High dynamic mobile topology-based clustering algorithm for UAV swarm networks

doi:10.23919/JSEE.2025.000090

Journal of Systems Engineering and Electronics ›› 2025, Vol. 36 ›› Issue (4): 1103-1112.doi: 10.23919/JSEE.2025.000090

• CONTROL THEORY AND APPLICATION • Previous Articles

High dynamic mobile topology-based clustering algorithm for UAV swarm networks

Siji CHEN¹^,²(), Bo JIANG¹^,²^,*(), Hong XU²^,³(), Tao PANG²(), Mingke GAO²()

¹ School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
² East-China Research Institute of Computer Technology, Shanghai 201800, China
³ School of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China

Received:2024-08-28 Online:2025-08-18 Published:2025-09-04
Contact: Bo JIANG E-mail:cqchensj@foxmail.com;b26jiang@126.com;frankxuh@126.com;t_pang@126.com;michaelgar@foxmail.com
About author:
CHEN Siji was born in 1993. He received his B.S. degree from Chongqing University of Posts and Telecommunications (CQUPT), Chongqing, China, in 2016, and M.S. degree in electronics and communication engineering with the School of Communication and Information Engineering, CQUPT, Chongqing, China, in 2019. He is currently pursuing his Ph.D. degree in computer science and technology, with the School of Computer Science and Technology, CQUPT, Chongqing, China. His main research interest is unmanned aerial vehicle (UAV) ad hoc network. E-mail: cqchensj@foxmail.com

JIANG Bo was born in 1968. He received his B.S. and M.S. degrees from Hangzhou Dianzi University, Hangzhou, China, in 1989 and 1992, respectively. He is currently a research fellow in East-China Research Institute of Computer Technology, Shanghai, China. He is the Director of National Trusted Embedded Software Engineering Technology Research Center, and a member of Standing Committee of Shanghai Association for Science and Technology. His research interests include cognitive radio, artificial intelligence, and cyberspace security. E-mail: b26jiang@126.com

XU Hong was born in 1990. He received his M.S. degree from the School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China. He is a Ph.D. candidate in School of Computer Science & Technology, Hangzhou Dianzi University. His research interests are computer software architecture, swarm robotics and image processing. E-mail: frankxuh@126.com

PANG Tao was born in 1984. He received his Ph.D. degree from Xidian University. Currently, he serves as a member of the Science and Technology Innovation and Talent Committee of East-China Research Institute of Computer Technology and the Director of the Intelligent Systems Research Center (ISRC). His research interest is intelligent computing. E-mail: t_pang@126.com

GAO Mingke was born in 1980. He received his Ph.D. degree from Shanghai University. He serves as the Director of the Laboratory of Architecture and Intelligence at the Intelligent Systems Research Center (ISRC) of East-China Research Institute of Computer Technology, and industry mentor for master’s students at Shanghai Jiao Tong University. His research interest is intelligent computing. E-mail: michaelgar@foxmail.com
Supported by:
This work was supported by the National Key Research and Development Program of China (2024YFB4504500) and Shanghai Collaborative Innovation Project(24xtcx00500).

Abstract

Abstract:

Unmanned aerial vehicles (UAVs) have become one of the key technologies to achieve future data collection due to their high mobility, rapid deployment, low cost, and the ability to establish line-of-sight communication links. However, when UAV swarm perform tasks in narrow spaces, they often encounter various spatial obstacles, building shielding materials, and high-speed node movements, which result in intermittent network communication links and cannot support the smooth completion of tasks. In this paper, a high mobility and dynamic topology of the UAV swarm is particularly considered and the high dynamic mobile topology-based clustering (HDMTC) algorithm is proposed. Simulation and real flight verification results verify that the proposed HDMTC algorithm achieves higher stability of network, longer link expiration time (LET), and longer node lifetime, all of which improve the communication performance for UAV swarm networks.

