Skip to main content
SpringerLink
Log in

QDVGDD: Query-Driven Virtual Grid based Data Dissemination for wireless sensor networks using single mobile sink

  • Published:
Wireless Networks Aims and scope Submit manuscript

Abstract

In wireless sensor networks, efficient resource management is a major concern for the battery operated sensor nodes. Data collection using mobile sink(s) is considered as a good strategy to prolong network lifetime and improve network coverage. Most of the existing mobile sink based data collection schemes operate in event driven or periodic sensing modes. There are several application environments, which dictate query driven data collection using a mobile sink e.g., a mobile sink might require reinforced data reporting from one particular network segment compared to others. In this regard, the existing query driven data collection schemes either impose too many constraints on network operation or poorly perform when delivering the requested data to a mobile sink with variable speed. In this paper we propose Query-Driven Virtual Grid based Data Dissemination (QDVGDD) scheme that aims to improve data delivery performance to a mobile sink. The proposed scheme makes use of a virtual infrastructure thereby causing minimal network control overheads while delivering the requested data with high quality of service to the mobile sink. We carried out extensive simulation works in NS-2.35 to evaluate the performance of our QDVGDD at different sink’s speeds and network sizes. Simulation results reveal improved performance of QDVGDD in terms of data delivery latency, data delivery ratio, average energy consumption, and estimated network traffic as compared to other state-of-the-art.

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
Fig. 14
Fig. 15

Similar content being viewed by others

References

  1. Cook, D. J., Augusto, J. C., & Jakkula, V. R. (2009). Ambient intelligence: Technologies, applications, and opportunities. Pervasive and Mobile Computing, 5(4), 277–298.

    Article  Google Scholar 

  2. Tacconi, D., Miorandi, D., Carreras, I., Chiti, F., & Fantacci, R. (2010). Using wireless sensor networks to support intelligent transportation systems. Ad Hoc Networks, 8(5), 462–473.

    Article  Google Scholar 

  3. Ammari, H. M., & Das, S. K. (2008). A trade-off between energy and delay in data dissemination for wireless sensor networks using transmission range slicing. Computer Communications, 31(9), 1687–1704.

    Article  Google Scholar 

  4. Anisi, M. H., Abdullah, A. H., Razak, S. A., & Ngadi, M. A. (2012). An overview of data routing approaches for wireless sensor networks. Sensors (Basel), 12(4), 3964–3996.

    Article  Google Scholar 

  5. Muthu Krishnan, A., & Ganesh Kumar, P. (2016). An effective clustering approach with data aggregation using multiple mobile sinks for heterogeneous WSN. Wireless Personal Communications: An International Journal, 90(2), 423–434.

    Article  Google Scholar 

  6. Kinalis, A., Nikoletseas, S., Patroumpa, D., & Rolim, J. (2014). Biased sink mobility with adaptive stop times for low latency data collection in sensor networks. Information Fusion, 15, 56–63.

    Article  Google Scholar 

  7. Tunca, C., Isik, S., Donmez, M. Y., & Ersoy, C. (2014). Distributed mobile sink routing for wireless sensor networks: A survey. IEEE Communications Surveys & Tutorials, 16(2), 877–897.

    Article  Google Scholar 

  8. Khan, A. W., Abdullah, A. H., Anisi, M. H., & Bangash, J. I. (2014). A comprehensive study of data collection schemes using mobile sinks in wireless sensor networks. Sensors (Basel), 14(2), 2510–2548.

    Article  Google Scholar 

  9. Sabor, N., Sasaki, S., Abo-Zahhad, M., & Ahmed, S. M. (2017). A comprehensive survey on hierarchical-based routing protocols for mobile wireless sensor networks: Review, taxonomy, and future directions. Wireless Communications and Mobile Computing, 2017, 1–23.

    Article  Google Scholar 

  10. Saleh, A. I., Abo-Al-Ez, K. M., & Abdullah, A. A. (2017). A Multi-Aware Query Driven (MAQD) routing protocol for mobile wireless sensor networks based on neuro-fuzzy inference. Journal of Network and Computer Applications, 88, 72–98.

    Article  Google Scholar 

  11. Wang, G., Wang, T., Jia, W., Guo, M., & Li, J. (2009). Adaptive location updates for mobile sinks in wireless sensor networks. The Journal of Supercomputing, 47(2), 127–145.

    Article  Google Scholar 

  12. Khan, A. W., Abdullah, A. H., Razzaque, M. A., & Bangash, J. I. (2015). VGDRA: a virtual grid-based dynamic routes adjustment scheme for mobile sink-based wireless sensor networks. IEEE Sensors Journal, 15(1), 526–534.

