24), 84–86 (2009)

    Google Scholar 

  2. Smith, G., Baker, M.: A Flexible Monitoring and Notification System for Distributed Resources. In: International Symposium Parallel and Distributed Computing, pp. 31–38 (2008)

    Google Scholar 

  3. Liu, Y., Gao, S.: WSRF-Based Distributed Visualization. In: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 615–619 (2009)

    Google Scholar 

  4. Zhang, J., Figueiredo, R.: Adaptive Predictor Integration for System Performance Prediction. In: Parallel and Distributed Processing Symposium, pp. 1–10 (2007)

    Google Scholar 

  5. Diaz, I., Fernandez, G., Martinm, M.: Integrating the common information model with MDS4. In: 9th IEEE/ACM International Conference on Grid Computing, pp. 298–303 (2008)

    Google Scholar 

  6. Fang, L., Hang, T., Shu, J.: Study on energy monitoring mechanism for event-driven wireless senstor networks. Sensor and Micro System 27(10), 14–17 (2008)

    Google Scholar 

  7. Nurmi, D., Wolski, R., Grzegorczyk, C.: The Eucalyptus Open-Source Cloud-Computing System. In: 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pp. 124–131 (2009)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Ge, J., Zhang, B., Fang, Y. (2010). Research on the Resource Monitoring Model Under Cloud Computing Environment. In: Wang, F.L., Gong, Z., Luo, X., Lei, J. (eds) Web Information Systems and Mining. WISM 2010. Lecture Notes in Computer Science, vol 6318. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16515-3_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-16515-3_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16514-6

  • Online ISBN: 978-3-642-16515-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics