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An Energy-Efficient Transmission in WSNs for Different Climatic Conditions

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Abstract

Applications of wireless sensor networks (WSNs) are increasing tremendously to facilitate and establish a link between the physical world and information system. The major issues to design such type of WSNs are to reduce the power consumption of sensor nodes and enhance the life-time of nodes having limited battery capacity. In this paper, an energy-efficient transmission scheme in dynamic climatic conditions in WSNs has been proposed. This scheme is IEEE 802.15.4 standard adaptable. It considers two processes one is with feedback and another is without feedback. Process without feedback is used to evaluate and compensate the link quality due to effects of different climatic conditions such as temperature, rain, and snow (dry and wet), albeit process with feedback is used to divide the network into two logical regions to decrease the overhead of control packets. The current number of nodes \([n_c(t)]\) and power loss in each region are used to adjust the transmit power level \((P_{level})\) of node according to variations in link quality and climatic conditions. Simulation results show that proposed scheme adjusts transmission \(P_{level}\) to compensate link quality with less packets overhead resulting less energy consumption.

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References

  1. Akila, I., & Venkatesan, R. (2016). A cognitive multi-hop clustering approach for wireless sensor networks. Wireless Personal Communications, 90(2), 729–747.

    Article  Google Scholar 

  2. Bannister, K., Giorgetti, G., & Gupta, S. K. (2008). Wireless sensor networking for hot applications: Effects of temperature on signal strength, data collection and localization. In Proceedings of the 5th workshop on embedded networked sensors (HotEmNets’ 08).

  3. Barabino, N., & Rodríguez, B. (2013). Performance evaluation of FSO and MMW for the uruguayan weather conditions. Wireless Personal Communications, 73(3), 1077–1088.

    Article  Google Scholar 

  4. Baradaran, A. A., & Navi, K. (2017). CAST-WSN: The presentation of new clustering algorithm based on steiner tree and C-means algorithm improvement in wireless sensor networks. Wireless Personal Communications, 97(1), 1323–1344.

    Article  Google Scholar 

  5. Dehghani, S., Pourzaferani, M., & Barekatain, B. (2015). Comparison on energy-efficient cluster based routing algorithms in wireless sensor network. Procedia Computer Science, 72, 535–542.

    Article  Google Scholar 

  6. Fiser, O., Brazda, V., & Wilfert, O. (2015). Different atmospheric effects causing fso link attenuation: Experimental results and modelling in Czech Republic. SPIE Optical Engineering+Applications (pp. 96140D–96140D).

  7. Grabner, M., & Kvicera, V. (2014). Multiple scattering in rain and fog on free-space optical links. Journal of Lightwave Technology, 32(3), 513–520.

    Article  Google Scholar 

  8. Haseeb, K., Bakar, K. A., Ahmed, A., Darwish, T., & Ahmed, I. (2017). WECRR: Weighted energy-efficient clustering with robust routing for wireless sensor networks. Wireless Personal Communications, 97(1), 695–721.

    Article  Google Scholar 

  9. Kaswan, A., Nitesh, K., & Jana, P. K. (2017). Energy efficient path selection for mobile sink and data gathering in wireless sensor networks. AEU-International Journal of Electronics and Communications, 73, 110–118.

    Article  Google Scholar 

  10. Kim, D. Y., Jin, Z., Choi, J., Lee, B., & Cho, J. (2015). Transmission power control with the guaranteed communication reliability in WSN. International Journal of Distributed Sensor Networks, 11(10), 632590.

    Google Scholar 

  11. Kumar, P., & Chaturvedi, A. (2015). Sink attributes analysis for energy efficient operations of wireless sensor networks under randomly varying temporal and spatial aspects of query generation. AEU-International Journal of Electronics and Communications, 69(7), 1058–1069.

    Article  Google Scholar 

  12. Lin, S., Miao, F., Zhang, J., Zhou, G., Gu, L., He, T., et al. (2006). ATPC: Adaptive transmission power control for wireless sensor networks. In Proceedings of the 4th international conference on embedded networked sensor systems (SenSys ’06) (pp. 223–236).

  13. Lin, S., Miao, F., Zhang, J., Zhou, G., Gu, L., He, T., et al. (2016). ATPC: Adaptive transmission power control for wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 12(1), 6.

    Article  Google Scholar 

  14. Markham, A., Trigoni, N., & Ellwood, S. (2010) Effect of rainfall on link quality in an outdoor forest deployment. In Proceedings of the 2010 international conference on wireless information networks and systems (WINSYS) (pp. 1–6). IEEE

  15. Meng, W., Gong, S., & Yang, J. (2012) Influence of multiple scattering on rain attenuation. In 2012 10th international symposium on antennas, propagation & EM theory (ISAPE) (pp. 616–619). IEEE

  16. Prasad, D. R., Naganjaneyulu, P. V., & Prasad, K. S. (2016). Energy efficient clustering in multi-hop wireless sensor networks using differential evolutionary MOPSO. Brazilian Archives of Biology and Technology. https://doi.org/10.1590/1678-4324-2016161011.

    Article  Google Scholar 

  17. Sabet, M., & Naji, H. R. (2015). A decentralized energy efficient hierarchical cluster-based routing algorithm for wireless sensor networks. AEU-International Journal of Electronics and Communications, 69(5), 790–799.

    Article  Google Scholar 

  18. Singhal, P., Gupta, P., & Rana, P. (2015). Basic concept of free space optics communication (FSO): An overview. In 2015 International conference on communications and signal processing (ICCSP) (pp. 0439–0442). IEEE

  19. Sivaraj, C., Alphonse, P., & Janakiraman, T. (2017). Independent neighbour set based clustering algorithm for routing in wireless sensor networks. Wireless Personal Communications, 96(4), 6197–6219.

    Article  Google Scholar 

  20. Tahir, M., Javaid, N., Iqbal, A., Khan, Z. A., & Alrajeh, N. (2013). On adaptive energy-efficient transmission in WSNS. International Journal of Distributed Sensor Networks, 9(5), 923714.

    Article  Google Scholar 

  21. Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks, 52(12), 2292–2330.

    Article  Google Scholar 

  22. Zhang, R. B., Guo, J. G., Chu, F. H., & Zhang, Y. C. (2011). Environmental-adaptive indoor radio path loss model for wireless sensor networks localization. AEU-international Journal of Electronics and Communications, 65(12), 1023–1031.

    Article  Google Scholar 

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Authors and Affiliations

  1. Motilal Nehru National Institute of Technology, Allahabad, 211004, India

    Sunil Kumar, Prateek Raj Gautam, Akshay Verma, Tarique Rashid & Arvind Kumar

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  1. Sunil Kumar
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  2. Prateek Raj Gautam
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  3. Akshay Verma
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  4. Tarique Rashid
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  5. Arvind Kumar
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Correspondence to Sunil Kumar.

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Kumar, S., Gautam, P.R., Verma, A. et al. An Energy-Efficient Transmission in WSNs for Different Climatic Conditions. Wireless Pers Commun 110, 423–444 (2020). https://doi.org/10.1007/s11277-019-06735-x

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  • DOI: https://doi.org/10.1007/s11277-019-06735-x

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