ПЕРСПЕКТИВИ ВИКОРИСТАННЯ ЛІТАЮЧИХ ХМАРНИХ, ГРАНИЧНИХ ТА ТУМАННИХ ОБЧИСЛЕНЬ КОМПОНЕНТАМИ СИСТЕМИ МОНІТОРИНГУ ПОТЕНЦІЙНО НЕБЕЗПЕЧНИХ ОБ’ЄКТІВ
Ключові слова:
хмарні обчислення, граничні обчислення, туманні обчислення, безпілотний літаючий апарат, хмарні технології, штучний інтелект, система моніторингу, потенційно небезпечний об’єкт
Анотація
У статті проведено порівняльний аналіз технологій літаючих хмарних (ЛХО), граничних (ЛГО) та туманних (ЛТО) обчислень. Показані особливості систем, побудованих з використанням цих технологій, визначені їх переваги та недоліки. Розглянуто варіанти схем організації ЛХО, ЛГО та ЛТО. Обґрунтовано доцільність та запропоновано варіант застосування ЛХО, ЛГО та ЛТО компонентами системи моніторингу (СМ) потенційно небезпечного об’єкту (ПНО) з використанням безпілотних літальних апаратів (БПЛА). Оцінено перспективи використання методів штучного інтелекту (ШІ) підсистемами компонентів СМ ПНО. Запропоновано варіант використання методів ШІ для розширення можливостей ЛХО, ЛГО та ЛТО під час виконання СМ ПНО завдань з розвантаження обчислень, розподілу ресурсів, підтримки прийняття рішень, забезпечення безпеки та планування маршрутів руху БПЛА.Завантаження
Дані про завантаження поки що недоступні.
Посилання
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2. Mahmoud S., Mohamed N. Broker architecture for collaborative UAVs cloud computing. 2015 International Conference on Collaboration Technologies and Systems. CTS’2015 : proceedings, 1–5 June 2015, Atlanta, GA, USA. P. 212–219. DOI: 10.1109/CTS.2015.7210423.
3. Mahmoud S., Mohamed N., Al-Jaroodi J. Integrating UAVs into the Cloud Using the Concept of the Web of Things. Journal of Robotics. 2015. Vol. 2015. Article ID 631420. DOI: 10.1155/2015/631420.
4. Sara M., Jawhar I., Nader M. A softwarization architecture for UAVs and WSNs as Part of the cloud environment. 2016 International Conference on Cloud Engineering Workshops. IC2EW’2016 : proceedings, 4–8 April 2016, Berlin, Germany. P. 13–189. DOI: 10.1109/IC2EW.2016.17.
5. Majumder S., Prasad M. S. Cloud based control for unmanned aerial vehicles. 2016 3rd International Conference on Signal Processing and Integrated Networks. SPIN’2016 : proceedings, 11–12 February 2016, Noida, India. P. 421–424. DOI: 10.1109/SPIN.2016.7566731.
6. Yapp J., Seker R., Babiceanu R. UAV as a service: Enabling on-demand access and on-the-fly re-tasking of multi-tenant UAVs using cloud services. 2016 IEEE/AIAA 35th Digital Avionics Systems Conference. DASC’2016 : proceedings, 25–29 September 2016, Sacramento, CA, USA. P. 1–8. DOI: 10.1109/DASC.2016.7778007.
7. Youssef S. B. H., Rekhis S., Boudriga N., Bagula A. A cloud of UAVs for the delivery of a sink as a service to terrestrial WSNs. 2016 14th International Conference on Advances in Mobile Computing and Multi Media. MoMM'16 : proceedings, 28–30 November 2016, Singapore, Singapore. P. 317–326. DOI: 10.1145/3007120.3007138.
8. Zhang Y., Yuan Z. Cloud-based UAV data delivery over 4G network. 2017 10th International Conference on Mobile Computing and Ubiquitous Network. ICMU’2017 : proceedings, 03–05 October 2017, Toyama, Japan. P. 1–2. DOI: 10.23919/ICMU.2017.8330084.
9. Hong C., Shi D. A cloud-based control system architecture for multi-UAV. 2018 3rd International Conference on Robotics, Control and Automation. ICRCA’2018 : proceedings, 11–13 August 2018, Chengdu, China. P. 25–30. DOI: 10.1145/3265639.3265652.
10. Stan R. G., Negru C., Pop F. CloudWave: Content gathering network with flying clouds. Future Generation Computer Systems. 2019. Vol. 98. P. 474–486. DOI: 10.1016/j.future.2019.03.033.
11. Rodrigues M., Branco K. R. L. J. Cloud-SPHERE: Towards Secure UAV Service Provision. Journal of Intelligent & Robotic Systems. 2020. Vol. 97. P. 249–268. DOI: 10.1007/s10846-019-01046-6.
12. Narang M., Xiang S., Liu W., Gutierrez J., Chiaraviglio L., Sathiaseelan A., Merwaday A. UAV-assisted edge infrastructure for challenged networks. 2017 IEEE Conference on Computer Communications Workshops. INFOCOM WKSHPS’2017 : proceedings, 01–04 May 2017, Atlanta, GA, USA. P. 60–65. DOI: 10.1109/INFCOMW.2017.8116353.
13. Cheng N., Xu W., Shi W., Zhou Y., Lu N., Zhou H., Shen X. Air-Ground Integrated Mobile Edge Networks: Architecture, Challenges, and Opportunities. IEEE Communications Magazine. 2018. Vol. 56. P. 26–32. DOI: 10.1109/MCOM.2018.1701092.
