A data compression method for ultra-long linear ring wireless network

Abstract

The invention relates to a method for compressing data in an ultra-long linear annular wireless network. Each sensor in the wireless network is arranged according to an ultra-long linear annular distributed data transmission model, and all sensor nodes are divided into several clusters, and the sensors in each cluster The nodes include a cluster head node and several non-cluster head nodes; the initial sequence of data in the non-cluster head nodes is converted by a ring-shaped distributed 5 / 3 integer wavelet frequency division algorithm to obtain a wavelet coefficient sequence, and the high-level wavelet coefficient sequence in the wavelet coefficient sequence The frequency coefficient sequence is filtered by a threshold value to obtain a simplified wavelet coefficient sequence, and finally the simplified wavelet coefficient sequence is transmitted to the cluster head node. In the cluster head node, the simplified wavelet coefficient sequence is compressed by quasi-run encoding and transmitted to the base station node. Compared with the prior art, the present invention reduces the overall power consumption of clustering, increases the data compression rate, improves the compression effect, and at the same time, can further reduce the packet loss rate and improve the channel condition.

Description

technical field [0001] The invention relates to a data compression method, in particular to a super-long linear ring network data compression method. Background technique [0002] As a new generation of communication network, wireless sensor network can carry out long-term and effective intelligent monitoring of the environment through widely distributed network sensor nodes. For example, the ultra-long linear wireless sensor network applied to the subway tunnel monitoring system uses a large number of low-power and low-cost wireless sensor nodes to monitor the situation of the subway tunnel, which has a very wide range of application scenarios and very good application effects. [0003] The transmission nodes of the wireless sensor network need to periodically transmit data to the network for a long time, the data volume is large and the transmission energy consumption is high. The energy problem of wireless sensor network has always been the bottleneck that limits its wid...

AI Technical Summary

Problems solved by technology

[0003] The transmission nodes of the wireless sensor network need to periodically transmit data to the network for a long time, the data volume is large and the transmission energy consumption is high.

The energy problem of wireless sensor network has always been the bottleneck that limits its wide application

However, common data compression methods based on wireless sensor networks have low performance in ultra-long linear structures, and cannot efficiently operate a large number of nodes.

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