Modifying a method for direct data collection by a telecommunication aerial platform from nodes of wireless sensor networks

Authors

DOI:

https://doi.org/10.15587/1729-4061.2022.263559

Keywords:

wireless sensor networks, clustering, flight path, telecommunication aerial platform, data collection

Abstract

Wireless sensor networks are becoming increasingly important in both the civilian and military fields. The object of this study is the process of collecting data by a telecommunication aerial platform from network nodes under conditions of their remoteness from the telecommunication infrastructure. Most available papers consider a solution to partial problems related to the process of data acquisition by a telecommunication aerial platform: clustering of the network, search for the shortest flight route, minimization of energy costs of nodes, etc. Therefore, an improved method of direct data collection by a telecommunication air platform is proposed, which consistently and comprehensively solves these problems. Unlike existing methods, it takes into consideration several objective functions (optimization of data collection time by a telecommunication air platform and a network functioning time), parameters of the state of nodes and clusters, as well as makes it possible to obtain solutions in real time. A special feature of the proposed method is the search for the optimal solution according to the hierarchy: network – cluster – node. At the network level, the following is optimized: the number of clusters of a certain dimensionality and the trajectory of the cluster flyby. At the cluster level, the points (intervals) of data collection during the freezing (in motion) of the telecommunication air platform and the trajectory of its flight within a cluster are determined. At the node level, its energy consumption is minimized by reducing the distance to the telecommunication aerial platform. The trajectory of the platform within a cluster is calculated according to the developed rule base. The rules implement the method of situational management. The conditions of application are the parameters of the state of the nodes, the solutions are the parameters of the trajectory of a telecommunication aerial platform, and the intervals of data acquisition. The rules take into consideration the priority of the objective functions, the state of the parameters of the cluster nodes, and the previously made basic decision on the trajectory of the flyby. The simulation results show that the application of the method reduces the time of data collection up to 15 % or increases the network functioning time to 17 %.

Author Biographies

Andrii Hrymud, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

Adjunct

Department of Automated Management Systems

Valery Romaniuk, Military Institute of Telecommunications and Information Technologies named after Heroes of Kruty

Doctor of Technical Sciences, Professor

Department of Automated Management Systems

References

  1. Popescu, Stoican, Stamatescu, Chenaru, Ichim (2019). A Survey of Collaborative UAV–WSN Systems for Efficient Monitoring. Sensors, 19 (21), 4690. doi: https://doi.org/10.3390/s19214690
  2. Nguyen, M. T., Nguyen, C. V., Do, H. T., Hua, H. T., Tran, T. A., Nguyen, A. D. et. al. (2021). UAV-Assisted Data Collection in Wireless Sensor Networks: A Comprehensive Survey. Electronics, 10 (21), 2603. doi: https://doi.org/10.3390/electronics10212603
  3. Jawhar, I., Mohamed, N., Al-Jaroodi, J. (2015). UAV-based data communication in wireless sensor networks: Models and strategies. 2015 International Conference on Unmanned Aircraft Systems (ICUAS). doi: https://doi.org/10.1109/icuas.2015.7152351
  4. Romaniuk, V., Lysenko, O., Romaniuk, A., Zhuk, O. (2020). Increasing the efficiency of data gathering in clustered wireless sensor networks using UAV. Information and Telecommunication Sciences, 1, 102–107. doi: https://doi.org/10.20535/2411-2976.12020.102-107
  5. Alfattani, S., Jaafar, W., Yanikomeroglu, H., Yongacoglu, A. (2019). Multi-UAV Data Collection Framework for Wireless Sensor Networks. 2019 IEEE Global Communications Conference (GLOBECOM). doi: https://doi.org/10.1109/globecom38437.2019.9014306
  6. Qi, N., Wang, W., Ye, D., Wang, M., Tsiftsis, T. A., Yao, R. (2021). Energy‐efficient full‐duplex UAV relaying networks: Trajectory design for channel‐model‐free scenarios. ETRI Journal, 43 (3), 436–446. doi: https://doi.org/10.4218/etrij.2020-0060
  7. Ho, D.-T., Grotli, E. I., Sujit, P. B., Johansen, T. A., Sousa, J. B. (2013). Cluster-based communication topology selection and UAV path planning in wireless sensor networks. 2013 International Conference on Unmanned Aircraft Systems (ICUAS). doi: https://doi.org/10.1109/icuas.2013.6564674
  8. Romaniuk, A., Samberg, A. (2021). Direct data collection method by telecommunications aerial platforms from the wireless sensor network nodes. Information and Telecommunication Sciences, 1, 12–23. doi: https://doi.org/10.20535/2411-2976.12021.12-23
  9. Jasim, A. A., Idris, M. Y. I., Razalli Bin Azzuhri, S., Issa, N. R., Rahman, M. T., Khyasudeen, M. F. b. (2021). Energy-Efficient Wireless Sensor Network with an Unequal Clustering Protocol Based on a Balanced Energy Method (EEUCB). Sensors, 21 (3), 784. doi: https://doi.org/10.3390/s21030784
  10. Rashed, S., Soyturk, M. (2017). Analyzing the Effects of UAV Mobility Patterns on Data Collection in Wireless Sensor Networks. Sensors, 17(2), 413. doi: https://doi.org/10.3390/s17020413
  11. Huang, W., Yu, J. X. (2017). Investigating TSP Heuristics for Location-Based Services. Data Science and Engineering, 2 (1), 71–93. doi: https://doi.org/10.1007/s41019-016-0030-0
  12. Isaacs, J., Hespanha, J. (2013). Dubins Traveling Salesman Problem with Neighborhoods: A Graph-Based Approach. Algorithms, 6 (1), 84–99. doi: https://doi.org/10.3390/a6010084
  13. Yue, W., Jiang, Z. (2018). Path Planning for UAV to Collect Sensors Data Based on Spiral Decomposition. Procedia Computer Science, 131, 873–879. doi: https://doi.org/10.1016/j.procs.2018.04.291
  14. Chengliang, W, Jun-hui, Y. (2015). Path Planning for UAV to Collect Sensor Data in Large-Scale WSNs. Transaction of Beijing Institute of Technology, 35, 1044–1049.
  15. Nitesh, K., Jana, P. K. (2019). Convex hull based trajectory design for mobile sink in wireless sensor networks. International Journal of Ad Hoc and Ubiquitous Computing, 30 (1), 26. doi: https://doi.org/10.1504/ijahuc.2019.097092
  16. Jodeh, N. M., Cobb, R., Livermore, R. A. (2016). Optimal Flight Paths in Wireless Sensor Networks: Modeling, Simulation, and Flight Test. AIAA Guidance, Navigation, and Control Conference. doi: https://doi.org/10.2514/6.2016-0383
  17. Pan, Y., Yang, Y., Li, W. (2021). A Deep Learning Trained by Genetic Algorithm to Improve the Efficiency of Path Planning for Data Collection With Multi-UAV. IEEE Access, 9, 7994–8005. doi: https://doi.org/10.1109/access.2021.3049892
  18. Rezende, J. da C. V., Silva, R. I. da, Souza, M. J. F. (2020). Gathering Big Data in Wireless Sensor Networks by Drone. Sensors, 20 (23), 6954. doi: https://doi.org/10.3390/s20236954
  19. Ebrahimi, D., Sharafeddine, S., Ho, P.-H., Assi, C. (2019). UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks. IEEE Internet of Things Journal, 6 (2), 1893–1905. doi: https://doi.org/10.1109/jiot.2018.2878834
  20. Zhan, C., Zeng, Y., Zhang, R. (2018). Energy-Efficient Data Collection in UAV Enabled Wireless Sensor Network. IEEE Wireless Communications Letters, 7 (3), 328–331. doi: https://doi.org/10.1109/lwc.2017.2776922
  21. Nazib, R. A., Moh, S. (2021). Energy-Efficient and Fast Data Collection in UAV-Aided Wireless Sensor Networks for Hilly Terrains. IEEE Access, 9, 23168–23190. doi: https://doi.org/10.1109/access.2021.3056701
  22. Ho, D.-T., Grotli, E. I., Johansen, T. A. (2013). Heuristic algorithm and cooperative relay for energy efficient data collection with a UAV and WSN. 2013 International Conference on Computing, Management and Telecommunications (ComManTel). doi: https://doi.org/10.1109/commantel.2013.6482418
  23. Say, S., Inata, H., Liu, J., Shimamoto, S. (2016). Priority-Based Data Gathering Framework in UAV-Assisted Wireless Sensor Networks. IEEE Sensors Journal, 16 (14), 5785–5794. doi: https://doi.org/10.1109/jsen.2016.2568260
  24. Anwit, R., Tomar, A., Jana, P. K. (2020). Scheme for tour planning of mobile sink in wireless sensor networks. IET Communications, 14 (3), 430–439. doi: https://doi.org/10.1049/iet-com.2019.0613
  25. Pang, A., Chao, F., Zhou, H., Zhang, J. (2020). The Method of Data Collection Based on Multiple Mobile Nodes for Wireless Sensor Network. IEEE Access, 8, 14704–14713. doi: https://doi.org/10.1109/access.2020.2966652
  26. Ghdiri, O., Jaafar, W., Alfattani, S., Abderrazak, J. B., Yanikomeroglu, H. (2021). Offline and Online UAV-Enabled Data Collection in Time-Constrained IoT Networks. IEEE Transactions on Green Communications and Networking, 5 (4), 1918–1933. doi: https://doi.org/10.1109/tgcn.2021.3104801
  27. Zagoruyko, N. G. (1999). Prikladnye metody analiza dannykh i znaniy. Novosibirsk: IM SO RAN, 270.
  28. Rahman, S. ur, Cho, Y.-Z. (2018). UAV positioning for throughput maximization. EURASIP Journal on Wireless Communications and Networking, 2018 (1). doi: https://doi.org/10.1186/s13638-018-1038-0
  29. Hrymud, A., Romaniuk, V. (2022). Flight trajectory search model of a telecommunications aerial platform for collecting data from nodes of a clustered military wireless sensor network. Zbirnyk naukovykh prats Tsentru voienno-stratehichnykh doslidzhen NUOU imeni Ivana Cherniakhovskoho, 1 (74), 118–128. doi: https://doi.org/10.33099/2304-2745/2022-1-74/118-128

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Published

2022-08-31

How to Cite

Hrymud, A., & Romaniuk, V. (2022). Modifying a method for direct data collection by a telecommunication aerial platform from nodes of wireless sensor networks. Eastern-European Journal of Enterprise Technologies, 4(9(118), 15–29. https://doi.org/10.15587/1729-4061.2022.263559

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Section

Information and controlling system