Skip to main content
Log in

Channel dynamic adjustment in data broadcast

  • Published:
World Wide Web Aims and scope Submit manuscript

Abstract

Data broadcasting has become the preferred method to dispense data to a large number of mobile users. Current researches on on-demand data broadcast mainly propose algorithms based on a single broadcast channel or fixed multi-channel, i.e., fixed channel model. As a result of the dynamic diversity of data characteristics and client demands, the fixed channel model faces significant challenges in parallel broadcast diverse data. Further, the dynamic adjustment of the broadcast channel (dynamic channel model) based on client requests is favorable to service quality because it determines the number and sizes of channels that adapt to client demand in real-time. However, the dynamic channel model has not yet been thoroughly investigated for on-demand wireless data broadcasts. Accordingly, in this paper, a channel dynamic adjustment method (CDAM) is proposed. The innovations behind CDAM lie in three aspects. First, a data item priority evaluation and selection algorithm (S-RxW/SL) is proposed for evaluating the priority of data items and selecting the high priority data items to be considered in a broadcast cycle. Second, a weight and size average cluster algorithm (WSAC) is proposed for mining data item characteristics and clustering them. Third, based on the clustering results of WSAC, a channel splitting and data allocation algorithm (CSDA) is proposed for dynamically splitting the channel and allocating data items to the corresponding sub-channel. We compare the proposed method with some state-of-the-art scheduling methods through simulation. The theoretical findings and simulation results reveal that significantly better request loss rate (LR) can be obtained by using our method as compared to its alternatives.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9

Similar content being viewed by others

References

  1. Aksoy, D., Franklin, M.: RxW: a scheduling approach for large scale on-demand data broadcast. IEEE/ACM Trans. Networking. 7(6), 846–860 (1999)

    Article  Google Scholar 

  2. Anticaglia, S., Barsi, F., Bertossi, A.A., et al.: Efficient heuristics for data broadcasting on multiple channels. Wirel. Netw. 14(2), 219–231 (2008)

    Article  Google Scholar 

  3. Chen, J., Lee, V.C.S., Liu, K., et al.: Efficient processing of requests with network coding in on-demand data broadcast environments. Inf. Sci. 232(5), 27–43 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  4. Chung, Y., Chen, C., Lee, C.: Design and performance evaluation of broadcast algorithms for time-constrained data retrieval. IEEE Trans. Knowl. Data Eng. 18(11), 1526–1543 (2008)

    Article  Google Scholar 

  5. Dewri, R., Ray, I., Ray, I., et al.: Optimizing on-demand data broadcast scheduling in pervasive environments. In: EDBT 2008, International Conference on Extending Database Technology, Nantes, 25–29 Mar 2008, pp. 559–569. Proceedings, DBLP (2008)

  6. Dykeman, H.D., Wong, J.W.: A performance study of broadcast information delivery systems. In: INFOCOM '88. Networks: Evolution Or Revolution, Proceedings. Seventh Joint Conference of the IEEE Computer and Communcations Societies, IEEE, New Orleans, 27–31 Mar 1988, pp. 739–745. IEEE (2002)

  7. Fang, Q., Vrbsky, S.V., Dang, Y., et al.: A pull-based broadcast algorithm that considers timing constraints. In: International Conference on Parallel Processing Workshops. IEEE Computer Society, Montreal, 18 Aug 2004, pp. 46–53. IEEE (2004)

  8. Gao, X., Yang, Y., Chen, G., et al.: Global optimization for multi-channel wireless data broadcast with AH-tree indexing scheme. IEEE Trans. Comput. 65(7), 2104–2117 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  9. He, P., Shen, H.: On-demand multimedia data broadcast in MIMO wireless networks. Physical Communication. 20, 1–16 (2016)

    Article  Google Scholar 

  10. He, P., Shen, H., Tian, H.: On-demand data broadcast with deadlines for avoiding conflicts in wireless networks. J. Syst. Softw. 103(C), 118–127 (2015)

    Article  Google Scholar 

  11. Hu, W., Xia, C., Du, B., Wu, M.: An on-demanded data broadcasting scheduling considering the data item size. Wirel. Netw. 21(1), 35–56 (2015)

    Article  Google Scholar 

  12. Hu, W., Fan, C., Luo, J., et al.: An on-demand data broadcasting scheduling algorithm based on dynamic index strategy. Wireless Communications & Mobile Computing. 15(5), 947–965 (2015)

    Article  Google Scholar 

  13. Ji, H., Lee, V.C.S., Chow, C.Y., et al.: Coding-based cooperative caching in on-demand data broadcast environments. Inf. Sci. 385(C), 138–156 (2017)

    Article  Google Scholar 

  14. Jung, H., Chung, Y., Liu, L.: Processing generalized k-nearest neighbor queries on a wireless broadcast stream. Inf. Sci. 188(4), 64–79 (2012)

    Article  MathSciNet  Google Scholar 

  15. Kalyanasundaram, B., Velauthapillai, M. On-demand broadcasting under deadline. In: Proceedings of the 11th Annual European Symposium on Algorithms, pp. 313–324. (2003)

  16. Lee, W., Hu, Q., Lee, D.: A study on channel allocation for data dissemination in mobile computing environments. Mobile Networks and Applications. 1(2), 117–129 (1999)

