基于神经网络的无人机云服务质量控制方法研究
A Network Control-based QoS-enhanced MAC for UAV Cloud
查看参考文献19篇
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文摘
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无人机云通过动态卸载任务到云端进行高效处理,能够极大地提高无人机的智能水平。由于设计理念、任务环境、突发事件等因素,导致卸载的任务对网络服务质量(QoS)需求不尽相同。从控制角度研究无人机云系统的网络传输QoS控制问题,提出并实现了一种基于BP神经网络的双闭环接入控制方法,在最大化能量利用率的同时,实现绝对QoS和相对QoS保证。硬件实验结果表明,该方法不仅能够在任务动态变化时提供相对QoS和绝对QoS保证,并且在网络高负载下具有更高的吞吐量和能量利用率,在网络低负载下具有更低的能耗。 |
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其他语种文摘
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Unmanned aerial vehicle (UAV) cloud can greatly enhance the intelligence of unmanned system by dynamically uploading the compute-intensive applications to the cloud. The different UAV missions may have different quality of service (QoS) requirements due to the uncertainty of UAV missions and the fast-changing battlefield environment. A BP neuron network-based feedback differentiated control approach for QoS-aware (BPFD)-MAC in UAV cloud is proposed, which can support both absolute and relative QoS guarantees with the consideration of energy saving. The hardware experiments demonstrate the feasibility of BPFD-MAC. Under heavy loads, BPFD has better throughput and power use efficiency; and under light load, BPFD has lower total energy consumption. |
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来源
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兵工学报
,2018,39(9):1762-1771 【核心库】
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DOI
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10.3969/j.issn.1000-1093.2018.09.013
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关键词
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无人机云
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服务质量
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接入控制
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神经网络
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地址
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1.
西北工业大学电子信息学院, 陕西, 西安, 710072
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物联网技术及应用国家地方联合工程实验室, 物联网技术及应用国家地方联合工程实验室, 陕西, 西安, 710072
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长安大学电子与控制工程学院, 陕西, 西安, 710064
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语种
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中文 |
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文献类型
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研究性论文 |
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ISSN
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1000-1093 |
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学科
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航空 |
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基金
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中国博士后科学基金
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陕西省重点研发计划项目
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上海航天科技创新基金
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中央高校基础研究基金项目
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陕西省西安市科技计划项目
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文献收藏号
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CSCD:6371479
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