ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Real-time task scheduling algorithm for FANET considering communication topology control
Received date: 2025-07-31
Revised date: 2025-09-11
Accepted date: 2025-10-23
Online published: 2025-10-30
Supported by
National Natural Science Foundation of China(62373201);Technology Research and Development Program of Tianjin(18ZXZNGX00340)
The multiple Unmanned Aerial Vehicle （UAV） Flying Ad hoc Network （FANET）， with its enhanced situational awareness and environmental adaptability， can effectively ensure real-time ground task search， allocation， and execution in applications requiring immediate monitoring. Given these application scenarios and task requirements， the key issue of collaborative optimization of real-time task scheduling and dynamic topology control during autonomous allocation in FANET is addressed： the real-time task scheduling ensures the timeliness requirements of monitoring tasks， and the dynamic topology control ensures the stable transmission of tasks and location data. Firstly， a joint optimization framework integrating auction mechanism and topology control based on dynamic value assessment is constructed. Secondly， through the introduction of a dynamic task value assessment model， dynamic task priority ranking and allocation are realized， and a topology control strategy based on minimum maintenance cost is designed. The cost of topology adjustment is reduced via a selective link maintenance mechanism. Finally， the complexity analysis demonstrates that the proposed algorithm can meet the requirements for efficient solution and real-time optimization in dynamic scenarios. The significant advantages of the proposed algorithm in terms of task response speed and topology stability are demonstrated through simulation experiments. This work provides both theoretical support and technical references for engineering scenarios requiring immediate response and precise monitoring.
Peizhao WANG , Ming HE , Haihua CHEN , Hongpeng WANG . Real-time task scheduling algorithm for FANET considering communication topology control[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2026 , 47(6) : 332636 -332636 . DOI: 10.7527/S1000-6893.2025.32636
| [1] | UMAIR M， JOUNG J， CHO Y S. Transmission power and altitude design for energy-efficient mission completion of small-size unmanned aerial vehicle［J］. Electronics Letters， 2020， 56（22）： 1219-1222. |
| [2] | 聂伟， 戴琪霏， 杨小龙， 等. 基于多维信号特征的无人机探测识别方法［J］. 电子与信息学报， 2024， 46（3）： 1089-1099. |
| NIE W， DAI Q F， YANG X L， et al. Unmanned aerial vehicle detection and recognition method based on multi-dimensional signal feature［J］. Journal of Electronics & Information Technology， 2024， 46（3）： 1089-1099 （in Chinese）. | |
| [3] | ALAYA H， LETAIFA A BEN， RACHEDI A. State of the art and taxonomy survey on federated learning and blockchain integration in UAV applications［J］. The Journal of Supercomputing， 2025， 81（5）： 655. |
| [4] | SONG Z Q， FANG W. Research on scheduling problem for persistent servive of multiple unmanned aerial vehicles［C］∥2017 36th Chinese Control Conference （CCC）. Piscataway： IEEE Press， 2017： 2941-2944. |
| [5] | FAN B Y， BO Y M， WU X. Learning improvement heuristics for multi-unmanned aerial vehicle task allocation［J］. Drones， 2024， 8（11）： 636. |
| [6] | 高云飞， 胡钰林， 刘鸣柳， 等. 多无人机输电线路巡检联合轨迹设计方法［J］. 电子与信息学报， 2024， 46（5）： 1958-1967. |
| GAO Y F， HU Y L， LIU M L， et al. Joint multi-UAV trajectory design for power line inspection［J］. Journal of Electronics & Information Technology， 2024， 46（5）： 1958-1967 （in Chinese）. | |
| [7] | WU Y， XU S T， DAI W， et al. Heuristic position allocation methods for forming multiple UAV formations［J］. Engineering Applications of Artificial Intelligence， 2023， 118： 105654. |
| [8] | WU Y， LIANG T J， GOU J Z， et al. Heterogeneous mission planning for multiple UAV formations via metaheuristic algorithms［J］. IEEE Transactions on Aerospace and Electronic Systems， 2023， 59（4）： 3924-3940. |
| [9] | YUE W， ZHANG X Y， LIU Z C. Distributed cooperative task allocation for heterogeneous UAV swarms under complex constraints［J］. Computer Communications， 2025， 231： 108043. |
| [10] | LU Q W， QIU Y F， GUAN C T， et al. Coordinated multi-UAV reconnaissance scheme for multiple targets［J］. Applied Sciences， 2023， 13（19）： 10920. |
| [11] | LI Y B， ZHANG Z T， HE Z Y， et al. A heuristic task allocation method based on overlapping coalition formation game for heterogeneous UAVs［J］. IEEE Internet of Things Journal， 2024， 11（17）： 28945-28959. |