    Article  Google Scholar 

  17. Lei, M., Vrbsky, S.V., Xiao, Y.: Scheduling on-demand data broadcast in mixed-type request environments. Comput. Netw. 54(5), 811–825 (2010)

    Article  MATH  Google Scholar 

  18. Lei, J., Jiang, T., Wu, K., et al.: Robust K -means algorithm with automatically splitting and merging clusters and its applications for surveillance data. Multimedia Tools & Applications. 75(19), 1–17 (2016)

    Article  Google Scholar 

  19. Li, L.J., Liu, H.F., Yang, Z.Y., et al.: Broadcasting methods in vehicular ad hoc networks. Journal of Software. 21(7), 1620–1634 (2010)

    Google Scholar 

  20. Lim, J.H., Naito, K., Yun, J.H., et al.: Revisiting overlapped channels: Efficient broadcast in multi-channel wireless networks. In: Computer Communications (INFOCOM), 2015 I.E. Conference on. IEEE. (2015)

  21. Liu, C.M., Su, T.C.: Broadcasting on-demand data with time constraints using multiple channels in wireless broadcast environments. Inf. Sci. 242(2), 76–91 (2013)

    Article  MathSciNet  Google Scholar 

  22. Lu, Z., Shi, Y., Wu, W., et al.: Data retrieval scheduling for multi-item requests in multi-channel wireless broadcast environments. IEEE Trans. Mob. Comput. 13(4), 752–765 (2014)

    Article  Google Scholar 

  23. Lu, Z., Wu, W., Li, W.W., Pan, M.: Efficient scheduling algorithms for on-demand wireless data broadcast. In: IEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications, 10–14 Apr 2016. Institute of Electrical and Electronics Engineers Inc. (2016). doi:10.1109/INFOCOM.2016.7524596

  24. Lv, J., Lee, V.C.S., Li, M., et al.: Supporting multi-level quality of services in data broadcast systems[J]. ‎Int. J. Sens. Netw. 18(3/4), 142–153 (2012)

  25. Lv, J., Lee, V.C.S., Li, M., et al.: Supporting multi-level quality of services in data broadcast systems. International Journal of Sensor Networks. 18(3/4), 142–153 (2015)

    Article  Google Scholar 

  26. Nawaz Ali, G.G.M., Lee, V.C.S., Chan, E., et al.: Admission control-based multichannel data broadcasting for real-time multi-item queries. IEEE Trans. Broadcast. 60(4), 589–605 (2014)

    Article  Google Scholar 

  27. Ng, J., Lee, V., Hui, C.: Client-side caching strategies and on-demand broadcast algorithms for real-time information dispatch system. IEEE Trans. Broadcast. 54(1), 24–35 (2008)

    Article  Google Scholar 

  28. Saxena, N., Pinottti, M.C.: On-line balanced k-channel data allocation with hybrid schedule per channel. In: Proceedings of the 6th international conference on Mobile data management, Ayia Napa, 9–13 May 2005, pp. 239–246. ACM, New York (2005)

  29. Stefano, C., Claudio, L., Leonardo, T.: Knowledge discovery by accuracy maximization. Proc. Natl. Acad. Sci. U. S. A. 111(14), 5117–5122 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  30. Sun, W., Qin, Y., Wu, J., et al.: Air indexing for on-demand XML data broadcast. IEEE Transactions on Parallel and Distributed Systems. 25(6), 1371–1381 (2014)

    Article  Google Scholar 

  31. Waluyo, A., Srinlvasan, B., Taniar, D., et al.: Incorporating global index multi data placement scheme for multi channels mobile broadcast environment. Lect. Notes Comput. Sci. 3824, 755–764 (2005)

    Article  Google Scholar 

  32. Wang, H., Xiao, Y., Shu, L.C.: Scheduling periodic continuous queries in real-time data broadcast environments. IEEE Trans. Comput. 61(9), 1325–1340 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  33. World Cup 98 Web Site Access Logs. http://ita.ee.lbl.gov/html/contribute/WorldCup.html[EB/OL] (1998)

  34. Wu, X., Lee, V.C.S.: Wireless real-time on-demand data broadcast scheduling with dual deadlines. Journal of Parallel and Distributed Computing. 65(6), 714–728 (2005)

    Article  Google Scholar 

  35. Xuan, P., et. al.: Broadcast on demand - efficient and timely dissemination of data in mobile environments. In: IEEE Real-Time Technology and Applications Symposium, Montreal, 9–11 Jun 1997, pp. 38–48. IEEE (1997)

  36. Zheng, B., Wu, X., Jin, X., Lee, D.: TOSA: a near-optimal scheduling algorithm for multi-channel data broadcast. In: Proceedings of the Sixth ACM International Conference on Mobile Data Management (MDM’05), Ayia Napa, 9–13 May 2005, pp. 29–37

Download references

Acknowledgements

This work is partially supported by National Natural Science Foundation of China (61572369, 61471274).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Wenbin Hu.

Additional information

This article belongs to the Topical Collection: Special Issue on Mobile Crowdsourcing

Guest Editors: Bin Guo, Xing Xie, Raghu K. Ganti, Daqing Zhang, and Zhu Wang

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, W., Qiu, Z., Nie, C. et al. Channel dynamic adjustment in data broadcast. World Wide Web 21, 803–823 (2018). https://doi.org/10.1007/s11280-017-0479-4

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11280-017-0479-4

Keywords

Navigation