Key words: unmanned aerial vehichle (UAV) swarm network, UAV clustering, mobility, virtual tube

Siji CHEN, Bo JIANG, Hong XU, Tao PANG, Mingke GAO. High dynamic mobile topology-based clustering algorithm for UAV swarm networks[J]. Journal of Systems Engineering and Electronics, 2025, 36(4): 1103-1112.

Figures/Tables 14

Fig 1

Fig 2

Fig 3

Table 1

Fig 4

Fig 5

Fig 6

Fig 7

Fig 8

Fig 9

Fig 10

Fig 11

Fig 12

Fig 13

References 25

1	ARAGHIZADEH M A, TEYMOORI P, YAZDANI N, et al An efficient medium access control protocol for WSN-UAV. Ad Hoc Networks, 2016, 52, 146- 159. doi: 10.1016/j.adhoc.2016.09.007
2	NGUYEN M T, NGUYEN C V, DO H T, et al UAV-assisted data collection in wireless sensor networks: a comprehensive survey. Electronics, 2021, 10 (21): 2603. doi: 10.3390/electronics10212603
3	ZHU B, BEDEER E, NGUYEN H H, et al Joint cluster head selection and trajectory planning in UAV-aided IoT networks by reinforcement learning with sequential model. IEEE Internet of Things Journal, 2021, 9 (14): 12071- 12084.
4	CAMPION M, RANGANATHAN P, FARUQUE S UAV swarm communication and control architectures: a review. Journal of Unmanned Vehicle Systems, 2018, 7 (2): 93- 106.
5	NA Z, LI B, LIU X, et al UAV-based wide-area internet of things: an integrated deployment architecture. IEEE Network, 2021, 35 (5): 122- 128. doi: 10.1109/MNET.001.2100128
6	ISLAM N, RASHID M M, PASANDIDEH F, et al A review of applications and communication technologies for internet of things (IoT) and unmanned aerial vehicle (UAV) based sustainable smart farming. Sustainability, 2021, 13 (4): 1821.
7	WEI Z, ZHU M, ZHANG N, et al UAV-assisted data collection for internet of things: a survey. IEEE Internet of Things Journal, 2022, 9 (17): 15460- 15483. doi: 10.1109/JIOT.2022.3176903
8	JAVED S, HASSAN A, AHMAD R, et al State-of-the-art and future research challenges in UAV swarms. IEEE Internet of Things Journal, 2024, 11 (11): 19023- 19045. doi: 10.1109/JIOT.2024.3364230
9	QIN B Y, ZHANG D, TANG S, et al Two-layer formation-containment fault-tolerant control of fixed-wing UAV swarm for dynamic target tracking. Journal of Systems Engineering and Electronics, 2023, 34 (6): 1375- 1396. doi: 10.23919/JSEE.2023.000153
10	KE C X, CAI K Y, QUAN Q Analysis of a uniform passive fault-tolerant control method for multicopters. Journal of Systems Engineering and Electronics, 2024, 35 (6): 1574- 1582. doi: 10.23919/JSEE.2024.000127
11	LV S L, MAO P D, QUAN Q. Mean-field based time-optimal spatial iterative learning within the virtual tube. IEEE Control Systems Letters, 2024, 8: 2021−2026.
12	LV S L, GAO Y, CHE J X, et al. Autonomous drone racing: time-optimal spatial iterative learning control within a virtual tube. Proc. of the IEEE International Conference on Robotics and Automation, 2023: 3197−3203.
13	QUAN Q, FU R, LI M X, et al Practical distributed control for VTOL UAVS to pass a virtual tube. IEEE Trans. on Intelligent Vehicles, 2021, 7 (2): 342- 353.
14	MAO P D, FU R L, QUAN Q Optimal virtual tube planning and control for swarm robotics. The International Journal of Robotics Research, 2024, 43 (5): 602- 627. doi: 10.1177/02783649231210012
15	MAO P D, QUAN Q. Making robotics swarm flow more smoothly: a regular virtual tube model. Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022: 4498−4504.
16	SUO W B, WANG M Y, ZHANG D, et al Formation control technology of fixed-wing UAV swarm based on distributed ad hoc network. Applied Sciences, 2022, 12 (2): 535. doi: 10.3390/app12020535
17	XIA X W, YAN Y H, LI Z J, et al. A survey of UAV clustering algorithm. Proc. of the 24th International Conference on Advanced Communication Technology, 2022: 191−196.
18	SUN G Y, QIN D Y, LAN T T, et al Research on clustering routing protocol based on improved PSO in FANET. IEEE Sensors Journal, 2021, 21 (23): 27168- 27185. doi: 10.1109/JSEN.2021.3117496
19	GERLA M, TZU-CHIEH TSAI J Multicluster, mobile, multimedia radio network. Wireless Networks, 1995, 1 (3): 255- 265. doi: 10.1007/BF01200845
20	PAREKH A K. Selecting routers in ad-hoc wireless networks. Proc. of the SBT/IEEE International Telecommunications, 1994: 420−424.
21	CHATTERJEE M, DAS S K, TURGUT D. An on-demand weighted clustering algorithm (WCA) for ad hoc networks. Proc. of the Global Telecommunications Conference, 2000: 1697−1701.
22	AISSA M, ABDELHAFIDH M, MNAOUER A B EMASS: a novel energy, safety and mobility aware-based clustering algorithm for fanets. IEEE Access, 2021, 9, 105506- 105520. doi: 10.1109/ACCESS.2021.3097323
23	GUO J J, GAO H M, LIU Z Q, et al. ICRA: an intelligent clustering routing approach for UAV ad hoc networks. IEEE Trans. on Intelligent Transportation Systems, 2022, 24(2): 2447−2460.
24	CHEN S J, JIANG B, PANG T, et al Firefly swarm intelligence based cooperative localization and automatic clustering for indoor FANETS. PloS One, 2023, 18 (3): e0282333. doi: 10.1371/journal.pone.0282333
25	LIU D X, XU Y T, SHEN L, et al Self-organizing multiuser matching in cellular networks: a score-based mutually beneficial approach. IET Communications, 2016, 10 (15): 1928- 1937. doi: 10.1049/iet-com.2016.0129

