Skip to main content

Advertisement

SpringerLink
Log in

A Novel Sensor Node Deployment using Low Discrepancy Sequences for WSN

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

The foremost challenge in designing Wireless Sensor Networks (WSNs) is careful node placement. Sensor Node placement is a one of the powerful optimization technique for accomplishing the anticipated goals. This paper focuses on categories of node deployment in WSN. The paper highlights various problems and identifies the different objectives in sensor node deployment. The paper proposes a novel node deployment strategy based on Quasi- random method of low-discrepancy sequences to increase the lifetime and the coverage of the network. The aim of the paper is to study how the node deployment affects the different QoS parameters such as packet delivery ratio, average energy consumption, delay, etc. with various multi-objective routing algorithms WSN. To validate the proposal simulation, results are presented in this paper. The paper concludes with the future outlook.

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

Similar content being viewed by others

References

  1. Bhateja, V., Krishn, A., Patel, H., & Sahu, A. (2015). Medical image fusion in wavelet and ridgelet domains: A comparative evaluation. International Journal of Rough Sets and Data Analysis (IJRSDA), 2(2), 78–91.

    Article  Google Scholar 

  2. Cinque, M., Coronato, A., & Testa, A. (2012). Dependable services for mobile health monitoring systems. International Journal of Ambient Computing and Intelligence (IJACI), 4(1), 1–15.

    Article  Google Scholar 

  3. Kumar, S., & Nagarajan, N. (2013). Integrated network topological control and key management for securing wireless sensor networks. International Journal of Ambient Computing and Intelligence (IJACI), 5(4), 12–24.

    Article  Google Scholar 

  4. Nizar Banu, P. K., & Andrews, S. (2015). Performance analysis of hard and soft clustering approaches for gene expression data. International Journal of Rough Sets and Data Analysis (IJRSDA), 2(1), 58–69.

    Article  Google Scholar 

  5. Pantazis, N., Nikolidakis, S., & Vergados, D. (2013). Energy-efficient routing protocols in wireless sensor networks: A survey. Journal of IEEE Communications Surveys and Tutorials, 15(2), 551–591.

    Article  Google Scholar 

  6. Yessad, S., Bouallouche-Medjkoune, L., & Aïssani, D. (2014). A cross-layer routing protocol for balancing energy consumption in wireless sensor networks. Springer Journal of Wireless Personal Communications, 81(3), 1303–1320.

    Article  Google Scholar 

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

    Article  Google Scholar 

  8. Kulkarni, N., Prasad, R., Cornean, H., & Gupta, N. (2011). Performance Evaluation of AODV, DSDV & DSR for Quasi Random Deployment of Sensor Nodes in Wireless Sensor Networks. In IEEE International Conference on Devices and Communications (ICDeCom-11), (pp. 1–5).

  9. Xing, X., Xie, D., & Sun, Z. (2015). An approximate optimal coverage set algorithm in wireless sensor networks. In IEEE Seventh International Conference on Advanced Computational Intelligence (ICACI), (pp. 300–305).

  10. Horvat, G., Zagar, D., & Vinko, D. (2014). Influence of node deployment parameters on QoS in large-scale WSN. In IEEE 3rd Mediterranean Conference on Embedded Computing (MECO), (pp. 202–205).

  11. Oliveira, L. M., & Rodrigues, J. J. (2011). Wireless sensor networks: a survey on environmental monitoring. Journal Communication, 6(2), 143–151.

    Article  Google Scholar 

  12. Durisic, M. P., Tafa, Z., Dimic, G., & Milutinovic, V. (2012). A survey of military applications of wireless sensor networks. In IEEE Mediterranean conference on embedded computing (MECO), (pp. 196–199).

  13. Liu, G., Tan, R., Zhou, C. M., González, S., Cao, H., Zhang, Y., et al. (2013). Enabling low bit-rate and reliable video surveillance over practical wireless sensor network. Journal Supercomputing, 65(1), 287–300.

