Abstract
Trajectory and caching optimisation design is a promising joint solution for enhancing the quality of services in unmanned aerial vehicle (UAV) assisted content delivery networks (CDNs). In this paper, we review the problem of which contents to cache in the UAV and which trajectory to fly, i.e., where to stop and how to gain the shortest path over the stops, under the constraints of caching storage and energy resources, namely storage- and energy-aware caching and trajectory optimisation (SECTO) problem. The SECTO problem in UAV-assisted CDNs is formulated and solved by applying genetic algorithms (GAs) to maximise the content delivery capacity while minimising the flying distance. The simulation results are shown to demonstrate the benefits of GAs in terms of accuracy and time complexity performance compared to other conventional solutions such as exhausted and greedy search algorithms.
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Lam, T.C., Vo, NS., Nguyen, TH., Phan, TM., Huynh, DT. (2023). Genetic Algorithms for Storage- and Energy-Aware Caching and Trajectory Optimisation Problem in UAV-Assisted Content Delivery Networks. In: Vo, NS., Tran, HA. (eds) Industrial Networks and Intelligent Systems. INISCOM 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 531. Springer, Cham. https://doi.org/10.1007/978-3-031-47359-3_3
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DOI: https://doi.org/10.1007/978-3-031-47359-3_3
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