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Optimal Data Collection of MP-MR-MC Wireless Sensors Network for Structural Monitoring

机译:用于结构监测的MP-MR-MC无线传感器网络的最佳数据收集

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Structural health monitoring (SHM) is a kind of data-intensive applications for wireless sensors networks, which usually requires high network bandwidth. However, the bandwidth of traditional single-radio single-channel (SR-SC) WSN is quite limited. In order to meet the requirement of structural monitoring, multi-radio multi-channel (MR-MC) WSN is emerging. In this paper, we address the optimal data collection problem in MR-MC WSN by modelling it as an integer linear programming problem. Combining the advantages of the particle swarm optimization (PSO) algorithm and flower pollination optimization (FPA) algorithm, we propose a new hybrid algorithm BFPA-PSO to solve the optimization problem under the constraint of time slot and multi-power multi-radio multi-channel (MP-MR-MC). Theoretical analysis and simulation experiments are carried out and the results show that the proposed method has good performance in improving network capacity as well as reducing energy consumption.
机译:结构健康监控(SHM)是一种用于无线传感器网络的数据密集型应用程序,通常需要高网络带宽。但是,传统的单无线电单信道(SR-SC)WSN的带宽非常有限。为了满足结构监视的要求,出现了多无线电多信道(MR-MC)WSN。在本文中,我们通过将其建模为整数线性规划问题来解决MR-MC WSN中的最佳数据收集问题。结合粒子群算法(PSO)和花粉授粉算法(FPA)的优势,提出了一种新的混合算法BFPA-PSO,以解决时隙和多功率多无线电多信道约束下的优化问题。通道(MP-MR-MC)。进行了理论分析和仿真实验,结果表明该方法在提高网络容量和降低能耗方面具有良好的性能。

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