Skip to main content

Advertisement

Log in

Compatibility Analysis of Cluster-Based WSN Framework for IoT Applications

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

With the enormous potential of internet of things (IoT), many applications are developed for daily life. Availability of tiny sensors for all kind of physical stimulus with wireless communication, enabled wireless sensor network (WSN) to fulfill the development of IoT systems. Challenges of energy constraints and lower processing capabilities of WSN is the limitations for IoT. A proper design of WSN with energy efficient data routing algorithms is the aim of this paper. Alternative to the battery replacement of nodes with advanced node is explored for the heterogeneity aspect of IoT. Hierarchical clustering is taken as efficient mechanism for WSN. Although, cluster heads (CHs) has to perform data collection and communication with the sink node, which needs efficient selection to balance energy requirement. Air quality monitoring IoT system is considered for the framework. The network of immobile sensors with unstable wireless environments are taken for the simulation. The analysis of clustering algorithm shows network lifetime enhancement and better heterogeneous stability.

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.

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

Similar content being viewed by others

Data Availability

All data and materials are available to the author.

Code availability

All codes are available to the author.

References

  1. Davis, G. (2018). 2020: Life with 50 billion connected devices. In 2018 IEEE international conference on consumer electronics (ICCE), 12–14 Jan. 2018 (pp. 1–1). https://doi.org/10.1109/ICCE.2018.8326056.

  2. Borges, L. M., Velez, F. J., & Lebres, A. S. (2014). Survey on the characterization and classification of wireless sensor network applications. IEEE Communications Surveys & Tutorials, 16(4), 1860–1890. https://doi.org/10.1109/COMST.2014.2320073

    Article  Google Scholar 

  3. Deif, D., & Gadallah, Y. (2017). A comprehensive wireless sensor network reliability metric for critical Internet of Things applications. EURASIP Journal on Wireless Communications and Networking, 2017(1), 145. https://doi.org/10.1186/s13638-017-0930-3

    Article  Google Scholar 

  4. Samie, F., Bauer, L., & Henkel, J. (2020). Hierarchical classification for constrained IoT devices: A case study on human activity recognition. IEEE Internet of Things Journal, 7(9), 8287–8295. https://doi.org/10.1109/JIOT.2020.2989053

    Article  Google Scholar 

  5. Swamy, S. N., & Kota, S. R. (2020). An empirical study on system level aspects of Internet of Things (IoT). IEEE Access, 8, 188082–188134. https://doi.org/10.1109/ACCESS.2020.3029847

    Article  Google Scholar 

  6. Yosuf, B. A., Musa, M., Elgorashi, T., & Elmirghani, J. (2020). Energy efficient distributed processing for IoT. IEEE Access, 8, 161080–161108. https://doi.org/10.1109/ACCESS.2020.3020744

    Article  Google Scholar 

  7. Sobin, C. C. (2020). A survey on architecture, protocols and challenges in IoT. Wireless Personal Communications, 112(3), 1383–1429. https://doi.org/10.1007/s11277-020-07108-5

    Article  Google Scholar 

  8. Liu, X. (2015). Atypical hierarchical routing protocols for wireless sensor networks: A review. IEEE Sensors Journal, 15(10), 5372–5383. https://doi.org/10.1109/jsen.2015.2445796

    Article  Google Scholar 

  9. Sasirekha, S., & Swamynathan, S. (2017). Cluster-chain mobile agent routing algorithm for efficient data aggregation in wireless sensor network. Journal Of Communications And Networks, 19(4), 391–401.

    Article  Google Scholar 

  10. Morell, A., Correa, A., Barceló, M., & Vicario, J. L. (2016). Data aggregation and principal component analysis in WSNs. IEEE Transactions on Wireless Communications, 15(6), 3908–3919. https://doi.org/10.1109/TWC.2016.2531041

    Article  Google Scholar 

  11. Siva Ranjani, S., Radha Krishnan, S., Thangaraj, C., & Vimala Devi, K. (2013). Achieving energy conservation by cluster based data aggregation in wireless sensor networks. Wireless Personal Communications, 73(3), 731–751. https://doi.org/10.1007/s11277-013-1213-x

    Article  Google Scholar 

  12. Zhang, Z., Ma, M., & Yang, Y. (2008). Energy-efficient multihop polling in clusters of two-layered heterogeneous sensor networks. IEEE Transactions on Computers, 57(2), 231–245. https://doi.org/10.1109/TC.2007.70774

