Abstract

Aiming at the complexity of the underwater wireless sensor network and the characteristics of high temporal correlation of the data that continuously sensed by nodes, an optimization method of underwater data prediction based on exponential smoothing (ESDP) is proposed to improve the life cycle of the whole network. In this method, LEACH protocol is used to cluster the whole nodes and elect some cluster heads. Then a routing tree is constructed between the cluster heads to communicate with the water surface sink node. Finally, the optimized exponential smoothing method is used to establish the prediction model to predict the current data. Considering the CPU and RAM limitations of underwater nodes, the model adopts the difference transmission method, which reduces the calculation of the cluster heads, the communication overhead and the size of data packet. The simulation results show that ESDP can better balance the data prediction accuracy and energy consumption, and improve the life cycle of the whole network. Therefore, ESDP method can be better applied to underwater environments.

中文翻译：

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改善水下无线传感器网络的生命周期

摘要

针对水下无线传感器网络的复杂性和节点连续感知的数据时间相关性高的特点，提出一种基于指数平滑（ESDP）的水下数据预测优化方法，以提高整个生命周期。网络。在该方法中，LEACH 协议用于对整个节点进行聚类并选举一些簇头。然后在簇头之间构建路由树与水面汇节点进行通信。最后，采用优化的指数平滑方法建立预测模型，对当前数据进行预测。考虑到水下节点的CPU和RAM限制，模型采用差分传输方式，减少了簇头的计算，通信开销和数据包的大小。仿真结果表明，ESDP可以更好地平衡数据预测精度和能耗，提高整个网络的生命周期。因此，ESDP 方法可以更好地应用于水下环境。