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5G/IoT-enabled UAVs for multimedia delivery in industry-oriented applications

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Abstract

Industrial Internet of Things (IIoTs) is the fast growing network of interconnected things that collect and exchange data using embedded sensors planted everywhere. It is an interconnection of several things through a diverse communication system capable of monitoring, collecting, exchanging, analysing, and delivering valuable and challenging amount of information. Given their ability to be operated autonomously, their high mobility, and their communication and processing power, Unmanned Aerial Vehicles (UAVs) are expected to be involved in numerous IIoT-related applications, where multimedia and video streaming plays a key role. Our main interest is the multimedia routing in IIoT and its facilities during and/or after operational hours. For recovering, constructing and selecting k-disjoint paths, capable of putting up with failure of the parameters but satisfying the quality of service, we introduce an industry-oriented Canonical Particle Swarm (CPS) optimization data delivery framework. During communication with the UAV, multi-swarm strategy is used to determine the optimal direction while performing a multipath routing. Authenticity of the proposed approach has been tested and results show that, compared to the ordinary Canonical Particle Multi-path Swarm (CPMS) optimization and Fully Multi-path Particle Swarm (FMPS) optimization, the proposed method is better.

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References

  1. 3GPP LTE version 15, [Online]: http://www.3gpp.org/release-15. Accessed 25 April 2018

  2. Adnan M, Razzaque M, Ahmed I, Isnin I (2014) Bio-mimic optimization strategies in wireless sensor networks: a survey. Sensors 14(1):299–345

    Article  Google Scholar 

  3. Agiwal M, Roy A, Saxena N (2016) Next generation 5G wireless networks: a comprehensive survey. IEEE Commun Surv Tutorials 18(3):1617–1655

    Article  Google Scholar 

  4. Al-Nidawi Y, Yahya H, Kemp AH (2016) Tackling mobility in low latency deterministic multihop ieee 802.15. 4e sensor network. IEEE Sensors J 16(5):1412–1427

    Article  Google Scholar 

  5. Al-Turjman F (2017) Price-based data delivery framework for dynamic and pervasive IoT. Elsevier Pervasive and Mobile Computing Journal 42:299–316

    Article  Google Scholar 

  6. Al-Turjman F (2017) Information-centric sensor networks for cognitive IoT: an overview. Ann Telecommun 72(1):3–18

    Article  Google Scholar 

  7. Al-Turjman F (2017) Cognitive routing protocol for disaster-inspired internet of things. Futur Gener Comput Syst. https://doi.org/10.1016/j.future.2017.03.014.

  8. Chi Q, Yan H, Zhang C, Pang Z, Xu L (2014) A reconfigurable smart sensor interface for industrial WSN in IoT environment. IEEE Trans Ind Inf 10(2):1417–1425

    Article  Google Scholar 

  9. Dhir M (2016) A survey on fault tolerant multipath routing protocols in wireless sensor networks. Global J Comp Sci Technol 15(3)

  10. Elisa S, Pascoli SD, Iannaccone G (2016) Low-power wearable ECG monitoring system for multiple-patient remote monitoring. IEEE Sensors J 16(13):5452–5462

    Article  Google Scholar 

  11. Hadjidj A, Bouabdallah A, Challal Y (2010) HDMRP: An efficient fault-tolerant multipath routing protocol for heterogeneous wireless sensor networks. 7th International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, p 469–482

  12. Al-Turjman F, Hassanein H, Ibnkahla M (2015) Towards prolonged lifetime for deployed WSNs in outdoor environment monitoring. Ad Hoc Netw J 24(A):172–185

  13. Al-Turjman F, Alturjman S (2018) Context-sensitive Access in Industrial Internet of Things (IIoT) Healthcare Applications. IEEE Trans Ind Inf 14(6):2736–2744

  14. Al-Turjman F (2018) QoS–aware Data Delivery Framework for Safety-inspired Multimedia in Integrated Vehicular-IoT. Elsevier Computer Communications Journal 121:33–43

  15. Jiang S, Zhao Z, Mou S, Wu Z, Luo Y (2012) Linear Decision Fusion under the Control of Constrained PSO for WSNs. Int J Distrib Sens Netw 8(1):871596

    Article  Google Scholar 

  16. Karschnia B (2017) Industrial Internet of Things (IIoT) benefits, examples | Control Engineering, Controleng.com. [Online]. Available: http://www.controleng.com/single-article/industrial-internet-of-things-iiot-benefits-examples/a2fdb5aced1d779991d91ec3066cff40.html. Accessed 31 Aug 2017

  17. Lim WH, Mat Isa NA (2014) Particle swarm optimization with adaptive time-varying topology connectivity. Appl Soft Comput 24:623–642

    Article  Google Scholar 

  18. Pant M, Radha T, Singh VP (2007) A simple diversity guided particle swarm optimization. In: Proc. IEEE Congr. Evol. Comput., p 3294–3299

  19. Petrov V, et al (2017) When IoT keeps people in the loop: a path towards a new global utility. arXiv preprint arXiv:1703.00541

  20. Radwan A, Rodriguez J (2015) Energy efficient smart phone for 5G networks", Springer Book, ISBN 978–3–319-10314-3

  21. Radwan A, Domingues M, Rodriguez J (2017) Mobile caching-enabled small-cells for delay-tolerant e-Health apps. ICC

  22. Shieh H-L, Kuo C-C, Chiang C-M (2011) Modified particle swarm optimization algorithm with simulated annealing behavior and its numerical verification. Appl Math Comput 218(8):4365–4383

    MATH  Google Scholar 

  23. Singh G, Al-Turjman F (2016) Learning data delivery paths in QoI-aware information-centric sensor networks. IEEE Internet Things J 3(4):572–580

    Article  Google Scholar 

  24. Vis JK (2015) Particle swarm optimizer for finding robust optima, Leiden, The Netherlands. http://www.liacs.nl/assets/Bachelorscripties/2009-12JonathanVis.pdf

  25. What is 5G? [Online]: https://www.surrey.ac.uk/5gic. Accessed 25 April 2018

  26. Wu C-H, Chung Y-C (2007) Heterogeneous wireless sensor network deployment and topology control based on irregular sensor model. In: Cérin C, Li K-C (eds) Proceedings in advances in grid and pervasive computing. Springer Berlin Heidelberg, p 78–88

  27. Zhou Y, Wang X, Wang T, Liu B, Sun W (2016) Fault-tolerant multi- path routing protocol for WSN based on HEED. Int J Sensor Netw 20(1):37–45

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Engineering, Antalya Bilim University, Antalya, Turkey

    Fadi Al-Turjman & Sinem Alturjman

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  1. Fadi Al-Turjman
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  2. Sinem Alturjman
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Correspondence to Fadi Al-Turjman.

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Al-Turjman, F., Alturjman, S. 5G/IoT-enabled UAVs for multimedia delivery in industry-oriented applications. Multimed Tools Appl 79, 8627–8648 (2020). https://doi.org/10.1007/s11042-018-6288-7

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  • DOI: https://doi.org/10.1007/s11042-018-6288-7

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