Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption
Keywords:
farmland, wireless sensor networks, multi-path fading channel, routing protocol, energy optimizationAbstract
Wireless sensor network (WSN) can achieve real-time data collection and transmission of environment, soil, meteorology, crop physiology and other information in agriculture. The data provided by WSN could be used for decision making and management, which is very important in precision agriculture. Wheat farmland wireless sensor network has the characteristics of wide coverage area, long planting period, inconvenient energy supply, and serious impact of crop environment on wireless signal transmission. Routing protocol is an important method to achieve long-term WSN monitoring by selecting an appropriate path with low energy consumption for data transmission. According to the phenomenon of uneven environment and channel parameters caused by intensive crop growth in farmland, a non-uniform clustering routing protocol based on effective energy consumption (UCEEC) was proposed in this work. The method combined with the characteristics of multi-path fading of farmland environment signals. The idea of image segmentation was introduced. Nodes with high similarity were divided into a cluster area by the dissimilarity between nodes in order to improve the intracluster communication performance. Meanwhile, a multi-hop path selection method between cluster-heads based on the estimation of two-hop effective energy consumption is designed. The energy consumption cost factor is calculated by the effective energy consumption and the average energy consumption within the cluster to achieve the minimum and balance of the overall energy consumption of the network. Simulation results show that, compared with the existing Maximum Residual Energy Based Routing (MREBR) protocol, minimum Energy Consumption Based Routing (MEC) routing protocols, UCEEC improves the energy balance effect between nodes, prolongs the network life cycle, and realizes efficient energy utilization of wireless sensor network data collection in the complex environment of wheat field. Keywords: farmland, wireless sensor networks, multi-path fading channel, routing protocol, energy optimization DOI: 10.25165/j.ijabe.20211403.6540 Citation: Miao Y S, Zhao C J, Wu H R. Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption. Int J Agric & Biol Eng, 2021; 14(3): 163–170.References
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[2] Padilla-Medina J A, Contreras-Medina L M, Gavilan M U, Millan-Almaraz J R, Alvaro J E. Sensors in precision agriculture for the monitoring of plant development and improvement of food production. Journal of Sensors, 2019; 2019: 7138720. doi: 10.1155/2019/7138720.
[3] Fathallah K, Abid M A, Hadjalouane N B. Enhancing energy saving in smart farming through aggregation and partition aware IoT routing protocol. Sensors, 2020; 20(10): 2760. doi: 10.3390/s20102760.
[4] Thakur D, Kumar Y, Kumar A, Singh P K. Applicability of wireless sensor networks in precision agriculture: A review. Wireless Personal Communications, 2019; 107(1): 471–512.
[5] Miao Y S, Wu H R, Li F F, Zhu L. Study of wheat farmland multipath fading channel modeling based on statistical distribution. Acta Electronica Sinica, 2016; 44(3): 665–672. (in Chinese)
[6] Goldsmith A. Wireless communications. Oxford City: Cambridge University Press, 2005; pp. 36–46.
[7] Vougioukas S, Anastassiu H T, Regen C, Zude M. Influence of foliage on radio path losses (PLs) for wireless sensor network (WSN) planning in orchards. Biosystems Engineering. 2013; 114(4): 454–465.
[8] Wang L N, Wang B R. Greenhouse microclimate environment adaptive control based on a wireless sensor network. Int J Agric & Biol Eng, 2020; 13(3): 64–69.
[9] Guo X M, Yang X T, Chen M X, Li M, Wang Y A. A model with leaf area index and apple size parameters for 2.4 GHz radio propagation in apple orchards. Precision Agriculture, 2015; 16(2): 180–200.
[10] Chandrawanshi V S, Tripathi R K, Pachauri R. An intelligent low power consumption routing protocol to extend the lifetime of wireless sensor networks based on fuzzy C-means++ clustering algorithm. J. Intell. Fuzzy Syst, 2020; 38(5): 6561–6570.
[11] Li W, Baoyintu, Jia B, Wang J X, Watanabe T. An energy based dynamic AODV routing protocol in wireless Ad Hoc networks. CMC-Comput. Mat. Contin, 2020; 63(1): 353–368.
[12] Anisi M H, Abdul-Salaam G, Abdullah A H. A survey of wireless sensor network approaches and their energy consumption for monitoring farm fields in precision agriculture. Precis. Agric., 2015; 16(2): 216–238.
[13] Zhu L, Fan C, Wu H, Wen Z. Coverage optimization strategy for WSN based on energy-aware. International Journal of Computers Communications & Control, 2016; 11(6): 877–888.
[14] Mohamad M M, Kheirabadi M T. Energy efficient opportunistic routing algorithm for underwater sensor network: A review. 2nd ICSITech, IEEE, October 26-27, 2016; pp.41–46.
[15] Ben Fradj H, Anane R, Bouallegue R. Opportunistic routing protocols in wireless sensor networks. Wireless Personal Communications, 2019; 104(3): 921–933.
