基于无线传感器网络的小波数据压缩算法

Luo Xiao
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引用次数: 2

摘要

首先,本文提出了一种基于学习自动机的数据汇聚算法,解决了现有数据汇聚算法无法解决的问题、能量消耗不均匀以及现有算法在开销环境下无法动态改变采集路径等问题。在该方法中,节点可以通过改变其采集路径来调整开销环境。WSN的所有节点都配备了一个学习自动机。这些学习自动机学习所有节点的聚集路径。在传递信息的过程中,传递两种类型的数据,包括数据包和知识包。当节点的信息发生变化时,学习自动机根据节点的反馈对当前的采集路径进行奖励或惩罚,从而找到最佳的采集路径。其次,本文改进了小波数据压缩算法,提出了不同数据之间的相关性。该算法并没有减少太多与原始数据相关的数据。经过小波数据压缩后,霍夫曼编码压缩算法将提高数据压缩比。
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An Algorithm of Wavelet Data Compression Based on Wireless Sensor Network
Firstly, this paper gives a data aggregation algorithm based on learning automata to solve the problem that the existing data aggregation algorithm can’t solve, the uneven energy cost, and the existing algorithm can’t change the gathering path dynamically existing the overhead environment. In the proposed method, nodes can change its gathering path to adjust the overhead environment. All the nodes of WSN equipped with a learning automata. These leaning automata learn all the gathering path of the nodes. In the process of transmit information two kinds of data are transmitted, including data packet, knowledge packet .When the information of the nodes changes, according to the feedback of the nods, the learning automata gives the reward or punish to the current gathering path, which help to find the best gathering path. Secondly, this paper improved the wavelet data compression algorithm, which was brought out as the correlation between different data. The algorithm do not reduce much of the data relate to the original data. After the wavelet data compression, Huffman coding compression algorithm will improve the data compression ratio.
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