基于小世界概念的无人机无线传感器网络优化

Ruirui Zhang, Li Guo, Chao Dong
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引用次数: 1

摘要

随着5G网络的融合,由多个同质传感器组成的无线传感器网络(WSNs)越来越受到人们的关注。然而,这种网络在数据传输过程中存在明显的延迟。通过利用小世界特性,结合无人机的灵活性,可以减少延迟。本文主要研究如何部署无人机和设计无人机辅助的小世界无线传感器网络。首先,提出了一种基于路由跳数的区域划分方法,确定每架无人机的目标区域;其次,采用空对地通道模型确定无人机的最优高度,并将无人机的最优水平位置表述为一个依赖于传感器分布的混合整数非线性规划问题;最后,介绍了一种分析数据传输流程,在无人机与传感器节点之间创建快捷方式的算法。仿真结果充分验证了该方案的有效性和高效性,与传统的无线传感器网络相比,不仅降低了数据传输延迟,而且实现了较高的吞吐量。最优部署方案的平均性能优于随机部署方案。
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Optimization of Wireless Sensor Network by Applying Small World Concept with UAVs
Wireless Sensor Networks (WSNs) composed of many homogeneous sensors have attracted more attention especially with the integration of 5G networks. However, this kind of network suffers from significant latency during data transmission. Latency can be reduced by capitalizing on the Small World characteristic, in combination with the flexibility of Unmanned Aerial Vehicles (UAVs). The main work of interest of this paper is how to deploy UAVs and design UAV-assisted Small World WSNs. Firstly, we propose a region partition method based on routing hops to determine the target area for each UAV. Next, the Air-to-Ground channel model is adopted to determine the optimal altitude of UAVs, and the optimal horizontal location of UAVs formulated as a Mixed-Integer Nonlinear Programming problem which depends on the sensors distribution is put forward. Finally, an algorithm which analyzes the data transmission flow to create shortcuts between UAVs and sensor nodes is introduced.The simulation results fully validate the effectiveness and efficiency of the proposed scheme which not only reduces the data transmission delay but also attains high throughput compared with the traditional WSN. Furthermore, the optimal deployment scheme outperforms the random deployment on average.
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