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Energy Optimization in Multi-Hop Wireless Sensor Networks based on Proposed Harmony Search Routing Algorithm

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Abstract

Spread application of wireless sensor networks (WSNs), has led many researchers aiming at energy optimization in these networks. The Proposed Energy Efficient Harmony Search Routing Algorithm (PEEHSRA) in accordance with a novel energy model is stated in this study to minimize the amount of energy consumption in WSNs. We first proposed an energy model on the basis of modulation scheme parameters for multi-hop transmission. Then, in order to develop a harmony search routing algorithm, pitch adjustment rate in the harmony memory was introduced based on both, the proposed energy model, and the node’s distance. Also, an energy-efficient fitness function was determined, which results in the most energy-efficient route for the network. At the end, four modulations including MQAM, MQPSK, OQPSK and MFSK were applied and the most energy-efficient one with corresponding parameters was specified. By comparing the results of the proposed method to the state-of-the-art studies, the improvements in extending the lifetime of the network was proved. These findings seem quite useful in designing an energy-efficient multi-hop WSN and pave the way for enhancement of the widespread applications in these networks.

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References

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

    Article  Google Scholar 

  2. Deng, J. (2009). Multihop/direct forwarding (MDF) for static wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 5(4), 1–25.

    Article  Google Scholar 

  3. Rahman, M. N., & Matin, M. A. (2011). Efficient algorithm for prolonging network lifetime of wireless sensor networks. Tsinghua Science and Technology, 16(6), 561–568.

    Article  Google Scholar 

  4. Yaacoub, E., Abu-Dayya, A., & Matin, M. A. (2012). Multihop routing for energy efficiency in wireless sensor networks. In Wireless sensor networks-technology and protocols (pp. 165–186). InTech Press.‏

  5. Sendra Compte, S., Lloret, J., García Pineda, M., & Toledo Alarcón, J. F. (2011). Power saving and energy optimization techniques for wireless sensor networks. Journal of Communications, 6(6), 439–459.

    Google Scholar 

  6. Sharma, A., Shinghal, K., Srivastava, N., & Singh, R. (2011). Energy management for wireless sensor network nodes. International Journal of Advances in Engineering & Technology, 1(1), 7.

    Article  Google Scholar 

  7. Cui, S., Goldsmith, A. J., & Bahai, A. (2005). Energy-constrained modulation optimization. IEEE Transactions on Wireless Communications, 4(5), 2349–2360.

    Article  Google Scholar 

  8. Abouei, J., Plataniotis, K. N., & Pasupathy, S. (2011). Green modulations in energy-constrained wireless sensor networks. IET communications, 5(2), 240–251.

    Article  MathSciNet  Google Scholar 

  9. Holland, M., Wang, T., Tavli, B., Seyedi, A., & Heinzelman, W. (2011). Optimizing physical-layer parameters for wireless sensor networks. ACM Transactions on Sensor Networks (TOSN), 7(4), 1–20.

    Article  Google Scholar 

  10. Wang, J., Cho, J., & Lee, S. (2008). Experimental study of energy consumption in direct transmission and multi-hop transmission for wireless sensor networks. In 2008 IEEE international conference on networking, sensing and control (pp. 1179–1184). IEEE.‏

  11. Zardosht, M. J., & Almodarresi, S. M. T. (2012). Energy optimization in multi-hop wireless sensor networks. In 6th International symposium on telecommunications (IST) (pp. 450–454). IEEE.‏

  12. Rahimkhani, K., & Forouzesh, F. (2017). Improved routing in wireless sensor networks using harmony search algorithm. Wireless Sensor Network, 9(9), 333–353.

    Article  Google Scholar 

  13. Zeng, B., & Dong, Y. (2016). An improved harmony search based energy-efficient routing algorithm for wireless sensor networks. Applied Soft Computing, 41, 135–147.

    Article  Google Scholar 

  14. Anand, V., & Pandey, S. (2017). Particle swarm optimization and harmony search based clustering and routing in wireless sensor networks. International Journal of Computational Intelligence Systems, 10(1), 1252–1262.

    Article  Google Scholar 

  15. Zeng, B., Dong, Y., Li, X., & Gao, L. (2017). IHSCR: Energy-efficient clustering and routing for wireless sensor networks based on harmony search algorithm. International Journal of Distributed Sensor Networks, 13(11), 1550147717741103.

    Article  Google Scholar 

  16. Poonguzhali, P. K., & Ananthamoorthy, N. P. (2020). Design of mutated harmony search algorithm for data dissemination in wireless sensor network. Wireless Personal Communications, 111(2), 729–751.

    Article  Google Scholar 

  17. Zhu, Q., Tang, X., Li, Y., & Yeboah, M. O. (2020). An improved differential-based harmony search algorithm with linear dynamic domain. Knowledge-Based Systems, 187, 104809.

    Article  Google Scholar 

  18. Shiva, C. K., & Kumar, R. (2020). Quasi-oppositional harmony search algorithm approach for ad hoc and sensor networks. In Nature inspired computing for wireless sensor networks (pp. 175–194). Springer, Singapore.‏

  19. Manjarres, D., Del Ser, J., Gil-Lopez, S., Vecchio, M., Landa-Torres, I., & Lopez-Valcarce, R. (2011). On the application of a hybrid harmony search algorithm to node localization in anchor-based wireless sensor networks. In 2011 11th International conference on intelligent systems design and applications (pp. 1014–1019). IEEE.‏

  20. Zeng, B., & Dong, Y. (2014). An energy efficient harmony search based routing algorithm for small-scale wireless sensor networks. In 2014 IEEE 17th international conference on computational science and engineering (pp. 362–367). IEEE.‏

  21. Mahdavi, M., Fesanghary, M., & Damangir, E. (2007). An improved harmony search algorithm for solving optimization problems. Applied Mathematics and Computation, 188(2), 1567–1579.

    Article  MathSciNet  Google Scholar 

  22. Karl, H., & Willig, A. (2007). Protocols and architectures for wireless sensor networks. New York: Wiley.

    Google Scholar 

  23. Abouei, J., Plataniotis, K. N., & Pasupathy, S. (2010). Green modulation in dense wireless sensor networks. In 2010 IEEE international conference on acoustics, speech and signal processing (pp. 3382–3385). IEEE.‏

  24. Tang, Q., Yang, L., Giannakis, G. B., & Qin, T. (2007). Battery power efficiency of PPM and FSK in wireless sensor networks. IEEE Transactions on Wireless Communications, 6(4), 1308–1319.

    Article  Google Scholar 

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Correspondence to Mohammad Javad Zardosht.

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Zardosht, M.J., Parhizgar, N. Energy Optimization in Multi-Hop Wireless Sensor Networks based on Proposed Harmony Search Routing Algorithm. Wireless Pers Commun 118, 2717–2731 (2021). https://doi.org/10.1007/s11277-021-08151-6

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