Research Article
Genetic Algorithms for Storage- and Energy-Aware Caching and Trajectory Optimisation Problem in UAV-Assisted Content Delivery Networks
@INPROCEEDINGS{10.1007/978-3-031-47359-3_3, author={Thuong C. Lam and Nguyen-Son Vo and Thanh-Hieu Nguyen and Thanh-Minh Phan and De-Thu Huynh}, title={Genetic Algorithms for Storage- and Energy-Aware Caching and Trajectory Optimisation Problem in UAV-Assisted Content Delivery Networks}, proceedings={Industrial Networks and Intelligent Systems. 9th EAI International Conference, INISCOM 2023, Ho Chi Minh City, Vietnam, August 2-3, 2023, Proceedings}, proceedings_a={INISCOM}, year={2023}, month={10}, keywords={Content delivery network Genetic algorithm travelling salesman problem UAV caching UAV trajectory}, doi={10.1007/978-3-031-47359-3_3} }- Thuong C. Lam
Nguyen-Son Vo
Thanh-Hieu Nguyen
Thanh-Minh Phan
De-Thu Huynh
Year: 2023
Genetic Algorithms for Storage- and Energy-Aware Caching and Trajectory Optimisation Problem in UAV-Assisted Content Delivery Networks
INISCOM
Springer
DOI: 10.1007/978-3-031-47359-3_3
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.
