Skip to main content

Advertisement

SpringerLink
Log in

A novel disjoint set division algorithm for joint scheduling and routing in wireless sensor networks

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

High network connectivity and low energy consumption are two major challenges in wireless sensor networks (WSNs). It is even more challenging to achieve both at the same time. To tackle the problem, this paper proposes a novel disjoint Set Division (SEDO) algorithm for joint scheduling and routing in WSNs. We finely divide sensors into different disjoint sets with guaranteed connectivity based on their geographical locations to monitor the interested area. We propose a class of scheduling and routing algorithms, which sequentially schedule each disjoint set to be on and off and balance the energy consumption during packet transmission. Simulation results show that SEDO outperforms existing schemes with lower packet delivery latency and longer network lifetime.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Notes

  1. Failing of all the sensors in a hop causes network partition, and thus the network cannot operate after that time.

References

  1. Ma, J., Lou, W., Wu, Y., Li, X.-Y., & Chen, G. (2009). Energy efficient tdma sleep scheduling in wireless sensor networks. In INFOCOM.

  2. Ghidini, G., & Das, S. K. (2011). An energy-efficient markov chain-based randomized duty cycling scheme for wireless sensor networks. In 31st International conference on distributed computing systems.

  3. Tian, J., Zhang, W., Wang, G., & Gao, X. (2014). 2D k-barrier duty-cycle scheduling for intruder detection in wireless sensor networks. Computer Communications, 43, 31–42.

  4. Tian, J., Wang, G., Yan, T., & Zhang, W. (2014). Detect smart intruders in sensor networks by creating network dynamics. Computer Networks, 62, 182–196.

  5. Gui, C., & Mohapatra, P. (2004). Power conservation and quality of surveillance in target tracking sensor networks. In MobiCom.

  6. Cao, Y., Guo, S., & He, T. (2012). Robust multi-pipeline scheduling in low-duty-cycle wireless sensor networks. In INFOCOM.

  7. Liu, C., Wu, K., Xiao, Y., & Sun, B. (2006). Random coverage with guaranteed connectivity: Joint scheduling for wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems, 17(6), 562–575.

  8. Rizvi, S., Qureshi, H. K., Khayam, S. A., Rakocevic, V., & Rajarajan, M. (2012). A1: An energy efficient topology control algorithm for connected area coverage in wireless sensor networks. Journal of Network and Computer Applications, 35(2), 597–605.

    Article  Google Scholar 

  9. Wang, G., Cao, G., Porta, T. L., & Berman, P. (2007). Bidding protocols for deploying mobile sensors. IEEE Transaction on Mobile Computing, 6(5), 563–576.

  10. Liu, B., Dousse, O., Wang, J., & Saipulla, A. (2008). Strong barrier coverage of wireless sensor networks. In MobiHoc.

  11. Chen, A., Li, Z., Lai, T., & Liu, C. (2011). One-way barrier coverage with wireless sensors. In INFOCOM.

  12. Chen, T., Yang, Z., Liu, Y., Guo, D., & Luo, X. (2011). A localizability-aided approach: Localization in non-localizable sensor and ad-hoc networks. In INFOCOM.

  13. Liu, W., Wang, D., Jiang, H., Liu, W., & Wang, C. (2012). Approximate convex decomposition based localization in wireless sensor networks. In INFOCOM.

  14. Huang, M., Chen, S., & Wang, Y. (2010). Minimum cost localization problem in wireless sensor networks. In SECON.

  15. Yang, Z., Cai, L., Liu, Y., & Pan, J. (2012). Environment-aware clock skew estimation and synchronization for wireless sensor networks. In INFOCOM.

  16. Zhong, Z., Chen, P., & He, T. (2011). On-demand time synchronization with predictable accuracy. In INFOCOM.

  17. Chen, Y., Wang, Q., Chang, M., & Terzis, A. (2011). Ultra-low power time synchronization using passive radio receivers. In IPSN.

  18. Slijepcevic, S., & Potkonjak, M. (2001). Power efficient organization of wireless sensor networks. In ICC.

  19. Heinzelman, W., Chandrakasan, A., & Balakrishnan, H. (2002). An application-specific protocol architecture for wireless microsensor networks. IEEE Transaction on Wireless Communications, 1(4), 660–670.

  20. Younis, O., & Fahmy, S. (2004). Distributed clustering in ad hoc sensor networks: A hybrid, energy-efficient approach. IEEE Transaction on Mobile Computing, 3(4), 366–379.

  21. Lin, J., Xiao, W., Lewis, F., & Xie, L. (2009). Energy-efficient distributed adaptive multisensor scheduling for target tracking in wireless sensor networks. IEEE Transactions on Instrumentation and Measurement, 58(6), 1886–1896.

  22. Xiao, Y., Chen, H., Wu, K., Sun, B., Zhang, Y., Sun, X., & Liu, C. (2009). Coverage and detection of a randomized scheduling algorithm in wireless sensor networks. IEEE Transactions on Computers, 59(4), 507–521.

  23. Tang, S., & Yang, L. (2012). Morello: A quality-of-monitoring oriented sensing scheduling protocol in sensor networks. In The 31st annual IEEE international conference on computer communications: Mini-conference.

  24. Bagaa, M., Derhab, A., Lasla, N., Ouadjaout, A., & Badache, N. (2012). Semi-structured and unstructured data aggregation scheduling in wireless sensor networks. In The 31st annual IEEE international conference on computer communications: Mini-conference.

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, New Jersey Institute of Technology, Newark, NJ, USA

    Jie Tian, Xiaoyuan Liang, Tan Yan, Mahesh Kumar Somashekar & Guiling Wang

  2. School of Management, New Jersey Institute of Technology, Newark, NJ, USA

    Cesar Bandera

Authors
  1. Jie Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaoyuan Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tan Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mahesh Kumar Somashekar
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Guiling Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Cesar Bandera
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jie Tian.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tian, J., Liang, X., Yan, T. et al. A novel disjoint set division algorithm for joint scheduling and routing in wireless sensor networks. Wireless Netw 21, 1443–1455 (2015). https://doi.org/10.1007/s11276-014-0862-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-014-0862-3

Keywords

Search

Navigation