Parameter	Value
Area size/m	10×10
Number of UAVs	40
Communication range/m	3
Speed/(m/s)	1−4
Initial energy E/J	20
Hello message period T/s	0.1
Number of obstacles	5

[1]	Yan GAO, Chenggang BAI, Quan QUAN. A survey on passing-through control of multi-robot systems in cluttered environments [J]. Journal of Systems Engineering and Electronics, 2025, 36(4): 1037-1056.
[2]	Delong WU, Hao FANG, Yiren HAO, Aobo WANG. Outdoor navigation of millimeter-wave radar quadrotors based on optimal virtual tube [J]. Journal of Systems Engineering and Electronics, 2025, 36(4): 1057-1067.
[3]	Jiacheng TANG, Zixiao YANG, Lei ZHANG, Tianjiang HU, Bo ZHU. Regular virtual tube for cooperative transportation of a payload by multiple quadrotors [J]. Journal of Systems Engineering and Electronics, 2025, 36(4): 1068-1076.
[4]	Yangjie LYU, Yan GAO, Guoyuan QI. Multicopter interception control based on visual servo and virtual tube in a cluttered environment [J]. Journal of Systems Engineering and Electronics, 2025, 36(4): 1094-1102.
[5]	Yu Ziyue, Gong Bo & He Xingui. Virtual reality mobility model for wireless ad hoc networks [J]. Journal of Systems Engineering and Electronics, 2008, 19(4): 819-826.

High dynamic mobile topology-based clustering algorithm for UAV swarm networks

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

Share this article

Figures/Tables 14

References 25

Related Articles 5

Recommended Articles

Metrics

Comments