Method for compressing multiple principle component analysis data of wireless sensor network

Abstract

The invention relates to a method for compressing multiple principle component analysis data of a wireless sensor network. Data compression is performed by iteratively using principle component analysis on a plurality of layers of routers in the wireless sensor network, so that the relativity between data acquired by different nodes in the same cluster within a certain period of time and the relativity between primarily extracted principle components of adjacent clusters on the same layer of the routers are effectively eliminated and data compression ratio can be further enhanced on the premise of ensuring data reconstruction accuracy required by a user. Therefore, the method can reduce energy consumption of a sensor node and prolong network lifetime and can be used in cluster layered routing protocol algorithm of the wireless sensor network.

Description

Technical field [0001] The invention relates to a data compression method collected by a wireless sensor network, in particular to a multi-principal component analysis data compression method for a wireless sensor network. Background technique [0002] Wireless sensor network is currently a frontier hot research field that is attracting international attention, involving highly interdisciplinary and highly integrated knowledge. Advances in sensor technology, micro-electromechanical systems, modern networks, and wireless communications have promoted the emergence and development of wireless sensor networks. Wireless sensor networks have expanded people's ability to obtain information and connected physical information in the objective world with transmission networks. In the next-generation network, people will be provided with the most direct, effective and authentic information, which has very broad application prospects and can be widely used in military defense, industria...

AI Technical Summary

Problems solved by technology

[0005] The present invention provides a wireless sensor network multi-principal component analysis data compression method, which can effectively solve the single principal component analysis data compression method, which can only eliminate the correlation between data collected by different nodes in the same cluster for a period of time, while It is impossible to eliminate the correlation problem between adjacent cluster head data on the same layer routing, and at the same time improve the total data compression ratio, reduce communication overhead and energy consumption of sensor nodes, and prolong the network life cycle

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