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An enhanced energy optimization routing protocol for WSNs

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Abstract

Wireless sensor networks (WSNs) have received increasing attention due to their broad application prospects. However, the nature of sensor nodes, i.e., limited battery life and inefficient protocols, greatly reduces the sensor networks’ lifetime. Therefore, determining how to extend their lifetime has become an important issue for WSNs. This paper focuses on the technique of extending the networks’ lifetime by reducing and balancing energy consumption and proposes an enhanced energy optimization routing protocol (EEORP) for WSNs. EEORP proposes a grid-based cluster head (CH) election algorithm and introduces the energy weight and declaration number order weight factors to reduce the energy consumption in the rotation of CHs. EEORP adopts the dynamic clustering algorithm to reduce the energy consumption in intra-cluster data collection. The hop-count gradient field and grid distance are also introduced in EEORP to minimize the energy consumption in inter-cluster forwarding of the data. Our proposed protocol (EEORP) shows better performance than the existing protocols (LEACH, IEE-LEACH and EAMR) in terms of the networks’ lifetime and data throughput in WSNs, as has been demonstrated experimentally.

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References

  1. Kocakulak M, Butun I (2017) An overview of Wireless Sensor Networks towards internet of things. In: 2017 IEEE 7th annual computing and communication workshop and conference (CCWC). IEEE

  2. Rault T, Bouabdallah A, Challal Y (2014) Energy efficiency in wireless sensor networks: A top-down survey. Comput Netw 67:104–122

    Article  Google Scholar 

  3. Lin Y, Wang XM, Hao F, Wang L, Zhang LC, Zhao RN (2018) An on-demand coverage based self-deployment algorithm for big data perception in mobile sensing networks. Futur Gener Comput Syst 82:220–234

    Article  Google Scholar 

  4. Kaur N, Singh TA (2016) Review of wireless sensor network with its applications. Int J Compute Sci Info Technol 07(01):211–214

    Google Scholar 

  5. Li QY, Liu NZ (2020) Monitoring area coverage optimization algorithm based on nodes perceptual mathematical model in wireless sensor networks. Comput Commun 155:227–234

    Article  Google Scholar 

  6. Poongod T, Rathee A, Indrakumari R, Suresh P (2020) IoT sensing capabilities: sensor deployment and node discovery, wearable sensors, wireless body area network (WBAN), data acquisition. Princ Internet Things (IoT) Ecosyst Insight Paradigm 174:127–151

    Article  Google Scholar 

  7. Zhou GB, Huang LH, Li W, Zhu ZC (2014) Harvesting ambient environmental energy for wireless sensor networks: A survey. J Sensors 2014:1–20

    Google Scholar 

  8. Talat M, Alsayyari AS, Albawi A, Hatata AY (2020) Hybrid-cloud-based data processing for power system monitoring in smart grids. Sustain Cities Soc 55:1–47

    Article  Google Scholar 

  9. Zhan C, Zeng Y, Zhang R (2018) Energy-efficient data collection in UAV enabled wireless sensor network. IEEE Wirel Commun Lett 7(3):328–331

    Article  Google Scholar 

  10. Nguyen T-T, Pan J-S, Dao T-K (2019) An overview of wireless sensor networks towards internet of things. IEEE Access 7:75985–75998

    Article  Google Scholar 

  11. Elhoseny M, Tharwat A, Farouk A, Hassanien AE (2017) K-coverage model based on genetic algorithm to extend WSN lifetime. IEEE Sensors Lett 1(04):1–4

    Article  Google Scholar 

  12. Ma Z, Zhang S, Lu S (2018) Prolonging WSN lifetime with an actual charging model. In: IEEE Wireless communications and networking conference (WCNC). IEEE

  13. Elhoseny M, Hassanien E (2018) Extending homogeneous WSN lifetime in dynamic environments using the clustering mode. Dyn Wirel Sensor Netw 165:73–92

    Google Scholar 

  14. Afsar MM, Tayarani-N M-H (2014) Clustering in sensor networks: A literature survey. J Netw Comput Appl 46:198–226

    Article  Google Scholar 

  15. Heinzelman WR, 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. IEEE, pp 8020–8030

  16. Pino-Povedano S, Arroyo-Valles R, Cid-Sueiro J (2014) Selective forwarding for energy-efficient target tracking in sensor networks. Sig Process 94:557–569

    Article  Google Scholar 

  17. Pant M, Dey B, Nandi S (2015) A multi hop routing protocol for wireless sensor network based on grid clustering 2015. In: Applications and innovations in mobile computing (AIMoC). IEEE, pp 137–140

