Skip to main content

Reactive Load Balancing in Distributed Database Management Systems

  • Chapter
Databases and Information Systems II

Abstract

Distributed Database Management Systems (DDBMS) offer advantages and new possibilities to traditionally centralized database environments; but decisions taken at deployment or initial configuration time, affect the final behavior of the hole system directly. So, distribution does not imply immediate improvements necessarily: some new concepts and issues need to be considered, as availability, distributed security, distributed concurrency, or load balancing. Focus in this article will be on load balancing DDBMS environments; some techniques have been presented in the past and a new mechanism is to be introduced in this article. Particularities of this new load balancing mechanism, as no centralized component need or dependency, and its probabilistic nature form the basis of a new set of load balancing technologies. Performance results are reported based on public standards for OLTP performance measurement.

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 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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. Abdelguerfi, M. and Wong, K.-F. “Parallel Database Techniques”, IEEE Computer Society Press, 1998.

    Google Scholar 

  2. Chen, M.-S., Yu, P.S., and Wu, K.-L. “Optimization of Parallel Execution for Multi-Join Queries”, IEEE Transactions on Knowledge and Data Engineering, June 1996.

    Google Scholar 

  3. Corradi, A., Leonardi, L. and Zambonelli, F. “Diffusive Load-Balancing Policies for Dynamic Applications”, IEEE Concurrency, January-March 1999.

    Google Scholar 

  4. Jonsson, J. and Vassell, J. “Evaluation and Comparison of Task Allocation and Scheduling Methods for Distributed Real–Time Systems”, IEEE 0–8186–76140/96, 1996.

    Google Scholar 

  5. Lee, C., Shih, C.-S., and Chen, Y.-H. “Optimizing Large Join Queries using a Graph-Based approach”, IEEE Transactions on Knowledge and Data Engineering, Vol.13, No.2, March/April 2001.

    Google Scholar 

  6. Li, K. and Cheng, K.H. “Complexity of Resource Allocation and Job Scheduling”, 1st. IEEE Symp. Parallel and Distributed Processing, 1989, pp. 358–365.

    Google Scholar 

  7. Lo, M.-L., Chen, M.-S., and Ravishankar, C.V. “On Optimal Processor Allocation to Support Pipelined Hash Joins”, Proc. ACM SIGMOD, May 1993, pp. 67–78.

    Google Scholar 

  8. March, S.T. and Rho, S. “Allocating Data and Operations to Nodes in Distributed Database Design”, IEEE Transactions on Knowledge and Data Engineering, Vol. 7, No. 2, 1995.

    Google Scholar 

  9. Nicola, M. and Jarke, M. “Performance Modeling of Distributed and Replicated Databases”, IEEE Transactions on Knowledge and Data Engineering, Vol.12, No.4, July/August 2000.

    Google Scholar 

  10. Rahm, E. “Dynamic Load Balancing in Parallel Database Systems”, Proc. EURO-PAR 96 Conf. LNCS, Springer-Verlag, Lyon (Invited paper ), Aug 1996.

    Google Scholar 

  11. Scheuermann, P. and Inseck, E. “Adaptive Algorithms for Join Processing in Distributed Database Systems”, Distributed and Parallel Databases Vol.5, Kluwer Academic Publishers, 1997, pp. 233–269.

    Google Scholar 

  12. Spiliopoulou, M. and Hatzoopoulos, M. “Parallel Optimization of Large Join Queries with Set Operators and Aggregates in a Parallel Environment Supporting Pipeline”, IEEE Transactions on Knowledge and Data Engineering, June 1996.

    Google Scholar 

  13. Stonebraker, M., Devine, R., and Kornacker, M. “An economic paradigm for query processing and data migration in Mariposa”, Proc. 3rd. Int’1 Symp. on Parallel and Distributed Information Systems, Sept 1994, pp. 58–67.

    Google Scholar 

  14. Özsu, M.T. and Valduriez, P. “Principles of Distributed Database Systems”, 2nd Edition, Prentice Hall, 1999.

    Google Scholar 

  15. Yu, M. J. and Shen, P.C. Y. “Adaptive Join algorithms in Dynamic Distributed Databases”, Distributed and Parallel Databases Vol.5, Kluwer Academic Publishers, 1997, pp. 5–30.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2002 Springer Science+Business Media Dordrecht

About this chapter

Cite this chapter

Muixi, J.M., Climent, A., Canals, S. (2002). Reactive Load Balancing in Distributed Database Management Systems. In: Haav, HM., Kalja, A. (eds) Databases and Information Systems II. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9978-8_3

Download citation

  • DOI: https://doi.org/10.1007/978-94-015-9978-8_3

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-6182-9

  • Online ISBN: 978-94-015-9978-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics