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基于移动预测的集群组网分簇路由协议
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TP393

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陕西省重点研究计划


Clustering Routing Protocol for Cluster Networks Based on Mobile Prediction
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    摘要:

    针对无人机集群组网中拓扑结构更新快、网络通信效率低的问题,提出了基于移动预测的分簇算法MPC,并提出了一种分簇路由协议MPC-R。灰色WNN联合预测模型的基础上,通过将预测结果运用在方向、速度、位置评价因子上,得出移动状态评价因子。综合计算移动因子和链路保持时间进行簇头选择,路由协议簇间采用被动路由发现机制,簇内采用主动路由发现机制。通过仿真,对预测准确性、分簇算法、路由协议进行验证,结果表明:WNN提高了预测的准确性,分组投递率提高了3%~4%。该分簇算法延长了簇头持续时间和平均链路保持时间,能够提高分簇稳定性。相应的路由协议与其他同类协议相比降低了端到端时延,提高了数据包分组投递率和路由性能。

    Abstract:

    Aimed at the problem that topology updating is fast in construction and network communication is low in efficiency in drone cluster networking, a clustering algorithm MPC based on mobile prediction is proposed. On the basis of this, a new clustering routing protocol MPCR is proposed. At the base of the grayWNN joint forecasting model, the mobile state movement factor is obtained by applying the prediction results to the direction, speed, and position evaluation factors. The clustering algorithm selects cluster heads by calculating the mobility factor and link retention time comprehensively. Passive routing discovery mechanism between clusters and active routing discovery mechanism between cluster members are used by the routing protocol for decreasing routing overhead. This paper verifies the prediction accuracy, the clustering algorithm, and the routing protocol through the simulation. The results shows that WNN improves forecast accuracy and packet delivery rate by 3 to 4 percentage points. And the clustering algorithm extends the cluster head holding time and the average link holding time, improving the clustering stability. The corresponding routing protocol reduces the endtoend delay, compared with other same protocols, and increases packet delivery ratio of packets, improving the routing performance.

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王沁飞,南建国,黄金科,张红梅,贾旭峰.基于移动预测的集群组网分簇路由协议[J].空军工程大学学报,2018,19(6):90-96

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  • 在线发布日期: 2018-12-28
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