Soft Computing

, Volume 11, Issue 8, pp 697–716 | Cite as

Purposive behavior of honeybees as the basis of an experimental search engine

  • Reginald L. WalkerEmail author


The foraging behavior of active honeybee colonies serves as a model for Web explorers that are reactive, proactive, and robust. The Web explorers are developed to forage a simulated information ecosystem—the Internet—for useful information. Each explorer is designed to detect and report dynamic changes within the infrastructure of the Internet to its Web explorer dispatcher, which is responsible for coordinating thousands of explorers. Experimental results are presented.


Honeybee search strategies Information ecosystem dynamics Evolutionary computation Information sharing 


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  1. 1.
    Anderson D, Bansal D, Curtis D, Seshan S, Balakrishnan H (2000) System support for bandwidth management and content adaption in internet applications. In: OSDI 2000: Proceedings of fourth USENIX symposium on operating system design and implementation, ACM PressGoogle Scholar
  2. 2.
    Bagrodia R (1989) Process synchronization: design and performance evaluation of distributed algorithms. IEEE Trans Softw Eng 15(9):1053–1064CrossRefGoogle Scholar
  3. 3.
    Berners-Lee T, Cailliau R, Groff J, Pollermann B (1992) World-Wide Web: the information Universe. Electron Netw Res Appl Policy 1(1):74–82Google Scholar
  4. 4.
    Braden B, Cerpa A, Faber T, Lindell B, Phillips G, Kann J (1999) The ASP EE: an active execution environment for network control protocols. Tech. rep., Information Sciences Institute, University of Southern California, Marina del Rey, CaliforniaGoogle Scholar
  5. 5.
    Clark O, Kok R (1995) The study of ecosystem dynamics using simulation. For presentation to the Canadian Society of Agricultural Institute of Canada Annual Conference, 9–12 July 1995, Ottawa. CSAE Paper No. 95–606Google Scholar
  6. 6.
    Collins R, Jefferson D (1991) AntFarm: towards simulated evolution. In: Framer J, Langton C, Rasmussen S, Taylor C (eds) Artificial life (II). Addison-Wesley, Redwood City, pp 579–601Google Scholar
  7. 7.
    Dill S, Kumar R, McCurley K, Rajagopalan S, Sivakumar D, Tomkins A (2002) Self-similarity in the Web. ACM Transa Internet Technol (TOIT) 2(3):205–223CrossRefGoogle Scholar
  8. 8.
    Dornhaus A, Klugl F, Puppe F, Tautz J (1998) Task Selection in honeybees—experiments using multi-agent simulation. In: Wilke C, Altmeyer S, Martinez T (eds) 3rd German workshop on artificial life. Verlag Harri Deutsch, pp 171–183Google Scholar
  9. 9.
    von Eicken T, Culler D, Goldstein SC, Schauser K (1992) Active messages: a mechanism for integrated communication and computation. In: Proceedings of 19th annual international symposium on computer architecture, pp 256–266Google Scholar
  10. 10.
    Fraser A (1968) The evolution of purposive behavior. In: von Foerster H, White J, Peterson L, Russell J (eds) Purposive systems. Spartan Books, pp 15–23Google Scholar
  11. 11.
    Fritsch P (2000) Five mellow guys follow their dream: A ‘Tall Ship’ in Brazil. Wall Street Journal (Western Edition) CXLII(35):Sect A:1 (Col. 4)Google Scholar
  12. 12.
    Jung J, Sit E, Balakrishnan H, Morris R (2001) DNS performance and the Effectiveness of cachingIn: Proceedings of the first ACM SIGComm workshop on internet measurement. ACM Press, pp 153–167Google Scholar
  13. 13.
    Lachmann M, Sella G, Jablonka E (2000) On the advantages of information sharing. Proc R Soc Lond B 267:1287–1293CrossRefGoogle Scholar
  14. 14.
    Li L, Martinoli A, Abu-Mostafa Y (2002) Emergent specialization in swarm systems. In: Yin H, Allinson N, Freeman R, Keane J, Hubbard S (eds) IDEAL 2002: Proceedings of the intelligent data engineering and automated learning conference, LNCS, Vol 2412. Springer, Berlin Heidelberg Network, pp 261–266Google Scholar
  15. 15.
    Merugu S, Bhattacharjee S, Chae Y, Sanders M, Calvert K, Zegura E (1999) Bowman and CANEs: Implementation of an active network. In: Proceedings of the 37th annual Allerton conference on communication, control, and computingGoogle Scholar
  16. 16.
    Michtchenko A (2000) Search-for-service strategy and integration of LAN into Web operating system. In: Proceedings of HPC 2000. SCS Press, pp 231–235Google Scholar
  17. 17.
    Myllymaki J (2002) Effective Web Data extraction with standard XML technologies. Comput Netw 39:635–644CrossRefGoogle Scholar
  18. 18.
    Oates M, Corne D (2001) Global Web server load balancing using evolutionary computational techniques. soft comput 5:297–312zbMATHCrossRefGoogle Scholar
  19. 19.
    Oida K, Sekido M (1999) An agent-based routing system for QoS guarantees. In: Proceedings of the IEEE on systems, man, and cybernetics. IEEE, pp 833–838Google Scholar
  20. 20.
    Saxena P, Choudhury D, Gabrani G, Gupta S, Bhardwaj M, Chopra M (2002) A heuristic approach to resource locations in broadband networks. J Netw Comput Appl 25:1–35CrossRefGoogle Scholar
  21. 21.
    Srivastava A, Han E, Kumar V, Singh V (1999) Parallel formulations of decision-tree classification algorithms. Data Min Knowl Discov 3(3):237–261CrossRefGoogle Scholar
  22. 22.
    Sumpter D, Pratt S (2003) A modelling framework for understanding social insect foraging. Behav Ecol Sociobiol 53:131–144Google Scholar
  23. 23.
    Vasilakos A, Anagnostakis K, Pedrycz W (2001) Application of Computational intelligence techniques in active networks. Soft Comput 5:264–271zbMATHCrossRefGoogle Scholar
  24. 24.
    Walker R (2001) Parallel clustering system using the methodologies of evolutionary computations. In: Proceedings of CEC 2001. IEEE, Piscataway, pp 831–838Google Scholar
  25. 25.
    Walker R (2002) Using nearest neighbors to discover Web page similarities. In: Arabnia H (ed) PDPTA’02: Proceedings of the 2002 international conference on parallel and distributed processing techniques and applications. CSREA Press, pp 157–163Google Scholar
  26. 26.
    Walker R (2003) Tocorime Apicu: design of an experimental search engine using an information sharing model. Ph.D. Dissertation, University of CaliforniaGoogle Scholar
  27. 27.
    Walker R (2004) Search engine development using evolutionary computation methodologies. In: Tan K, Lim M, Yao X, Wang L (eds) Recent advances in simulated evolution and learning. World Scientific Singapore, pp 284–306Google Scholar
  28. 28.
    Walker R (2005) Hierarchical task topology for retrieving information from within a simulated information ecosystem. J Netw Comput Appli 28:77–96CrossRefGoogle Scholar
  29. 29.
    Yahoo (2003) Yahoo! news—front page. Yahoo Inc, Santa ClaraGoogle Scholar
  30. 30.
    Yuwono B, Lam S, Ying J, Lee D (1996) A world wide web resource discovery system. Worldw Web J 1(1):145–158Google Scholar

Copyright information

© Springer-Verlag 2006

Authors and Affiliations

  1. 1.Tapicu, Inc.Los AngelesUSA

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