Novel Computation and Communication Resources Allocation Using Relay Communications in UAV-Mounted Cloudlet Systems

• Published in: IEEE transactions on network science and engineering Vol. 8; no. 4; pp. 3140 - 3151
• Main Authors: Shimada, Hayato, Kawamoto, Yuichi, Kato, Nei
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01-10-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cloud computing; Communication; Complex systems; Control methods; Data processing; Delay; Delays; Edge computing; Internet of Things; Load balancing; Mathematical model; Mobile computing; mobile edge computing; Relay; relay communication; Relays; Resource allocation; Servers; unmanned aerial vehicle; Unmanned aerial vehicles; Workload; Workloads
• ISSN: 2327-4697; 2334-329X
• DOI: 10.1109/TNSE.2021.3105455

At present, the Internet of things (IoT) is widely employed in various systems. The operation of these systems requires intelligent data processing, which needs to be performed rapidly at the network edge. Hence, studies on mobile edge computing (MEC) have been increasingly conducted in recent years. In MEC, edge servers perform data processing to reduce service delay. To meet the demand for computational and communication resources in infrastructureless areas or during large-scale disasters, the use of unmanned aerial vehicles (UAVs) in providing computational resources has attracted considerable attention. However, in MEC using UAVs, it is necessary to consider the workload balance and communication range of vehicles used. In this study, we highlight problems associated with such systems from a new perspective. Furthermore, we propose a relay control method equalizing the workload balance between UAVs and reducing network delay. We modeled the proposed method as a complex system, mathematically formulating each delay element. Additionally, experimental results highlight the effectiveness of the proposed method in various environments. The reduction in delay considerably improved the feasibility of the system. This study is expected to help achieve a significant advancement in MEC using UAVs by establishing a foundation for further research.