    Article  Google Scholar 

  14. Honghai, Z., & Jennifer, C., H. (2005). Maintaining sensing coverage and connectivity in large sensor networks. In Handbook on Theoretical and Algorithmic Aspects of Sensor, AdHocWireless and Peer-to-Peer Networks, Auerbach Publications.

  15. Ghosh, A., & Das, S. K. (2006). Coverage and connectivity issues in wireless sensor networks. In R. Shorey (Ed.), Mobile, Wireless, and Sensor Networks: Technology, Applications, and Future Directions, John Wiley & Sons, (pp.221–256).

  16. Poe, W. Y., & Schmitt, J. B. (2009). Node Deployment in Large Wireless Sensor Networks: Coverage, Energy Consumption, and Worst-case Delay (pp. 1–8). AINTEC: Proc. ACM.

    Google Scholar 

  17. Abo-Zahhad, M., Sabor, N., Sasaki, S., & Ahmed, S. M. (2016). A centralized immune-Voronoi deployment algorithm for coverage maximization and energy conservation in mobile WSNs. Journal of Information Fusion, Elsevier, 30, 36–51.

    Article  Google Scholar 

  18. Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: A survey on recent developments and potential synergies. Journal of Supercomputing, 68(1), 1–48.

    Article  Google Scholar 

  19. Kapnadak, V., & Coyle, E. J. (2014). Optimal non-uniform deployment of sensors for distributed detection in wireless sensor networks. ACM Transaction Sensor Network, 10, 1–27.

    Article  Google Scholar 

  20. Sevgia, C., & Koçyiğitb, A. (2014). Optimal deployment in randomly deployed heterogeneous WSNs: A connected coverage approach. Journal of Network and Computer Applications., 46, 182–197.

    Article  Google Scholar 

  21. Sengupta, S., Das, S., Nasir, M. D., & Panigrahi, B. K. (2012). Multi-objective node deployment in WSNs. In search of an optimal trade-off among coverage, lifetime, energy consumption and connectivity. Engineering Applications of Artificial Intelligence, 26, 405–416.

    Article  Google Scholar 

  22. Ramalakshmi, R., & Radhakrishnan, S. (2013). Coverage and connectivity guaranteed deterministic deployment pattern for WSN. Computer Networks & Communications (NetCom), 13, 341–347.

    Article  Google Scholar 

  23. Halder, S., Ghosal, A., Chaudhuri, A., & DasBit, S. (2011). A Probability Density Function for Energy-Balanced Lifetime-Enhancing Node Deployment in WSN. In Proceedings of 11th International Conference on Computational Science and its Application, LNCS, vol. 6018, (pp. 472–487).

  24. Halder, S., Ghosal, A., & DasBit, S. (2011). A pre-determined node deployment strategy to prolong network lifetime in wireless sensor network. Computer Communications, 34(11), 1294–1306.

    Article  Google Scholar 

  25. Marks, M. (2010). A survey of multi-objective deployment in wireless sensor network. Journal of Telecommunication and Information Technology, 3, 36–41.

    Google Scholar 

  26. Lemieux, C. (2009). Quasi- Monte Carlo constructions. In Book Monte Carlo and Quasi-Monte Carlo Sampling, Springer series in Statistics, (pp. 139–197).

Download references

Author information

Authors and Affiliations

  1. Department of Business Development and Technology, Aarhus University, Aarhus, Herning, Denmark

    Nandkumar Kulkarni & Ramjee Prasad

  2. International Technological University (ITU), San Jose, CA, USA

    Neeli Rashmi Prasad

Authors
  1. Nandkumar Kulkarni
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neeli Rashmi Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramjee Prasad
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Nandkumar Kulkarni.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kulkarni, N., Prasad, N.R. & Prasad, R. A Novel Sensor Node Deployment using Low Discrepancy Sequences for WSN. Wireless Pers Commun 100, 241–254 (2018). https://doi.org/10.1007/s11277-017-5063-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-017-5063-9

Keywords

Search

Navigation