Shortest Delay Routing Protocol for UAV Formation with Discrete Time Aggregation Graph

LI Bo; WANG Gaifang; YANG Hongjuan; RU Xuefei; ZHANG Jingchun; WANG Gang

doi:10.11999/JEIT230707

Volume 46 Issue 5

May 2024

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Article Navigation > Journal of Electronics & Information Technology > 2024 > 46(5): 1931-1939

LI Bo, WANG Gaifang, YANG Hongjuan, RU Xuefei, ZHANG Jingchun, WANG Gang. Shortest Delay Routing Protocol for UAV Formation with Discrete Time Aggregation Graph[J]. Journal of Electronics & Information Technology, 2024, 46(5): 1931-1939. doi: 10.11999/JEIT230707

Citation:

LI Bo, WANG Gaifang, YANG Hongjuan, RU Xuefei, ZHANG Jingchun, WANG Gang. Shortest Delay Routing Protocol for UAV Formation with Discrete Time Aggregation Graph[J]. Journal of Electronics & Information Technology, 2024, 46(5): 1931-1939. doi: 10.11999/JEIT230707

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Shortest Delay Routing Protocol for UAV Formation with Discrete Time Aggregation Graph

doi: 10.11999/JEIT230707

1.
School of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai 264209, China
2.
Communication Research Center, Harbin Institute of Technology, Harbin 150001, China

Funds: The National Natural Science Foundation of China (62171154, 61971156), The Natural Science Foundation of Shandong Province (ZR2020MF007), The Research Fund Program of Guangdong Key Laboratory of Aerospace Communication and Networking Technology (2018B030322004)

Received Date: 2023-07-15
Rev Recd Date: 2024-01-17

Available Online: 2024-01-25

Publish Date: 2024-05-30

Abstract

Abstract

Aiming at the problems that the traditional UAV formation routing algorithm cannot effectively utilize the advance predictability of topology changes, and the high cost is caused by acquiring the link connection by sending detection packets, a UAV formation shortest delay routing protocol based on discrete time aggregation graph is proposed by introducing the time-varying graph model. Firstly, using the prior knowledge of the UAV formation network, such as the movement trajectory of nodes and the network topology changes, the network link resources and network topology are characterized by using the discrete time aggregation graph. Secondly, the routing decision algorithm is designed based on the graph model. The delay in the process of route discovery is used as the link weight to solve the shortest delay route from the source node to the destination node of the network. Finally, the simulation performance shows that the routing protocol improves the packet delivery rate, reduces the end-to-end delay and diminishes the network control overhead compared with the traditional Ad-hoc On-Demand Distance Vector routing protocol.
- UAV ad hoc network,
- UAV formation,
- Time-varying graph model,
- Shortest delay route

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References(17)

References

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