Ant colony optimization based polymorphism-aware routing algorithm for AdHoc UAV network

被引:1
|
作者
Sun M. [1 ,2 ]
Zhou L. [1 ]
Yu Y. [1 ]
Gu J. [3 ]
机构
[1] Air and Missile Defense College, Air Force Engineering University, Xi'an
[2] Unit 93861 of the PLA, Xianyang
[3] Unit 32272 of the PLA, Lanzhou
关键词
AdHoc unmanned aerial vehicle (UAV) network; Ant colony algorithm; Congestion level of route; Dynamic source routing algorithm; Polymorphism-aware; Stability of route;
D O I
10.12305/j.issn.1001-506X.2021.09.24
中图分类号
学科分类号
摘要
AdHoc unmanned aerial vehicle (UAV) network is characterized for its high node mobility, fast changing network topology, high frequency of interchanging data and complex application environment. The performances of traditional routing algorithms are so bad over aspects such as transmitting delay, packet loss rate and routing overhead that they cannot provide efficient communication for multi-UAVs carrying out missions synergistically. To solve the problems, an ant colony optimization based polymorphism-aware routing (APAR) algorithm is proposed. This algorithm integrates ant colony optimization algorithm and dynamic source routing algorithm, and the level of pheromone in routes, which are gained in routing discovery process, is chosen as a standard to choose route and calculated by sensing the distance, the congestion level, and the stability of a route. A new volatilization mechanism of pheromone is also introduced to the algorithm. Meanwhile, the algorithm can make adjustment to the variance of UAV formation to prevent the compromise of the network performance. The simulation results show that compared with traditional algorithms the APAR algorithm improves the data packet transmission ratio, reduces the average end to end delay, reduces the routing overhead and has reliability in battlefield environment. © 2021, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码:2562 / 2572
页数:10
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