Cover
Vol. 17 No. 1 (2021)

Published: June 30, 2021

Pages: 94-99

Original Article

Increasing WSN Lifetime using Clustering and Fault Tolerance Methods

Sama Hussam Sabah 1 Muayad Sadik Croock
1Computer Engineering Department, University of Technology, Baghdad, Iraq
History
  • Received: March 12, 2021
  • Revised: April 24, 2021
  • Accepted: April 25, 2021
  • Available Online: April 28, 2021
DOI

https://doi.org/10.37917/ijeee.17.1.11

Abstract

Energy consumption problems in wireless sensor networks are an essential aspect of our days where advances have been made in the sizes of sensors and batteries, which are almost very small to be placed in the patient's body for remote monitoring. These sensors have inadequate resources, such as battery power that is difficult to replace or recharge. Therefore, researchers should be concerned with the area of saving and controlling the quantities of energy consumption by these sensors efficiently to keep it as long as possible and increase its lifetime. In this paper energy-efficient and fault-tolerance strategy is proposed by adopting the fault tolerance technique by using the self-checking process and sleep scheduling mechanism for avoiding the faults that may cause an increase in power consumption as well as energy-efficient at the whole network. this is done by improving the LEACH protocol by adding these proposed strategies to it. Simulation results show that the recommended method has higher efficiency than the LEACH protocol in power consumption also can prolong the network lifetime. In addition, it can detect and recover potential errors that consume high energy.

