Survey of Promising Technologies for Quantum Drones and Networks

Kumar, Adarsh; Bhatia, Surbhi; Kaushik, Keshav; Gandhi, S. Manjula; Devi, S. Renuga; Pacheco, Diego Augusto de Jesus; Mashat, Arwa

doi:10.1109/access.2021.3109816

Cited by 37 publications

(17 citation statements)

References 185 publications

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“…Recently, quantum drones has emerged as an interesting technology that can enhance the performance of real-time applications. It integrates quantum sensors, radars, and other quantum devices within the system [51]. In addition, quantum drones employ techniques such as quantum machine learning, quantum genetic systems, and secure quantum cryptography.…”

Section: A Drl For Internet Of Quantum Dronesmentioning

confidence: 99%

Deep Reinforcement Learning for Internet of Drones Networks: Issues and Research Directions

Aboueleneen

Alwarafy

Abdallah

2023

IEEE Open J. Commun. Soc.

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Internet of Drones (IoD) is one of the promising technologies to enhance the performance of wireless networks. Deploying IoD to assist wireless networks, however, needs to address various design issues. Due to the highly dynamic nature of IoD networks, conventional methods are expected to encounter inadequacies that can be resolved using emerging deep reinforcement learning (DRL) techniques. In this paper, we discuss the application of DRL for addressing various issues in IoD networks. We first overview the main features, types, applications, and services of IoD networks. Then, we briefly discuss some DRL algorithms used to address the issues and challenges of IoD networks. After that, we explain the most crucial issues in IoD networks and discuss some papers that show how DRL can address them. Finally, we provide insights into some promising research directions in the context of using DRL in IoD networks.

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Section: A Drl For Internet Of Quantum Dronesmentioning

confidence: 99%

Deep Reinforcement Learning for Internet of Drones Networks: Issues and Research Directions

Aboueleneen

Alwarafy

Abdallah

2023

IEEE Open J. Commun. Soc.

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“…x 2018 Abdulkareem et al [33] x x 2019 Gill et al [19] x x 2019 Massimo et al [34] x x 2020 Li et al [36] x x 2020 Kumar el al. [35] x x 2021 Hassan et al [37] x…”

Section: Benefits Of Ai/ml-integrated Next Generation Computingmentioning

confidence: 99%

“…The surveys from Kumar el al. [35] and Li et al [36] highlighted the potential role of AI in quantum computing. The suitability of AI for serverless computing is described in Hassan et al [37].…”

Section: Related Surveys and Our Contributionsmentioning

confidence: 99%

AI for Next Generation Computing: Emerging Trends and Future Directions

Gill,

Xu,

Ottaviani

et al. 2022

Preprint

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Autonomic computing investigates how systems can achieve (user) specified "control" outcomes on their own, without the intervention of a human operator. Autonomic computing fundamentals have been substantially influenced by those of control theory for closed and open-loop systems. In practice, complex systems may exhibit a number of concurrent and inter-dependent control loops. Despite research into autonomic models for managing computer resources, ranging from individual resources (e.g., web servers) to a resource ensemble (e.g., multiple resources within a data center), research into integrating Artificial Intelligence (AI) and Machine Learning (ML) to improve resource autonomy and performance at scale continues to be a fundamental challenge. The integration of AI/ML to achieve such autonomic and self-management of systems can be achieved at different levels of granularity, from full to human-in-the-loop automation. In this article, leading academics, researchers, practitioners, engineers, and scientists in the fields of cloud computing, AI/ML, and quantum computing join to discuss current research and potential future directions for these fields. Further, we discuss challenges and opportunities for leveraging AI and ML in next generation computing for emerging computing paradigms, including cloud, fog, edge, serverless and quantum computing environments.

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“…At present, quantum secure communication has been successfully applied to optical fibre communication [3,4] and satellite optical communication [5,6]. Several works on drone-based quantum networks have been published [7][8][9].…”

Section: Introductionmentioning

confidence: 99%

A Lower Size, Weight Acquisition and Tracking System for Airborne Quantum Communication

Shen

Dai

et al. 2022

IEEE Photonics J.

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The features of unmanned aerial vehicles (UAVs), such as strong manoeuvrability, small size, and light weight, make them considered to participate in free space optical (FSO) quantum communication, becoming an important part of the Space-Air-Ground Integrated Network. However, research reports on small-sized drones based long-range optical quantum link are few. A major challenge is that traditional opto-mechanical structure is difficult to adapt to small UAV platforms. Here, a lower size, weight, and power (SWaP) acquisition and tracking system prototype is developed, and its greatest advantage is that the system can be easily integrated into small flying platforms and quickly build a long-distance quantum communication link. The prototype weighs less than 8 kg. A small-sized two-axis mirror mechanism is designed for wide-range acquisition and tracking. Moreover, the system can automatically point to ground station. The SWaP acquisition and tracking system can support quantum key distribution (QKD) link and general FSO link by drones. In the 7 km air-to-ground demonstration, the acquisition and tracking system prototype is tested in practice, which is suspended under the small six-rotor UAV platform, and a special passive vibration isolation unit is added in between. A ten-minute continuous and stable beacon tracking proves that the system can quickly and automatically align.

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Survey of Promising Technologies for Quantum Drones and Networks

Cited by 37 publications

References 185 publications

Deep Reinforcement Learning for Internet of Drones Networks: Issues and Research Directions

Deep Reinforcement Learning for Internet of Drones Networks: Issues and Research Directions

AI for Next Generation Computing: Emerging Trends and Future Directions

A Lower Size, Weight Acquisition and Tracking System for Airborne Quantum Communication

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