国家自然科学基金(61571328); 天津市自然科学基金(18JCZDJC96800); 天津市重大科技专项(17YFZCGX00360)
针对在实际环境下无线传感器网络出现随机丢包、能量消耗快的问题, 结合传感器网络的特点和压缩感知的优势设计了一个边缘计算场景下的可靠的数据收集方法, 首先对网络进行分簇, 在数据采集阶段设计基于实际链路状态的测量矩阵并构造适合该传感器数据的稀疏基, 在数据传输阶段即从簇头传输到汇聚节点, 采取最优最差蚁群算法对链路质量进行评估, 然后进行基于链路质量的多路径传输, 最后将数据重构任务卸载到边缘节点执行.实验结果证明所提数据收集方法与其他方法对比, 在链路出现随机丢包的情况下, 数据传输的可靠性与网络的能耗都表现出较好的效果.
Aiming at the problem of random packet loss and fast energy consumption in actual wireless sensor networks, a reliable collection method is designed based on the characteristics of sensor network and the advantages of compressed sensing. Firstly, the network is clustered. In the data acquisition phase, the measurement matrix based on the actual link state is designed and sparse base suitable for the sensor data is constructed. In the data transmission phase, the data is transmitted from the cluster head to the aggregation node. The best-worst ant system is adopted to evaluate the link quality. Then, the multi-path transmission based on the link quality is carried out. Finally, the data reconstruction task is unloaded to the edge node Implementation. The experimental results show that in the sceanario of random packet loss in the network, the data collection method proposed in this study, compared with other methods, the reliability of data transmission and energy consumption of the network show better results.