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Microsearch: When Search Engines Meet Small Devices

  • Chiu C. Tan
  • Bo Sheng
  • Haodong Wang
  • Qun Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5013)

Abstract

In this paper, we present Microsearch, a search system suitable for small devices used in ubiquitous computing environments. Akin to a desktop search engine, Microsearch indexes the information inside a small device, and accurately resolves user queries. Given the very limited hardware resources, conventional search engine designs and algorithms cannot be used. We adopt information retrieval techniques for query resolution, and propose a space efficient algorithm to perform top-k query on limited hardware resources. Finally, we present a theoretical model of Microsearch to better understand the tradeoffs in system design parameters. By implementing Microsearch on actual hardware for evaluation, we demonstrate the feasibility of scaling down information retrieval systems onto very small devices.

Keywords

Smart Card Query Term User Query Small Device Query Performance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References

  1. 1.
    Abowd, G.D., Atkeson, C.G., Hong, J., Long, S., Kooper, R., Pinkerton, M.: Cyberguide: a mobile context-aware tour guide. Wirel. Netw. (1997)Google Scholar
  2. 2.
  3. 3.
    Baeza-Yates, R., Dupret, G., Velasco, H.: A study of mobile search queries in japan. In: WWW 2006 (2006)Google Scholar
  4. 4.
  5. 5.
    Chen, J., Diekema, A., Taffet, M.D., McCracken, N.J., Ozgencil, N.E., Yilmazel, O., Liddy, E.D.: Question answering: CNLP at the TREC-10 question answering track. In: Text REtrieval Conference (2001)Google Scholar
  6. 6.
    Cheverst, K., Davies, N., Mitchell, K., Friday, A.: Experiences of developing and deploying a context-aware tourist guide: the guide project. In: MobiCom 2000 (2000)Google Scholar
  7. 7.
    Cheverst, K., Davies, N., Mitchell, K., Friday, A., Efstratiou, C.: Developing a context-aware electronic tourist guide: some issues and experiences. In: CHI 2000 (2000)Google Scholar
  8. 8.
    Church, K., Smyth, B., Cotter, P., Bradley, K.: Mobile information access: A study of emerging search behavior on the mobile internet. ACM Trans. Web (2007)Google Scholar
  9. 9.
    Dai, H., Neufeld, M., Han, R.: ELF: an efficient log-structured flash file system for micro sensor nodes. In: SenSys 2004 (2004)Google Scholar
  10. 10.
    Faloutsos, C.: Access methods for text. ACM Comput. Surv. 17(1) (1985)Google Scholar
  11. 11.
    Faloutsos, C., Oard, D.W.: A survey of information retrieval and filtering methods. Technical Report CS-TR-3514 (1995)Google Scholar
  12. 12.
    Frakes, W.B., Baeza-Yates, R.A. (eds.): Information Retrieval: Data Structures and Algorithms. Prentice-Hall, Englewood Cliffs (1992)Google Scholar
  13. 13.
    French, J.C., Powell, A.L., Callan, J.P., Viles, C.L., Emmitt, T., Prey, K.J., Mou, Y.: Comparing the performance of database selection algorithms. In: Research and Development in Information Retrieval (1999)Google Scholar
  14. 14.
    Gal, E., Toledo, S.: Algorithms and data structures for flash memories. ACM Comput. Surv. 37(2) (2005)Google Scholar
  15. 15.
  16. 16.
  17. 17.
    Kamvar, M., Baluja, S.: A large scale study of wireless search behavior: Google mobile search. In: CHI 2006 (2006)Google Scholar
  18. 18.
    Kobayashi, M., Takeda, K.: Information retrieval on the web. ACM Computing Surveys 2000 (2000)Google Scholar
  19. 19.
  20. 20.
    Mathur, G., Desnoyers, P., Ganesan, D., Shenoy, P.: Capsule: An energy-optimized object storage system for memory-constrained sensor devices. In: SenSys 2006 (2006)Google Scholar
  21. 21.
    Mathur, G., Desnoyers, P., Ganesan, D., Shenoy, P.: Ultra-low power data storage for sensor networks. In: IPSN 2006 (2006)Google Scholar
  22. 22.
    Paradise, J., Mynatt, E.D.: Audio note systemGoogle Scholar
  23. 23.
    Pucheral, P., Bouganim, L., Valduriez, P., Bobineau, C.: PicoDBMS: Scaling down database techniques for the smartcard. In: VLDB 2001 (2001)Google Scholar
  24. 24.
    Rekimoto, J., Ayatsuka, Y., Hayashi, K.: Augment-able reality: Situated communication through physical and digital spaces. In: ISWC 1998 (1998)Google Scholar
  25. 25.
    Shah, C., Croft, W.B.: Evaluating high accuracy retrieval techniques. In: SIGIR 2004 (2004)Google Scholar
  26. 26.
    Starner, T., Kirsch, D., Assefa, S.: The locust swarm: An environmentally-powered, networkless location and messaging system. In: ISWC 1997 (1997)Google Scholar
  27. 27.
    Voorhees, E.M.: Overview of the TREC 2001 question answering track. In: Text REtrieval Conference (2001)Google Scholar
  28. 28.
    Wang, H., Tan, C.C., Li, Q.: Snoogle: A search engine for the physical world. In: Infocom 2008 (2008)Google Scholar
  29. 29.
    Woodhouse, D.: Jffs : The journalling flash file systemGoogle Scholar
  30. 30.
    Wookey. Yaffs: Yet another flash file systemGoogle Scholar
  31. 31.
    Yap, K.-K., Srinivasan, V., Motani, M.: Max: human-centric search of the physical world. In: SenSys 2005 (2005)Google Scholar
  32. 32.
    Zeinalipour-Yazti, D., Lin, S., Kalogeraki, V., Gunopulos, D., Najjar, W.A.: Microhash: An efficient index structure for flash-based sensor devices. In: FAST 2005 (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Chiu C. Tan
    • 1
  • Bo Sheng
    • 1
  • Haodong Wang
    • 1
  • Qun Li
    • 1
  1. 1.College of William and MaryWilliamsburg VAUSA

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