Skip to main content

An Ant Inspired Technique for Storage Area Network Design

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3141))

Abstract

Designing storage area networks is an NP-hard problem. Previous work has focused on traditional algorithmic techniques to automatically determine fabric requirements, network topology, and flow routes. This paper looks at the ability of an ant colony optimisation algorithm to evolve new architectures. For some small networks (10 hosts, 10 devices, and single-layered) we find that we can create networks which result in savings of several thousand dollars over previously established methods. This paper is the first publication, to our knowledge, to describe the successful application of this technique to storage area network design.

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

Buying options

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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Baran, B., Sosa, R.: A new approach for AntNet routing. In: Proceedings of the Ninth International Conference on computer communications and Networks, October 2000, pp. 303–308. IEEE Computer Society, Los Alamitos (2000)

    Google Scholar 

  2. Birattari, M., Di Caro, G., Dorigo, M.: Toward the formal foundation of ant programming. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms 2002. LNCS, vol. 2463, pp. 188–201. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  3. Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence. Oxford University Press, Oxford (1999)

    MATH  Google Scholar 

  4. Bullnheirmer, B., Hartl, R.F., Strauss, C.: An improved ant system algorithm for the vehicle routing problem. Annals of Operations Research 89, 319–328 (1999)

    Article  MathSciNet  Google Scholar 

  5. Dicke, E.K.: Designing storage area networks with biologically-inspired approaches. Master’s thesis, University of Sussex (September 2003); To be published as an HP Labs Technical Report

    Google Scholar 

  6. Dorigo, M., Gambardella, L.M.: Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1(1), 53–66 (1997)

    Article  Google Scholar 

  7. Dorigo, M., Maniezzo, V., Colorni, A.: The ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics - Part B 26(1), 29–41 (1996)

    Article  Google Scholar 

  8. Maniezzo, V., Colorni, A.: The ant system applied to the quadratic assignment problem. IEEE Transactions on knowledge and Data Engineering 11(5), 769–778 (1999)

    Article  Google Scholar 

  9. Peh, L.-S., O’Sullivan, M., Wilkes, J., Ward, J.: Generating interconnect fabric requirements. US Patent #20030144822 (July 2003)

    Google Scholar 

  10. Schoonderwoerd, R., Holland, O., Bruten, J., Rothkrantz, L.: Ant-based load balancinng in telecommunications networks. Adaptive Behavior 5(2), 169–207 (1997)

    Article  Google Scholar 

  11. Socha, K., Knowles, J., Sampels, M.: A MAX-MIN ant system for the university course timetabling problem. In: Dorigo, M., Di Caro, G.A., Sampels, M. (eds.) Ant Algorithms 2002. LNCS, vol. 2463, pp. 1–13. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  12. Solnon, C.: Ants can solve constraint satisfaction problems. IEEE Transactions on Evolutionary Computation 6(4), 347–357 (2002)

    Article  Google Scholar 

  13. Steward, S., Appleby, S.: Mobile software agents for control of distributed systems based on principles of social insect behaviour. In: Singapore ICCS 1994. Conference Proceedings, November 1994, vol. 2, pp. 549–553. IEEE Computer Society, Los Alamitos (1994)

    Google Scholar 

  14. Ward, J., O’Sullivan, M., Shahoumian, T., Wilkes, J.: Appia: automatic storage area network fabric design. In: Proceedings of the FAST 2002 Conference on File and Storage Technologies, January 2002, pp. 203–217 (2002)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Dicke, E., Byde, A., Cliff, D., Layzell, P. (2004). An Ant Inspired Technique for Storage Area Network Design. In: Ijspeert, A.J., Murata, M., Wakamiya, N. (eds) Biologically Inspired Approaches to Advanced Information Technology. BioADIT 2004. Lecture Notes in Computer Science, vol 3141. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27835-1_27

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-27835-1_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23339-8

  • Online ISBN: 978-3-540-27835-1

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics