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Wireless Networks
Erschienen in: Wireless Networks 4/2022

22.03.2022 | Original Paper

Trajectory optimization for the UAV assisted data collection in wireless sensor networks

verfasst von: Kartik Saxena, Nitin Gupta, Jahnvi Gupta, Deepak Kumar Sharma, Kapal Dev

Erschienen in: Wireless Networks | Ausgabe 4/2022

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Abstract

Wireless sensor networks (WSNs) have been imperative means for the collection of information in various fields. Integration of WSN with the latest technology like unmanned aerial vehicles (UAVs) can increase the overall performance of the WSN by increasing the sensor coverage or reducing the latency. However, for full coverage of the sensors to avoid data loss, to reduce the time required to deliver the data to sink and to minimize the calculation of the total path length, overall trajectory optimization is required. In order to solve these challenges, in this work, trajectory of the UAV is considered as a hamiltonian path that covers all the cluster heads in the WSN. The proposed scheme is able to calculate path in polynomial time which is otherwise considered to be NP-Hard. Moreover, data of sensor nodes is sent directly to the UAV thereby eliminating the need of any routing protocol. Simulation results show that the coverage of nodes is improved along with minimized data loss in comparison with single-hop and multi-hop routing protocols of WSN.
Vorheriger Artikel Wireless powered backscatter-aided cooperative communication scheme for IoT
Nächster Artikel Design of a Coplanar Waveguide-Fed Wideband Compact-Size Circularly Polarized Antenna and polarization-sense alteration

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Literatur
1.
de Souza, B. J. O., & Endler, M. (2020). Evaluating flight coordination approaches of UAV squads for WSN data collection enhancing the internet range on WSN data collection. Journal of Internet Services and Applications, 11(1), 1–44.CrossRef
2.
Vijay, U., & Gupta, N. (2013). Clustering in WSN based on minimum spanning tree using divide and conquer approach. International Journal of Computer and Information Engineering, 7(7), 926–930.
3.
Huang, H., Savkin, A. V., Ding, M., & Huang, C. (2019). Mobile robots in wireless sensor networks: A survey on tasks. Computer Networks, 148, 1–19.CrossRef
4.
Popescu, D., Stoican, F., Stamatescu, G., Chenaru, O., & Ichim, L. (2019). A survey of collaborative UAV-WSN systems for efficient monitoring. Sensors, 19(21), 4690.CrossRef
5.
Zhang, T., Xu, Y., Loo, J., Yang, D., & Xiao, L. (2019). Joint computation and communication design for UAV-assisted mobile edge computing in IOT. IEEE Transactions on Industrial Informatics, 16(8), 5505–5516.CrossRef
6.
7.
Zeng, Y., & Zhang, R. (2017). Energy-efficient UAV communication with trajectory optimization. IEEE Transactions on Wireless Communications, 16(6), 3747–3760.CrossRef
8.
Shi, W., Zhou, H., Li, J., Xu, W., Zhang, N., & Shen, X. (2018). Drone assisted vehicular networks: Architecture, challenges and opportunities. IEEE Network, 32(3), 130–137.CrossRef
9.
He, D., Chan, S., & Guizani, M. (2017). Drone-assisted public safety networks: The security aspect. IEEE Communications Magazine, 55(8), 218–223.CrossRef
10.
Grover, K., Kahali, D., Verma, S., & Subramanian, B. (2020). WSN-based system for forest fire detection and mitigation. In B. Subramanian, S. S. Chen, & K. Reddy (Eds.), Emerging technologies for agriculture and environment (pp. 249–260). Springer.CrossRef
11.
Vera-Amaro, R., Rivero-Ángeles, M. E., & Luviano-Juárez, A. (2020). Data collection schemes for animal monitoring using WSNS-assisted by UAVS: WSNS-oriented or UAV-oriented. Sensors, 20(1), 262.CrossRef
12.
Velez, F. J., Nadziejko, A., Christensen, A. L., Oliveira, S., Rodrigues, T., Costa, V., Duarte, M., Silva, F., & Gomes, J. (2015). Wireless sensor and networking technologies for swarms of aquatic surface drones (Vol. VTC2015-Fall, pp. 1–2). IEEE.
13.
Hefeeda, M., & Bagheri, M. (2009). Forest fire modeling and early detection using wireless sensor networks. Ad-Hoc and Sensor Wireless Networks, 7(3–4), 169–224.
14.
Bahrepour, M., Meratnia, N., & Havinga, P. J. (2008). Automatic fire detection: A survey from wireless sensor network perspective. Pervasive System Group, Univeristy of Twente.
15.
Ngai, E., Zhou, Y., Lyu, M. R., & Liu, J. (2010). A delay-aware reliable event reporting framework for wireless sensor-actuator networks. Ad Hoc Networks, 8(7), 694–707.CrossRef
16.
Doolin, D. M., & Sitar, N. (2005). Wireless sensors for wildfire monitoring. In Smart structures and materials 2005: Sensors and smart structures technologies for civil, mechanical, and aerospace systems (Vol. 5765, pp. 477–484). International Society for Optics and Photonics.
17.
Anisi, M. H., Abdullah, A. H., Razak, S. A., Ngadi, M., et al. (2012). Overview of data routing approaches for wireless sensor networks. Sensors, 12(4), 3964–3996.CrossRef
18.
Khan, A. W., Abdullah, A. H., Anisi, M. H., & Bangash, J. I. (2014). A comprehensive study of data collection schemes using mobile sinks in wireless sensor networks. Sensors, 14(2), 2510–2548.CrossRef
19.
Martinez-de Dios, J. R., Lferd, K., de San Bernabé, A., Núnez, G., Torres-González, A., & Ollero, A. (2013). Cooperation between UAS and wireless sensor networks for efficient data collection in large environments. Journal of Intelligent & Robotic Systems, 70(1), 491–508.
20.
Wang, J., Cao, J., Ji, S., & Park, J. H. (2017). Energy-efficient cluster-based dynamic routes adjustment approach for wireless sensor networks with mobile sinks. The Journal of Supercomputing, 73(7), 3277–3290.CrossRef
21.
Wang, C., Ma, F., Yan, J., De, D., & Das, S. K. (2015). Efficient aerial data collection with UAV in large-scale wireless sensor networks. International Journal of Distributed Sensor Networks, 11(11), 286,080.CrossRef
22.
Khawaja, W., Guvenc, I., Matolak, D. W., Fiebig, U. C., & Schneckenburger, N. (2019). A survey of air-to-ground propagation channel modeling for unmanned aerial vehicles. IEEE Communications Surveys & Tutorials, 21(3), 2361–2391.CrossRef
23.
Uragun, B. (2011). Energy efficiency for unmanned aerial vehicles. In 2011 10th international conference on machine learning and applications and workshops (Vol. 2, pp. 316–320). IEEE
24.
Mozaffari, M., Saad, W., Bennis, M., & Debbah, M. (2017). Mobile unmanned aerial vehicles (UAVS) for energy-efficient internet of things communications. IEEE Transactions on Wireless Communications, 16(11), 7574–7589.CrossRef
25.
26.
Fotouhi, A., Qiang, H., Ding, M., Hassan, M., Giordano, L. G., Garcia-Rodriguez, A., & Yuan, J. (2019). Survey on UAV cellular communications: Practical aspects, standardization advancements, regulation, and security challenges. IEEE Communications Surveys & Tutorials, 21(4), 3417–3442.CrossRef
27.
Garraffa, M., Bekhti, M., Létocart, L., Achir, N., & Boussetta, K. (2018). Drones path planning for WSN data gathering: A column generation heuristic approach (pp. 1–6). IEEE.
28.
Pascarella, D., Venticinque, S., & Aversa, R. (2013). Agent-based design for UAV mission planning. In 2013 eighth international conference on P2P, parallel, grid, cloud and internet computing (pp. 76–83). IEEE.
29.
Thakur, D., Likhachev, M., Keller, J., Kumar, V., Dobrokhodov, V., Jones, K., Wurz, J., & Kaminer, I. (2013). Planning for opportunistic surveillance with multiple robots. In 2013 IEEE/RSJ international conference on intelligent robots and systems (pp. 5750–5757). IEEE.
30.
Ladosz, P., Oh, H., & Chen, W. H. (2018). Trajectory planning for communication relay unmanned aerial vehicles in urban dynamic environments. Journal of Intelligent & Robotic Systems, 89(1), 7–25.CrossRef
31.
Wu, Q., Sun, P., & Boukerche, A. (2018). An energy-efficient UAV-based data aggregation protocol in wireless sensor networks. In Proceedings of the 8th ACM symposium on design and analysis of intelligent vehicular networks and applications (pp. 34–40).
32.
Fu, Y., Ding, M., Zhou, C., & Hu, H. (2013). Route planning for unmanned aerial vehicle (UAV) on the sea using hybrid differential evolution and quantum-behaved particle swarm optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 43(6), 1451–1465.CrossRef
33.
Nikhitha, S., & Panda, M. (2018). Optimal sensor data harvesting using a mobile sink. Procedia Computer Science, 143, 921–930.CrossRef
34.
Sun, P., & Boukerche, A. (2018). Performance modeling and analysis of a UAV path planning and target detection in a UAV-based wireless sensor network. Computer Networks, 146, 217–231.CrossRef
35.
Alemayehu, T. S., & Kim, J. H. (2017). Efficient nearest neighbor heuristic tsp algorithms for reducing data acquisition latency of UAV relay WSN. Wireless Personal Communications, 95(3), 3271–3285.CrossRef
36.
Dong, M., Ota, K., Lin, M., Tang, Z., Du, S., & Zhu, H. (2014). UAV-assisted data gathering in wireless sensor networks. The Journal of Supercomputing, 70(3), 1142–1155.CrossRef
37.
Xu, Y. H., Sun, Q. Y., & Xiao, Y. T. (2018). An environmentally aware scheme of wireless sensor networks for forest fire monitoring and detection. Future Internet, 10(10), 102.CrossRef
38.
Molina-Pico, A., Cuesta-Frau, D., Araujo, A., Alejandre, J., & Rozas, A. (2016). Forest monitoring and wildland early fire detection by a hierarchical wireless sensor network. Journal of Sensors, 2016, 1–8.CrossRef
39.
Mozaffari, M., Saad, W., Bennis, M., Nam, Y. H., & Debbah, M. (2019). A tutorial on UAVS for wireless networks: Applications, challenges, and open problems. IEEE Communications Surveys & Tutorials, 21(3), 2334–2360.CrossRef
40.
Rahman, M. N., Hanuranto, M. I. A. T., & Mayasari, S. R. (2017). Trilateration and iterative multilateration algorithm for localization schemes on wireless sensor network. In 2017 international conference on control, electronics, renewable energy and communications (ICCREC) (pp. 88–92). IEEE.
41.
Xu, J., Jin, N., Lou, X., Peng, T., Zhou, Q., & Chen, Y. (2012). Improvement of leach protocol for WSN. In 2012 9th international conference on fuzzy systems and knowledge discovery (pp. 2174–2177). IEEE.
42.
43.
44.
Dargie, W., & Poellabauer, C. (2010). Fundamentals of wireless sensor networks: Theory and practice. Wiley.CrossRef
45.
Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to algorithms. MIT Press.MATH
46.
Fitriawan, H., Susanto, M., Arifin, A.S., Mausa, D., Trisanto, A. (2017). Zigbee based wireless sensor networks and performance analysis in various environments. In 2017 15th international conference on quality in research (QiR): International symposium on electrical and computer engineering (pp. 272–275). IEEE.
47.
48.
49.
50.
Xing, G., Wang, T., Xie, Z., & Jia, W. (2008). Rendezvous planning in wireless sensor networks with mobile elements. IEEE Transactions on Mobile Computing, 7(12), 1430–1443.CrossRef
51.
Mazayev, A., Correia, N., & Schütz, G. (2016). Data gathering in wireless sensor networks using unmanned aerial vehicles. International Journal of Wireless Information Networks, 23(4), 297–309.CrossRef
52.
Liu, S., Wei, Z., Guo, Z., Yuan, X., & Feng, Z. (2018). Performance analysis of UAVS assisted data collection in wireless sensor network. In 2018 IEEE 87th vehicular technology conference (VTC Spring) (pp. 1–5). IEEE.
53.
Sharma, G., Bala, S., & Verma, A. K. (2013). Extending certificateless authentication for wireless sensor networks: A novel insight. International Journal of Computer Science Issues (IJCSI), 10(6), 167.
54.
Yaacoub, E., Abu-Dayya, A., & Matin, M. (2012). Multihop routing for energy efficiency in wireless sensor networks. In Wireless sensor networks—Technology and protocols (pp. 165–186). InTech Press.
Metadaten
Titel
Trajectory optimization for the UAV assisted data collection in wireless sensor networks
verfasst von
Kartik Saxena
Nitin Gupta
Jahnvi Gupta
Deepak Kumar Sharma
Kapal Dev
Publikationsdatum
22.03.2022
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 4/2022
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-022-02934-w

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