14. Zhou Z., Feng J., Tan L., He Y., Gong, J. An Air-Ground Integration Approach for Mobile Edge Computing in IoT. IEEE Communications Magazine. 2018. Vol. 56. P. 40–47. DOI: 10.1109/MCOM.2018.1701111.
15. Chen W., Liu B., Huang H., Guo S., Zheng Z. When UAV Swarm Meets Edge-Cloud Computing: The QoS Perspective. IEEE Network. 2019. Vol. 33. P. 36–43. DOI: 10.1109/MNET.2019.1800222.
16. Zhou F., Wu Y., Sun H., Chu Z. UAV-Enabled mobile edge computing: Offloading optimization and trajectory design. 2018 IEEE International Conference on Communications. ICC’2018 : proceedings, 20–24 May 2018, Kansas City, MO, USA. P. 1–6. DOI: 10.1109/ICC.2018.8422277.
17. Zhou F., Wu Y., Hu R. Q., Qian Y. Computation rate maximization in UAV-Enabled wireless-powered mobile-edge computing systems. IEEE Journal on Selected Areas in Communications. 2018. Vol. 36. P. 1927–1941. DOI: 10.1109/JSAC.2018.2864426.
18. Hu X., Wong K.-K., Yang K., Zheng Z. UAV-Assisted Relaying and Edge Computing: Scheduling and Trajectory Optimization. IEEE Transactions on Wireless Communications. 2019. Vol. 18. P. 4738–4752. DOI: 10.1109/TWC.2019.2928539.
19. Li J., Liu Q., Wu P., Shu F., Jin S. Task Offloading for UAV-based Mobile Edge Computing via Deep Reinforcement Learning. 2018 IEEE/CIC International Conference on Communications in China. ICCC’2018 : proceedings, 16–18 August 2018, Beijing, China. P. 798–802. DOI: 10.1109/ICCChina.2018.8641189.
20. Messous M. A., Senouci S. M., Sedjelmaci H., Cherkaoui S. A Game Theory Based Efficient Computation Offloading in an UAV Network. IEEE Transactions on Vehicular Technology. 2019. Vol. 68. P. 4964–4974. DOI: 10.1109/TVT.2019.2902318.
21. Nguyen V. D., Khanh T. T., Van Nam P., Thu N. T., Seon Hong C., Huh E. N. Towards Flying Mobile Edge Computing. 2020 International Conference on Information Networking. ICOIN’2020 : proceedings, 07–10 January 2020, Barcelona, Spain. P. 723–725. DOI: 10.1109/ICOIN48656.2020.9016537.
22. You W., Dong C., Cheng X., Zhu X., Wu Q., Chen G. Joint Optimization of Area Coverage and Mobile-Edge Computing with Clustering for FANETs. IEEE Internet of Things Journal. 2021. Vol 8. P. 695–707. DOI: 10.1109/JIOT.2020.3006891.
23. Lee G., Saad W., Bennis M. Online Optimization for UAV-Assisted Distributed Fog Computing in Smart Factories of Industry 4.0. 2018 IEEE Global Communications Conference. GLOBECOM’2018 : proceedings, 09–13 December 2018, Abu Dhabi, United Arab Emirates. P. 1–3 DOI: 10.1109/GLOCOM.2018.8647441.
24. Mohamed N., Al-Jaroodi J., Jawhar I., Noura H., Mahmoud S. UAVFog: A UAV-based fog computing for Internet of Things. 2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI’2017 : proceedings, 04–08 August 2017, San Francisco, CA, USA. P. 1–8. DOI: 10.1109/UIC-ATC.2017.8397657.
25. Ti N. T., Bao Le L. Joint resource allocation, computation offloading, and path planning for UAV based hierarchical fog-cloud mobile systems. 2018 IEEE 7th International Conference on Communications and Electronics. ICCE’2018 : proceedings, 18–20 July 2018, Hue, Vietnam. P. 373–378. DOI: 10.1109/CCE.2018.8465572.
26. Hou X., Ren Z., Cheng W., Chen C., Zhang H. Fog Based Computation Offloading for Swarm of Drones. 2019 IEEE International Conference on Communications. ICC’2019 : proceedings, 20–24 May 2019, Shanghai, China. Vol. 2019. DOI: 10.1109/ICC.2019.8761932.
27. Devraj, Rao R. S., Das S. Fog Computing Environment in Flying Ad-hoc Network. Cloud Computing Enabled Big-Data Analytics in Wireless Ad-hoc Networks : collective monograph / ed. by S. Das, R. S. Rao, I. Das, V. Jain, N. Singh. Boca Raton, FL, USA : CRC Press, 2022. P. 31–48. DOI: 10.1201/9781003206453-3.
28. Uddin M. A., Ayaz M., Mansour A., Aggoune, el H. M., Sharif Z., Razzak I. Cloud-connected flying edge computing for smart agriculture. Peer-to-Peer Networking and Applications. 2021. Vol. 14. P. 3405–3415. DOI: 10.1007/s12083-021-01191-6.
29. Yazid Y., Ez-Zazi I., Guerrero-González A., El Oualkadi A., Arioua M. UAV-enabled mobile edge-computing for IoT based on AI: A comprehensive review. Drones. 2021. Vol 5. Article ID 631420. DOI: 10.3390/drones5040148.
Опубліковано
2022-11-29
Як цитувати
Skorobohatko S. Перспективи використання літаючих хмарних, граничних та туманних обчислень компонентами системи моніторингу потенційно небезпечних об’єктів / S. Skorobohatko, H. Fesenko // Системи управління, навігації та зв’язку. Збірник наукових праць. – Полтава: ПНТУ, 2022. – Т. 4 (70). – С. 145-152. – doi:https://doi.org/10.26906/SUNZ.2022.4.145.
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Цивільна безпека
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