Keywords

References

  1. S. A. Shaikh, M. Ali, R. Ali, S. H. Memon, and N. K. Pathan, “Design of Solar Tracking System Using Piezoelectric Effect for Multi - Power Generation Based on IoT”, Iraqi Journal for Electrical and Electronic Engineering, vol. 03, no. 02, pp. 30–33, 2020.
  2. E. Technology, F. Komal, T. Khanam, and Z. Ahmed, “Wireless Power Transfer for Battery Charging of Electrical Vehicles”, Iraqi Journal for Electrical and Electronic Engineering, vol. 01, no. 01, pp. 19–23, 2018.
  3. S. Savitha, S. C. Lingareddy, and S. Chitnis, “Energy efficient clustering and routing optimization model for maximizing lifetime of wireless sensor network,” Int. J. Electr. Comput. Eng., vol. 10, no. 5, pp. 4798–4808, 2020, doi: 10.11591/ijece.v10i5.pp4798-4808.
  4. S. A. Mohammed, K. A. E. Aly, and A. M. Ghuniem, “An enhancement process for reducing energy consumption in wireless sensor network,” Int. J. Emerg. Trends Eng. Res., vol. 8, no. 6, pp. 2765–2769, 2020, doi: 10.30534/ijeter/2020/89862020. Sabah & Croock | 99
  5. V. Saranya, S. Shankar, and G. R. Kanagachidambaresan, “Energy Efficient Data Collection Algorithm for Mobile Wireless Sensor Network,” Wirel. Pers. Commun., vol. 105, no. 1, pp. 219–232, 2019, doi: 10.1007/s11277-018- 6109-3.
  6. A. Ahmad, N. Javaid, Z. A. Khan, U. Qasim, and T. A. Alghamdi, “(ACH)2: Routing scheme to maximize lifetime and throughput of wireless sensor networks,” IEEE Sens. J., vol. 14, no. 10, pp. 3516–3532, 2014, doi: 10.1109/JSEN.2014.2328613.
  7. D. W. Sambo, B. O. Yenke, A. Förster, and P. Dayang, “Optimized clustering algorithms for large wireless sensor networks: A review,” Sensors (Switzerland), vol. 19, no. 2, 2019, doi: 10.3390/s19020322.
  8. V. Sharma, P. Rajpoot, A. Gupta, K. Dubey, N. Pandey, and N. Verma, “Heterogeneous clustering for energy optimization in wireless sensor networks,” Proc. 9th Int. Conf. Cloud Comput. Data Sci. Eng. Conflu. 2019, pp. 92–99, 2019, doi: 10.1109/CONFLUENCE.2019.8776933.
  9. Q. Bian, Y. Zhang, and Y. Zhao, “Research on clustering routing algorithms in wireless sensor networks,” 2010 Int. Conf. Intell. Comput. Technol. Autom. ICICTA 2010, vol. 2, pp. 1110–1113, 2010, doi: 10.1109/ICICTA.2010.343.
  10. T. M. Behera, S. K. Mohapatra, U. C. Samal, M. S. Khan, M. Daneshmand, and A. H. Gandomi, “Residual energy-based cluster-head selection in WSNs for IoT application,” IEEE Internet Things J., vol. 6, no. 3, pp. 5132–5139, 2019, doi: 10.1109/JIOT.2019.2897119.
  11. D. S. Park, “Fault tolerance and energy consumption scheme of a wireless sensor network,” Int. J. Distrib. Sens. Networks, vol. 2013, no. March, 2013, doi: 10.1155/2013/396850.
  12. Z. Zhang, A. Mehmood, L. Shu, Z. Huo, Y. Zhang, and M. Mukherjee, “A survey on fault diagnosis in wireless sensor networks,” IEEE Access, vol. 6, pp. 11349–11364, 2018, doi: 10.1109/ACCESS.2018.2794519.
  13. P. H. and B. S. B. Karunakara Rai, J. P. Harshitha, Radhika S. Kalagudi, B. S. Priyanka Chowdary, and Texture Features of Chest X-Rays, no. January. Springer Singapore, 2019.
  14. K. Arulmozhi, V. R. S. Dhulipala, and R. Prabakaran, “A study on optimized power consumption routing in Wireless Sensor Networks,” ICECT 2011 - 2011 3rd Int. Conf. Electron. Comput. Technol., vol. 3, pp. 271–274, 2011, doi: 10.1109/ICECTECH.2011.5941752.
  15. M. Abo-Zahhad, M. Farrag, A. Ali, and O. Amin, “An energy consumption model for wireless sensor networks,” 5th Int. Conf. Energy Aware Comput. Syst. Appl. ICEAC 2015, 2015, doi: 10.1109/ICEAC.2015.7352200.
  16. P. C. Srinivasa Rao and H. Banka, “Energy efficient clustering algorithms for wireless sensor networks: novel chemical reaction optimization approach,” Wirel. Networks, vol. 23, no. 2, pp. 433–452, 2017, doi: 10.1007/s11276-015-1156-0.
  17. M. R. Mundada, N. Thimmegowda, T. Bhuvaneswari, and V. Cyrilraj, “Clustering in wireless sensor networks: Performance comparison of EAMMH and LEACH protocols using MATLAB,” Adv. Mater. Res., vol. 705, pp. 337–342, 2013, doi: 10.4028/www.scientific.net/AMR.705.337.
  18. S. Devi, I. Ahmed, M. Urvashi, and P. G. Student, “Optimization Technique to Improve the Energy Efficiency in WSN : LEACH-MGWO,” no. 5, pp. 176– 182, 2018.
  19. Z. Arabi and R. Parikhani, “E FP : NEW E NERGY – EFFICIENT F AULT - TOLERANT,” vol. 4, no. 6, pp. 111–119, 2012.
  20. S. Jafarali Jassbi and E. Moridi, “Fault Tolerance and Energy Efficient Clustering Algorithm in Wireless Sensor Networks: FTEC,” Wirel. Pers. Commun., vol. 107, no. 1, pp. 373–391, 2019, doi: 10.1007/s11277-019- 06281-6.
  21. A. Choudhary, S. Choudhary, and A. Mishra, “Review on Fault Tolerance in Wireless Sensor Network,” Int. J. Comput. Appl., vol. 182, no. 45, pp. 22–25, 2019, doi: 10.5120/ijca2019918597.
  22. C. H. Lin, H. Y. Lin, and W. Bin Lee, “Routing protocols with power saving and data salvation for wireless sensor networks,” Proc. - 2012 7th Int. Conf. Broadband, Wirel. Comput. Commun. Appl. BWCCA 2012, pp. 468–471, 2012, doi: 10.1109/BWCCA.2012.83.
  23. D. Goyal and Sonal, “Power management in Wireless Sensor Network,” Proc. 10th INDIACom; 2016 3rd Int. Conf. Comput. Sustain. Glob. Dev. INDIACom 2016, vol. 4, no. 4, pp. 598–601, 2016.
  24. K. M. Krishnapriya, S. Anand, and S. Sinha, “A customised approach for reducing energy consumption in wireless sensor network,” Int. J. Innov. Technol. Explor. Eng., vol. 8, no. 8, pp. 1427–1431, 2019.
  25. A. O. Abu Salem and N. Shudifat, “Enhanced LEACH protocol for increasing a lifetime of WSNs,” Pers. Ubiquitous Comput., vol. 23, no. 5–6, pp. 901–907, 2019, doi: 10.1007/s00779-019-01205-4.