  18. Yang L, Lu YZ, Zhong YC (2016) A multi-hop energy neutral clustering algorithm for maximizing network information gathering in energy harvesting wireless sensor networks. Sensors 16(01):1–22

    Article  Google Scholar 

  19. Mohapatra H, Rath AK (2019) Fault tolerance in WSN through PE-LEACH protocol. IET Wirel Sensor Syst 9(6):358–365

    Article  Google Scholar 

  20. Cui ZH, Cao Y, Cai XJ, Cai JH, Chen JJ (2019) Optimal LEACH protocol with modified bat algorithm for big data sensing systems in Internet of Things. J Parallel Distrib Comput 132:217–229

    Article  Google Scholar 

  21. Lindsey S, Raghavendra CS (2002) PEGASIS: Power-efficient gathering in sensor information systems. In: Proceedings IEEE aerospace conference. IEEE, pp 1125–1130

  22. Younis O, Fahmy S (2004) HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Trans Mob Comput 03(04):366–379

    Article  Google Scholar 

  23. Ali MS, Dey T, Biswas R (2008) ALEACH: Advanced LEACH routing protocol for wireless microsensor networks. In: 2008 International conference on electrical and computer engineering. IEEE, pp 909–914

  24. Shirmohammadi MM, Faez K, Chhardoli M (2009) LELE: Leader election with load balancing energy in wireless sensor network. In: 2009 WRI International conference on communications and mobile computing. IEEE, pp 106–110

  25. Heinzelman WB, Chandrakasan AP, Balakrishnan H (2002) An application-specific protocol architecture for wireless microsensor networks. IEEE Trans Wirel Commun 01(04):660–670

    Article  Google Scholar 

  26. Popat PL, Trivedi MD (2015) Optimization of cluster head selection technique in LEACH protocol. Int J Comput Appl 05(04):99–103

    Google Scholar 

  27. Cengiz K, Dag T (2017) Energy aware multi-hop routing protocol for WSNs. IEEE Access 06:2622–2633

    Article  Google Scholar 

  28. Liu Y, Wu Q, Zhao T, Tie Y, Bai F, Jin M (2019) An improved energy-efficient routing protocol for wireless sensor networks. Sensors 19:4579–4598

    Article  Google Scholar 

  29. Ruan TW, Chew ZJ, Zhu ML (2018) Energy-aware approaches for energy harvesting powered wireless sensor nodes. IEEE Sensors J 17(7):2165–2173

    Article  Google Scholar 

  30. Sasirekha S, Swamynathan S (2017) Cluster-chain mobile agent routing algorithm for efficient data aggregation in wireless sensor network. J Commun Netw 19(04):392–401

    Article  Google Scholar 

  31. Jha SK, Eyong EM (2018) An energy optimization in wireless sensor networks by using genetic algorithm. Telecommun Syst 67:113–121

    Article  Google Scholar 

  32. Huang CW, Zappone A, Alexandropoulous GC, Debbah M, Yuen C (2019) Reconfigurable intelligent surfaces for energy efficiency in wireless communication. IEEE Trans Wirel Commun 18(8):4157–4170

    Article  Google Scholar 

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Funding

This work was supported in part by the Primary Research and Development Plan of Shandong Province (grant 2019GNC106034) and in part by Weifang University of Science and Technology Doctoral Fund Project (grant 2017BS19).

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Authors and Affiliations

  1. Blockchain Laboratory of Agricultural Vegetables, Weifang University of Science and Technology, Weifang, Shandong, 262700, China

    Xiaojun Ren, Yongtang Wu & Hongwei Sun

  2. School of Mechanical, Electrical, Information Engineering, Shandong University, Weihai, Shandong, 264200, China

    Jiaqing Li

  3. School of Cyberspace, Hangzhou Dianzi University, Hangzhou, Zhejiang, 310018, China

    Yuanfang Chen

  4. Network Infomation Center, Weifang University, Weifang, Shandong, 261021, China

    Zhichen Shi

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  1. Xiaojun Ren
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  2. Jiaqing Li
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  3. Yongtang Wu
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  4. Yuanfang Chen
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  5. Hongwei Sun
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  6. Zhichen Shi
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Correspondence to Zhichen Shi.

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Ren, X., Li, J., Wu, Y. et al. An enhanced energy optimization routing protocol for WSNs. Ann. Telecommun. 76, 343–354 (2021). https://doi.org/10.1007/s12243-021-00838-y

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  • DOI: https://doi.org/10.1007/s12243-021-00838-y

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