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

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Abstract

Ad hoc UAV network is characterized for its high node mobility, fast changing network topology, high frequency of interchanging data and complex application environment. The performance of traditional routing algorithms are so poor over aspects such as end to end delay, data packet delivery ratio and routing overhead that they cannot provide efficient communication for multi-UAVs carrying out missions synergistically. An ant colony optimization based polymorphism-aware routing algorithm– APAR algorithm is proposed to solve the problems. This algorithm integrates ACO algorithm and dynamic source routing algorithm, 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 of a route, the congestion level of a route, 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 the APAR algorithm has superiority over traditional algorithms in data package delivery ratio, end to end delay, routing overhead and it is dependable in battlefield environment.

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Authors and Affiliations

  1. Aeronautics and Astronautics Engineering College, Air Force Engineering University, Xi’an, 710038, China

    Yunlong Yu, Le Ru, Wensheng Chi, Yaqing Liu, Qiangqiang Yu & Kun Fang

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  1. Yunlong Yu
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  2. Le Ru
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  3. Wensheng Chi
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  4. Yaqing Liu
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  5. Qiangqiang Yu
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  6. Kun Fang
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Correspondence to Yunlong Yu.

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Yu, Y., Ru, L., Chi, W. et al. Ant colony optimization based polymorphism-aware routing algorithm for ad hoc UAV network. Multimed Tools Appl 75, 14451–14476 (2016). https://doi.org/10.1007/s11042-015-3240-y

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