[16] Zhang S M, Madadkhani M, Shafieezadeh M A, Mirzaei A. Novel approach to optimize power consumption in orchard WSN: Efficient opportunistic routing. Wireless Personal Communications, 2019; 108(3): 1611–1634.
[17] Alajeely M, Doss R, Ahmad A. Routing protocols in opportunistic networks - A survey. IETE Tech. Rev., 2018; 35(4): 369–387.
[18] Wu H R, Zhang L H, Miao Y S. The propagation characteristics of radio frequency signals for wireless sensor networks in large-scale farmland. Wireless Personal Communications, 2017; 95(4): 1–18.
[19] Ismail M, Islam M, Ahmad I, Khan F A, Qazi A B, Khan Z H, et al. Reliable path selection and opportunistic routing protocol for underwater wireless sensor networks. IEEE Access, 2020; 8: 100346–100364.
[20] Xuan C Z, Wu P, Zhang L N, Ma Y H, Liu Y Q, Maksim. Compressive sensing in wireless sensor network for poultry acoustic monitoring. Int J Agric & Biol Eng, 2017; 10(2): 94–102.
[21] Chen Y, Shi Y L, Wang Z Y, Huang, L. Connectivity of wireless sensor networks for plant growth in greenhouse. Int J Agric & Biol Eng, 2016; 9(1): 89–98.
[22] Pandiyaraju V, Logambigai R, Ganapathy S, Kannan A. An energy efficient routing algorithm for WSNs using intelligent fuzzy rules in precision agriculture. Wireless Personal Communications, 2020; 112(1): 243–259.
[23] Haseeb K, Din I U, Almogren A, Islam N. An energy efficient and secure IoT-based WSN framework: An application to smart agriculture. Sensors, 2020; 20(7): 2081. doi: 10.3390/s20072081.
[24] Khan T H F, Kumar D S. Ambient crop field monitoring for improving context based agricultural by mobile sink in WSN. Journal of Ambient Intelligence and Humanized Computing, 2020; 11(4): 1431–1439.
[25] Liu Y, Tong K F, Wong K K. Reinforcement learning based routing for energy sensitive wireless mesh IoT networks. Electronic Letters, 2019; 55(17): 966–968.
[26] Noh K M, Park J H, Park J S. Data transmission direction based routing algorithm for improving network performance of IoT systems. Applied Sciences, 2020; 10(11): 3784. doi: 10.3390/app10113784.
[27] Varsa G V S, Sridharan D. A balanced energy efficient virtual backbone construction algorithm in wireless sensor networks. AEU - International Journal of Electronics and Communications, 2019; 107: 110–124.
[28] Li D, Li Z. System Analysis and Development Prospect of Unmanned Farming. Transactions of the CSAM, 2020; 51(7): 1–12. (in Chinese)
[29] Chen Y, Shi Y L, Wang Z Y, Huang L. Connectivity of wireless sensor networks for plant growth in greenhouse. Int J Agric & Biol Eng, 2016; 9(1): 89–98.
[30] Liu H, Meng Z J, Wang H, Xu M. Spatio-temporal variation analysis of soil temperature based on wireless sensor network. Int J Agric & Biol Eng, 2016; 9(6): 131–138.
[31] Zhao M, Kumar A, Chong P H J, Lu R. A reliable and energy-efficient opportunistic routing protocol for dense lossy networks. IEEE Wireless Communication Letters, 2017; 6(1): 26–29.
[32] Luo J, Hu J, Wu D, Li R F. Opportunistic routing algorithm for relay node selection in wireless sensor networks. IEEE Transactions on Industrial Informatics, 2015; 11(1): 112–121.
[33] Jawad H M, Jawad A M, Nordin R, Gharghan S K, Abdullah N F, Ismail M, et al. Accurate empirical path-loss model based on particle swarm optimization for wireless sensor networks in smart agriculture. IEEE Sensors Journal, 2020; 20(1): 552–561.
[34] Mansouri M, Ilham O, Snoussi H, Richard C. Adaptive quantized target tracking in wireless sensor networks. Wireless Networks, 2011; 17(7): 1625–1639.
[35] Felzenszwalb P F, Huttenlocher D P. Efficient graph-based image segmentation. International Journal of Computer Vision, 2004; 59(2): 167–181.
[36] Barkunan S R, Bhanumathi V. An efficient deployment of sensor nodes in wireless sensor networks for agricultural field. Journal of Information Science and Engineering, 2018; 34(4): 903–918.
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Published
2021-06-11
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Miao, Y., Zhao, C., & Wu, H. (2021). Non-uniform clustering routing protocol of wheat farmland based on effective energy consumption. International Journal of Agricultural and Biological Engineering, 14(3), 163–170. Retrieved from https://ijabe.migration.pkpps03.publicknowledgeproject.org/index.php/ijabe/article/view/6540
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Information Technology, Sensors and Control Systems
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