What question did this study set out to answer?

To develop an efficient and flexible network framework and flow-scheduling mechanism for cooperative multi-task unmanned aerial vehicle (UAV) networks.

June 10, 2020Chinese Journal of AeronauticsOpen Access

An aggregate flow based scheduler in multi-task cooperated UAVs network

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Authors

XLXiaohuan LiShandong University of Technology ZXZiqi Xie YJYe JinBeijing Tongren Hospital

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Implication

Network simulation study demonstrates improved task completion rates in cooperative drone networks using flow aggregation, indicating enhanced scheduling efficiency for complex aerial missions.

Key Points

To develop an efficient and flexible network framework and flow-scheduling mechanism for cooperative multi-task unmanned aerial vehicle (UAV) networks.
Designed a three-layer network architecture composed of a core layer, an aggregation layer, and an execution layer for multi-task distribution and transmission.
Formulated an Aggregate Flow (AGFlow) scheduler that groups individual flows by task and dynamically assigns transmission priority according to calculated urgency levels.
Evaluated scheduling performance via network simulations compared against state-of-the-art UAV schedulers.
The AGFlow-based scheduler increased the average task completion rate by 0.278 compared to the state-of-the-art scheduler.

Cite This Study

Li et al. (2020) studied this question.

synapsesocial.com/papers/6a86f3f93f44447e627cba87 https://doi.org/10.1016/j.cja.2020.03.029

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Implication

Network simulation study demonstrates improved task completion rates in cooperative drone networks using flow aggregation, indicating enhanced scheduling efficiency for complex aerial missions.

An aggregate flow based scheduler in multi-task cooperated UAVs network

Discussion

Member takes

Implication

Key Points

Cite This Study

An aggregate flow based scheduler in multi-task cooperated UAVs network

Discussion

Member takes

Implication

Key Points

Cite This Study

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