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Interval Optimization of Correlated Data Items in Data Broadcasting

  • Etsuko Yajima
  • Takahiro Hara
  • Masahiko Tsukamoto
  • Shojiro Nishio
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1909)

Abstract

The server strategy of repeatedly broadcasting data items can result in higher throughput than sending the requested data items to individual clients. Various methods have been studied to reduce the average response time in such systems. In this paper, we introduce a strategy to determine the optimal broadcast interval between two correlated data items. Based on these estimated optimal intervals, we propose a new scheduling strategy of a broadcast program to accommodate an environment where a large number of correlated data items exist in the broadcast program.

keywords

data broadcast data correlation scheduling strategy broadcast interval 

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References

  1. 1.
    Acharya, S., Alonso, R., Franklin, M., and Zdonik, S.: “Broadcast Disks: Data Management for Asymmetric Communication Environments,” Proc. ACM SIGMOD Conference, pp. 199–210 (1995).Google Scholar
  2. 2.
    Acharya, S., Franklin, M., and Zdonik, S.: “Dissemination-Based Data Delivery Using Broadcast Disks,” IEEE Personal Communications, Vol. 2, No. 6, pp. 50–60 (1995).CrossRefGoogle Scholar
  3. 3.
    Acharya, S., Franklin, M., and Zdonik, S.: “Disseminating Updates on Broadcast Disks,” Proc. VLDB Conference, pp. 354–365 (1996).Google Scholar
  4. 4.
    Acharya, S., Franklin, M., and Zdonik, S.: “Balancing Push and Pull for Data Broadcast,” Proc. ACM SIGMOD Conference, pp. 183–194 (1997).Google Scholar
  5. 5.
    Chen, M.S., Yu, P.S., and Wu., K.L.: “Indexed Sequential Data Broadcasting in Wireless Mobile Computing,” Proc. Int’l Conf. on Distributed Computing Systems (ICDCS), pp. 124–131 (1997).Google Scholar
  6. 6.
    Dao, S. and Perry, B.: “Information Dissemination in Hybrid Satellite/Terrestrial Networks,” Proc. Int’l Conf. on Data Engineering, Vol. 19, No. 3, pp. 12–18 (1996).Google Scholar
  7. 7.
    Franklin, M. and Zdonik, S.: “Dissemination-Based Information Systems,” Proc. Int’l Conf. on Data Engineering, Vol. 19, No. 3, pp. 20–30 (1996).Google Scholar
  8. 8.
    Hameed, S. and Vaidya, N.H.: “Log-time Algorithms for Scheduling Single and Multiple Channel Data Broadcast,” Proc. MOBICOM 97, pp. 90–99 (1997).Google Scholar
  9. 9.
    Hameed, S. and Vaidya, N.H.: “Efficient Algorithm for Scheduling Data Broadcast,” Wireless Networks, Vol. 5, No. 3, pp. 183–193 (1999).CrossRefGoogle Scholar
  10. 10.
    Hara, T., Yajima, E., Tsukamoto, M., Nishio, S., and Okui, J.: “A Scheduling Strategy of a Broadcast Program for Correlative Data,” Proc. ISC A Int’l Conf. on Computer Applications in Industry and Engineering, pp. 141–145 (Nov. 1998).Google Scholar
  11. 11.
    Imielinski, T., Viswanathan, S., and Badrinath, B.R.: “Data on Air: Organization and Access,” IEEE Transaction on Knowledge and Data Engineering, Vol. 9, No. 3, pp. 353–372 (1997).CrossRefGoogle Scholar
  12. 12.
    Stathatos, K., Roussopoulos, N., and Baras, J.: “Adaptive Data Broadcast in Hybrid Networks,” Proc. VLDB Conference, pp. 326–335 (1997).Google Scholar
  13. 13.
    Su, C.J., Tassiulas, L., and Tsotras, V.J.: “Broadcast Scheduling for Information Distribution,” Wireless Networks, Vol. 5, No. 2, pp. 137–147 (1999).CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Etsuko Yajima
    • 1
  • Takahiro Hara
    • 2
  • Masahiko Tsukamoto
    • 2
  • Shojiro Nishio
    • 2
  1. 1.Sales Department, Tokyo OfficeFM Osaka Co., LtdJapan
  2. 2.Dept. of Information Systems Eng., Grad. Sch. of EngineeringOsaka UniversityJapan

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