| [12] | 王政， 王华， 崔可可， 等. 局部引导强化学习的舰载机自主调运方法［J］. 航空学报， 2025， 46（13）： 531333. |
| WANG Z， WANG H， CUI K K， et al. Locally guided reinforcement learning for autonomous dispatching of carrier-based aircraft［J］. Acta Aeronautica et Astronautica Sinica， 2025， 46（13）： 531333 （in Chinese）. | |
| [13] | 陆音， 刘金志， 张珉. 一种模型辅助的联邦强化学习多无人机路径规划方法［J］. 电子与信息学报， 2025， 47（5）： 1368-1380. |
| LU Y， LIU J Z， ZHANG M. A model-assisted federated reinforcement learning method for multi-UAV path planning［J］. Journal of Electronics & Information Technology， 2025， 47（5）： 1368-1380 （in Chinese）. | |
| [14] | ZHANG X， ZHANG X. A binary artificial bee colony algorithm for constructing spanning trees in vehicular ad hoc networks［J］. Ad Hoc Networks， 2017， 58： 198-204. |
| [15] | ALAMERI I， KOMARKOVA J， AL-HADHRAMI T， et al. Optimizing connections： applied shortest path algorithms for MANETs［J］. CMES-Computer Modeling in Engineering and Sciences， 2024， 141（1）： 787-807. |
| [16] | XIE G Q， ZHONG B W， XU H R， et al. Connectivity-preserving rendezvous in discrete-time multi-agent systems via relative neighborhood proximity graph［J］. Transactions of the Institute of Measurement and Control， 2024， 46（4）： 771-784. |
| [17] | KHAN S A， MAHMOOD A. Fuzzy goal programming-based ant colony optimization algorithm for multi-objective topology design of distributed local area networks［J］. Neural Computing and Applications， 2019， 31（7）： 2329-2347. |
| [18] | HOLLY S， NIE?E A. Dynamic communication topologies for distributed heuristics in energy system optimization algorithms［C］∥2021 16th Conference on Computer Science and Intelligence Systems （FedCSIS）. Piscataway： IEEE Press， 2021： 191-200. |
| [19] | LIN A P， SUN W， YU H S， et al. Global genetic learning particle swarm optimization with diversity enhancement by ring topology［J］. Swarm and Evolutionary Computation， 2019， 44： 571-583. |
| [20] | PARK S， KIM H T， KIM H. Energy-efficient topology control for UAV networks［J］. Energies， 2019， 12（23）： 4523. |
| [21] | WANG P Y， LI Q K， YI J K. Topology control of low-connection UAV laser network with virtual nodes［J］. Applied Sciences， 2025， 15（3）： 1086. |
| [22] | ALAM M M， MOH S. Joint topology control and routing in a UAV swarm for crowd surveillance［J］. Journal of Network and Computer Applications， 2022， 204： 103427. |
| [23] | XU L， CAO X B， DU W B， et al. Cooperative path planning optimization for multiple UAVs with communication constraints［J］. Knowledge-Based Systems， 2023， 260： 110164. |
| [24] | GUO J， GAN M G， HU K. Cooperative path planning for multi-UAVs with time-varying communication and energy consumption constraints［J］. Drones， 2024， 8（11）： 654. |
| [25] | CHEN L， LIU G R， ZHU X， et al. A heuristic routing algorithm for heterogeneous UAVs in time-constrained MEC systems［J］. Drones， 2024， 8（8）： 379. |
| [26] | 王鸿鹏， 王前， 张晓阳， 等. 基于3D-Tabu禁忌搜索的广域环境MESH网络节点部署优化算法研究［J］. 传感技术学报， 2021， 34（2）： 261-267. |
| WANG H P， WANG Q， ZHANG X Y， et al. Research on the optimization of node deployment in wide-area MESH networks using 3D-Tabu search［J］. Chinese Journal of Sensors and Actuators， 2021， 34（2）： 261-267 （in Chinese）. | |
| [27] | WANG Y， LI W Z， JIANG R. A novel hybrid algorithm based on improved particle swarm optimization algorithm and genetic algorithm for multi-UAV path planning with time windows［C］∥2022 IEEE 5th Advanced Information Management， Communicates， Electronic and Automation Control Conference （IMCEC）. Piscataway： IEEE Press， 2022： 1005-1009. |
| [28] | 王祝， 张梦通， 张振鹏， 等. 基于多指标动态优先级的无人机协同路径规划［J］. 航空学报， 2024， 45（4）： 328816. |
| WANG Z， ZHANG M T， ZHANG Z P， et al. Multi-UAV cooperative path planning based on multi-index dynamic priority［J］. Acta Aeronautica et Astronautica Sinica， 2024， 45（4）： 328816 （in Chinese）. | |
| [29] | GOTO T， NAJAFABADI H R， FALHEIRO M， et al. Topological optimization and simulated annealing［J］. IFAC-PapersOnLine， 2021， 54（1）： 205-210. |
| [30] | 王法俊， 李喆， 陆浩然. 基于复杂网络理论的战术通信网络拓扑构建方法［C］∥第十三届中国指挥控制大会论文集（下册）. 北京： 中国指挥与控制学会， 2025： 513-518. |
| WANG F J， LI Z， LU H R. Topology construction methods for tactical communication networks based on complex network theory［C］∥Proceedings of the 13th China Conference on Command and Control （Vol 2）. Beijing：Chinese Institute of Command and Control， 2025： 513-518 （in Chinese）. |
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