    Article  MathSciNet  MATH  Google Scholar 

  13. Al Aghbari, Z., Khedr, A. M., Osamy, W., Arif, I., & Agrawal, D. P. (2020). Routing in wireless sensor networks using optimization techniques: A survey. Wireless Personal Communications, 111(4), 2407–2434. https://doi.org/10.1007/s11277-019-06993-9

    Article  Google Scholar 

  14. Hamidouche, R., Aliouat, Z., Ari, A. A. A., & Gueroui, M. (2019). An efficient clustering strategy avoiding buffer overflow in IoT sensors: A bio-inspired based approach. IEEE Access, 7, 156733–156751. https://doi.org/10.1109/ACCESS.2019.2943546

    Article  Google Scholar 

  15. Xu, L., Collier, R., & O’Hare, G. M. P. (2017). A survey of clustering techniques in WSNs and consideration of the challenges of applying such to 5G IoT scenarios. IEEE Internet of Things Journal, 4(5), 1229–1249. https://doi.org/10.1109/JIOT.2017.2726014

    Article  Google Scholar 

  16. Balaji, S., Nathani, K., & Santhakumar, R. (2019). IoT technology, applications and challenges: A contemporary survey. Wireless Personal Communications, 108(1), 363–388. https://doi.org/10.1007/s11277-019-06407-w

    Article  Google Scholar 

  17. Asif, M., Khan, S., Ahmad, R., Sohail, M., & Singh, D. (2017). Quality of service of routing protocols in wireless sensor networks: A review. IEEE Access, 5, 1846–1871. https://doi.org/10.1109/ACCESS.2017.2654356

    Article  Google Scholar 

  18. Wang, F., & Liu, J. (2011). Networked wireless sensor data collection: Issues, challenges, and approaches. IEEE Communications Surveys & Tutorials, 13(4), 673–687. https://doi.org/10.1109/SURV.2011.060710.00066

    Article  Google Scholar 

  19. Hammoudeh, M., Al-Fayez, F., Lloyd, H., Newman, R., Adebisi, B., Bounceur, A., & Abuarqoub, A. (2017). A wireless sensor network border monitoring system: Deployment issues and routing protocols. IEEE Sensors Journal, 17(8), 2572–2582. https://doi.org/10.1109/JSEN.2017.2672501

    Article  Google Scholar 

  20. Bazzi, H. S., Haidar, A. M., & Bilal, A. (2015). Classification of routing protocols in wireless sensor network. In International conference on computer vision and image analysis applications, 18–20 Jan. 2015 (pp. 1–5). https://doi.org/10.1109/ICCVIA.2015.7351790.

  21. Lin, H., & Üster, H. (2014). Exact and heuristic algorithms for data-gathering cluster-based wireless sensor network design problem. IEEE/ACM Transactions on Networking, 22(3), 903–916. https://doi.org/10.1109/TNET.2013.2262153

    Article  Google Scholar 

  22. Rhazi, A. E., & Pierre, S. (2009). A Tabu search algorithm for cluster building in wireless sensor networks. IEEE Transactions on Mobile Computing, 8(4), 433–444. https://doi.org/10.1109/TMC.2008.125

    Article  Google Scholar 

  23. Asaduzzaman, & Kong, H. Y. (2010). Energy efficient cooperative LEACH protocol for wireless sensor networks. Journal of Communications and Networks, 12(4), 358–365.https://doi.org/10.1109/JCN.2010.6388472

  24. 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, 7–7 Jan. 2000 (Vol. 12, p. 10). https://doi.org/10.1109/HICSS.2000.926982.

  25. Yassein, M. B., & Hijazi, N. (2010) Improvement on Cluster based routing protocol by using vice cluster head. In 2010 Fourth international conference on next generation mobile applications, services and technologies, 27–29 July 2010 (pp. 137–141). https://doi.org/10.1109/NGMAST.2010.36.

  26. 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. https://doi.org/10.1109/TWC.2002.804190

    Article  Google Scholar 

  27. Xiangning, F., & Yulin, S. (2007). Improvement on LEACH protocol of wireless sensor network. In 2007 International conference on sensor technologies and applications (SENSORCOMM 2007), 14–20 Oct. 2007 (pp. 260–264). https://doi.org/10.1109/SENSORCOMM.2007.4394931.