    Article  Google Scholar 

  13. Sara, G. S., & Sridharan, D. (2014). Routing in mobile wireless sensor network: A survey. Telecommunication Systems, 57(1), 51–79.

    Article  Google Scholar 

  14. Anisi, M. H., & Abdullah, A. H. (2015). Efficient data reporting in intelligent transportation systems. Networks and Spatial Economics, 16(2), 623–642.

    Article  MathSciNet  MATH  Google Scholar 

  15. Erman, A., Dilo, A., & Havinga, P. (2012). A virtual infrastructure based on honeycomb tessellation for data dissemination in multi-sink mobile wireless sensor networks. EURASIP Journal on Wireless Communications and Networking, 2012(1), 1–54.

    Article  Google Scholar 

  16. Lee, E., Park, S., Oh, S., & Kim, S. H. (2014). Rendezvous-based data dissemination for supporting mobile sinks in multi-hop clustered wireless sensor networks. Wireless Networks, 20(8), 2319–2336.

    Article  Google Scholar 

  17. Oliveira, H. A. B. F., Barreto, R. S., Fontao, A. L., Loureiro, A. A. F., & Nakamura, E. F. (2010). A novel greedy forward algorithm for routing data toward a high speed sink in wireless sensor networks. In 2010 proceedings of 19th international conference on computer communications and networks (pp. 1–7).

  18. Kim, J., In, J., Hur, K., Kim, J., & Eom, D. (2010). An intelligent agent-based routing structure for mobile sinks in WSNs. IEEE Transactions on Consumer Electronics, 56(4), 2310–2316.

    Article  Google Scholar 

  19. Ma, J., Chen, C., & Salomaa, J. P. (2008). mWSN for large scale mobile sensing. Journal of Signal Processing Systems, 51(2), 195–206.

    Article  Google Scholar 

  20. Luo, H., Ye, F., Cheng, J., Lu, S., & Zhang, L. (2005). TTDD: two-tier data dissemination in large-scale wireless sensor networks. Wireless Networks, 11(1–2), 161–175.

    Article  Google Scholar 

  21. Tang, B., Wang, J., Geng, X., Zheng, Y., & Kim, J. (2012). A novel data retrieving mechanism in wireless sensor networks with path-limited mobile sink. International Journal of Grid and Distributed Computing, 5(3), 133–140.

    Google Scholar 

  22. Hamida, E. B. & Chelius, G. (2008). A line-based data dissemination protocol for wireless sensor networks with mobile sink. In 2008 IEEE international conference on communications (pp. 2201–2205).

  23. Manjeshwar, A., & Agrawal, D. P. (2001). TEEN: A routing protocol for enhanced efficiency in wireless sensor networks. In Proceedings 15th international parallel and distributed processing symposium. IPDPS 2001, (Vol. 1, pp. 2009–2015).

  24. Manjeshwar A., & Agrawal, D. P. (2002). APTEEN: A hybrid protocol for efficient routing and comprehensive information retrieval in wireless sensor networks. In Proc. 16th Int. Parallel Distrib. Process. Symp.

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

    Article  Google Scholar 

  26. Heinzelman, W. R., Chandrakasan, A., & Balakrishnan, H. (2000) Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd annual hawaii international conference on system sciences (Vol. 1, No. c, pp. 1–10).

Download references

Acknowledegment

This paper was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University. The authors, therefore, acknowledge with thanks to DSR’s technical and financial support.

Author information

Authors and Affiliations

  1. Faculty of Computing and Information Technology in Rabigh, King Abdulaziz University, Jeddah, Saudi Arabia

    Abdul Waheed Khan

  2. Department of Computing, Abasyn University, Peshawar, Pakistan

    Javed Iqbal Bangash

  3. Faculty of Computer System Engineering, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah, Pakistan

    Adnan Ahmed

  4. Faculty of Computing, Universiti Teknologi Malaysia (UTM), Johor Bahru, Malaysia

    Abdul Hanan Abdullah

Authors
  1. Abdul Waheed Khan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Javed Iqbal Bangash
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Adnan Ahmed
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Abdul Hanan Abdullah
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Abdul Waheed Khan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khan, A.W., Bangash, J.I., Ahmed, A. et al. QDVGDD: Query-Driven Virtual Grid based Data Dissemination for wireless sensor networks using single mobile sink. Wireless Netw 25, 241–253 (2019). https://doi.org/10.1007/s11276-017-1552-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11276-017-1552-8

Keywords

Search

Navigation