References
- M. Sharma, D. Chadha, and V. Chandra, High-altitude platform for free-space optical communication: performance evaluation and reliability analysis, IEEE/OSA J. Opt. Commun. Netw. 8 (2016), 600-609. https://doi.org/10.1364/JOCN.8.000600
- M. Mozaffari et al., A tutorial on uavs for wireless networks: applications, challenges, and open problems, IEEE Commun. Surveys Tutorials 21 (2019), 2334-2360. https://doi.org/10.1109/COMST.2019.2902862
- Z. Zhang et al., 6G wireless networks: vision, requirements, architecture, and key technologies, IEEE Veh. Technol. Mag. 14 (2019), 28-41. https://doi.org/10.1109/MVT.2019.2921208
- M. A. Esmail, H. Fathallah, and M. Alouini, Channel modeling and performance evaluation of FSO communication systems in fog, In Proc. int. Conf. Telecommun. (Thessaloniki, Greece), 2016, pp. 1-5.
- S. Song et al., Analysis of wireless backhaul networks based on aerial platform technology for 6g systems, CMC Comput. Materials Continua. 62 (2020), 473-494. https://doi.org/10.32604/cmc.2020.09052
- S. Chandrasekharan et al., Designing and implementing future aerial communication networks, IEEE Commun. Mag. 54 (2016), 26-34. https://doi.org/10.1109/MCOM.2016.7470932
- N. Wang, E. Hossain, and V. K. Bhargava, Backhauling 5G small cells: a radio resource management perspective, IEEE Wireless Commun. 22 (2015), 41-49. https://doi.org/10.1109/MWC.2015.7306536
- S. J. Lee et al., Development of autonomous flight control system for 50m unmanned airship, in Proc. Intell. Sens., Sens. Netw. Inf. Process. Conf. (Melbourne, Australia), 2004, pp. 457-461.
- R. La Scalea et al.Opportunities for autonomous UAV in harsh environments, in Proc. Int. Symp. Wireless Commun. Syst. (Oulu, Finland), 2019, pp. 227-232.
- M. A. Esmail, H. Fathallah, and M. S. Alouini, Outdoor FSO communications under fog: Attenuation modeling and performance evaluation, IEEE Photon. J. 8 (2016), 1-22.
- S. Wan et al., Towards big data processing in IoT: Path planning and resource management of UAV base stations in mobile-edge computing system, IEEE Internet Things J. 7 (2020), 5995-6009. https://doi.org/10.1109/JIOT.2019.2954825
- J. Zhang, Y. Zeng, and R. Zhang, UAV-enabled radio access network: Multi-mode communication and trajectory design, IEEE Trans. Signal Process. 66 (2018), 5269-5284. https://doi.org/10.1109/TSP.2018.2866384
- G. Wang, L. Zhang, and W. Xu, What can we learn from four years of data center hardware failures?, in Proc. Annu. IEEE/IFIP Int. Conf. Dependable Syst. Netw. (Denver, CO, USA), 2017, pp. 25-36.
- S. Kavulya, et al., An analysis of traces from a production mapreduce cluster, in Proc. IEEE/ACM Int. Conf. Cluster, Cloud Grid Comput. (Melbourne, Australia), 2010, pp. 94-103.
- Q. Zhang et al., Response delay optimization in mobile edge computing enabled UAV swarm, IEEE Trans. Veh. Technol. 69 (2020), 3280-3295. https://doi.org/10.1109/TVT.2020.2964821
- A. Asheralieva, and D. Niyato, Game theory and lyapunov optimization for cloud-based content delivery networks with device-to-device and UAV-enabled caching, IEEE Trans. Veh. Technol. 68 (2019), 10094-10110. https://doi.org/10.1109/TVT.2019.2934027
- J. Li, and Y. Han, A traffic service scheme for delay minimization in multi-layer UAV networks, IEEE Trans. Veh. Technol. 67 (2018), 5500-5504. https://doi.org/10.1109/TVT.2018.2806625
- X. Wei et al., Joint optimization of energy consumption and delay in cloud-to-thing continuum, IEEE Internet Things J. 6 (2019), 2325-2337. https://doi.org/10.1109/JIOT.2019.2906287
- J. Zhang et al., Stochastic computation offloading and trajectory scheduling for UAV-assisted mobile edge computing, IEEE Internet Things J. 6 (2018), 3688-3699. https://doi.org/10.1109/JIOT.2018.2890133
- M. Koushik, and F. Hu, S. Kumar, Deep Q-learning-based node positioning for throughput-optimal communications in dynamic UAV swarm network, IEEE Trans. Cognitive Commun. Netw. 5 (2019), 554-566. https://doi.org/10.1109/TCCN.2019.2907520
- Z. Zhang et al., UAV-enabled multiple traffic backhaul based on multiple RNAs: A batch-arrival-queuing-inspired approach, IEEE Access 7 (2019), 161437-161448. https://doi.org/10.1109/ACCESS.2019.2951603
- M. Zaharia et al., Discretized streams: Fault-tolerant streaming computation at scale, in Proc. ACM Symp. Oper. Syst. Principles (Farmington, PA), 2013, pp. 423-438.
- W. Li et al., Wide-area spark streaming: Automated routing and batch sizing, IEEE Trans. Parallel Distrib. Syst. 30 (2018), 1434-1448. https://doi.org/10.1109/tpds.2018.2880189
- F. Luo et al., Stability of cloud-based UAV systems supporting big data acquisition and processing, IEEE Trans. Cloud Comput. 7 (2019), 866-877. https://doi.org/10.1109/TCC.2017.2696529
- S. Sidhanta, W. Golab, and S. Mukhopadhyay, Deadline-aware cost optimization for spark, IEEE Trans. Big Data (2019), https://doi.org/10.1109/TBDATA.2019.2908188.
- J. Lee, B. Kim, and J. M. Chung, Time estimation and resource minimization scheme for apache spark and hadoop big data systems with failures, IEEE Access 7 (2019), 9658-9666. https://doi.org/10.1109/ACCESS.2019.2891001
- M. Akkouchi, On the convolution of exponential distributions, J. Chungcheong Math. Soc. 21 (2008), 501-510.
Cited by
- The Intelligent Integration of Interactive Installation Art Based on Artificial Intelligence and Wireless Network Communication vol.2021, 2021, https://doi.org/10.1155/2021/3123317
- Optimization of the Online Teaching System Based on Streaming Media vol.2021, 2020, https://doi.org/10.1155/2021/5552168
- 6G and Internet of Things: a survey vol.8, pp.2, 2020, https://doi.org/10.1080/23270012.2021.1882350