  28. Hu, J., Jin, Y., & Dou, L. (2008). A time-based cluster-head selection algorithm for LEACH. In 2008 IEEE symposium on computers and communications, 6–9 July 2008 (pp. 1172–1176). https://doi.org/10.1109/ISCC.2008.4625714.

  29. Gautam, N., & Pyun, J. (2010). Distance aware intelligent clustering protocol for wireless sensor networks. Journal of Communications and Networks, 12(2), 122–129. https://doi.org/10.1109/JCN.2010.6391368

    Article  Google Scholar 

  30. Ihsan, A., Saghar, K., Fatima, T., & Hasan, O. (2019). Formal comparison of LEACH and its extensions. Computer Standards & Interfaces, 62, 119–127. https://doi.org/10.1016/j.csi.2018.10.001

    Article  Google Scholar 

  31. Smaragdakis, G., Matta, I., & Bestavros, A. (2004). SEP: A stable election protocol for clustered heterogeneous wireless sensor networks. In Second international workshop on sensor and actor network protocols and applications (SANPA 2004).

  32. Khalil, E. A., & Attea, B. A. (2011). Energy-aware evolutionary routing protocol for dynamic clustering of wireless sensor networks. Swarm and Evolutionary Computation, 1(4), 195–203. https://doi.org/10.1016/j.swevo.2011.06.004

    Article  Google Scholar 

  33. Khediri, S. E., Nasri, N., Khan, R. U., & Kachouri, A. (2021). An improved energy efficient clustering protocol for increasing the life time of wireless sensor networks. Wireless Personal Communications, 116(1), 539–558. https://doi.org/10.1007/s11277-020-07727-y

    Article  Google Scholar 

  34. Manap, Z., Ali, B. M., Ng, C. K., Noordin, N. K., & Sali, A. (2013). A review on hierarchical routing protocols for wireless sensor networks. Wireless Personal Communications, 72(2), 1077–1104. https://doi.org/10.1007/s11277-013-1056-5

    Article  Google Scholar 

  35. Mansour, S., Nasser, N., Karim, L., & Ali, A. (2014). Wireless sensor network-based air quality monitoring system. In 2014 International conference on computing, networking and communications (ICNC), 3–6 Feb. 2014 (pp. 545–550). https://doi.org/10.1109/ICCNC.2014.6785394.

  36. Imran, L. B., Latif, R. M. A., Farhan, M., & Aldabbas, H. (2020). Smart city based autonomous water quality monitoring system using WSN. Wireless Personal Communications, 115(2), 1805–1820. https://doi.org/10.1007/s11277-020-07655-x

    Article  Google Scholar 

  37. Baoqiang, K., Li, C., Hongsong, Z., & Yongjun, X. (2008). Accurate energy model for WSN node and its optimal design. Journal of Systems Engineering and Electronics, 19(3), 427–433. https://doi.org/10.1016/S1004-4132(08)60102-4

    Article  Google Scholar 

  38. Abo-Zahhad, M., Ahmed, S. M., Sabor, N., & Sasaki, S. (2015). Mobile sink-based adaptive immune energy-efficient clustering protocol for improving the lifetime and stability period of wireless sensor networks. IEEE Sensors Journal, 15(8), 4576–4586. https://doi.org/10.1109/JSEN.2015.2424296

    Article  Google Scholar 

Download references

Funding

No funding is provided for this research.

Author information

Authors and Affiliations

Authors

Contributions

Both authors performed the primary literature review, data collection, experiments, and approved the final manuscript. Mridul Chawla supervised the research and Sarvesh Kumar Sharma drafted the final manuscript.

Corresponding author

Correspondence to Sarvesh Kumar Sharma.

Ethics declarations

Conflict of interest

Sarvesh Kumar Sharma and Mridul Chawla declares that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Consent to participate

The authors affirm consent for participation.

Consent for publication

The authors affirm that research article with figures provided are informed consent for publication.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Sharma, S.K., Chawla, M. Compatibility Analysis of Cluster-Based WSN Framework for IoT Applications. Wireless Pers Commun 131, 1365–1380 (2023). https://doi.org/10.1007/s11277-023-10486-1

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-023-10486-1

Keywords

Navigation