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中文核心期刊

综合链路质量认知的水声传感网络路由优化方法

A comprehensive link quality cognitive routing protocol for underwater acoustic sensor networks

  • 摘要: 针对水声传感网络(UASN)在复杂多变海洋环境条件下网络路由适应性差, 导致网络性能起伏严重、鲁棒性低的问题, 通过不同层面、不同机制的环境认知进行链路质量评估及路由优化, 提出一种综合链路质量认知路由方法。首先, 定义了由莱斯因子、信噪比、节点负载等多维度参数组成的综合链路质量特征, 对变化海洋环境下的信号、信道、链路信息进行综合感知, 并通过结合多址接入交互与监听实现低开销链路质量评估; 在此基础上, 根据理想解相似排序法设计多属性优化机制进行UASN路由的认知优化。仿真及实际海洋环境下开展的水声传感网络试验结果表明, 所提方法可获得优于固定路由及常规认知路由方法的网络数据包投递率等网络指标, 验证了通过认知优化改善水声传感网络对海洋环境适应性的有效性。

     

    Abstract: In response to the poor adaptability of network routing in complex and dynamic marine environments for underwater acoustic sensor network (UASN), which leads to significant fluctuations in network performance and low robustness, a comprehensive link quality cognitive routing protocol (CLQ-CR) is proposed. This protocol evaluates link quality and optimizes routing through environmental cognition at different levels and mechanisms. Firstly, the comprehensive link quality factor, such as the K-factor, signal-to-noise ratio, and node load, is defined to comprehensively qualify the UASN link from the perspective of signal, channel, and link feature in the marine environment. Low-cost link quality assessment is achieved by combining multiple access contention and monitoring. Based on this, a multi-attribute optimization mechanism is designed using the technique for order preference by similarity to ideal solution (TOPSIS) for cognitive optimization of UASN routing. The simulation and experimental results of UASN conducted in practical shallow sea environment show that the proposed method can achieve better network performance indicators such as packet delivery rate than fixed routing and conventional cognitive routing methods, thus verifying the effectiveness of improving the adaptability of underwater acoustic sensing networks to marine environments through cognitive optimization.

     

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