Wireless sensor networks data compression method based on self-adaptive optimal zero suppression
A wireless sensor and network data technology, applied in network topology, wireless communication, network traffic/resource management, etc., can solve the problem of wasting communication bandwidth, increasing network delay and node energy consumption, affecting the stability and life of sensor network systems, etc. problem, to achieve the effect of reducing network delay and reducing average energy consumption
Inactive Publication Date: 2013-08-07
HANGZHOU DIANZI UNIV
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[0002] In a monitoring system based on wireless sensor networks, there is a large amount of redundant information in the original data collected by sensor nodes, including the time redundancy of data collected by the same node at adjacent times, and the data collected by adjacent nodes in geographical areas. Spatial redundancy, if the data carrying a large amount of redundant information is directly transmitted to the base station, it will waste communication bandwidth, increase network delay and node energy consumption, and then affect the stability and life of the entire sensor network system. Compressing redundant information before raw data is a mechanism that can effectively reduce node energy consumption
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[0014] The present invention will be further described below in conjunction with drawings and embodiments.
[0015] The core idea of the present invention is to introduce a lossless self-adaptive optimal zero-suppression algorithm, and perform zero-suppression operation and coding on the perceptual data sequence arranged incrementally by adaptively finding the optimal bit factor, so that the final perceptual data sequence The encoding length is the shortest, fully excavating the correlation between the data collected by sensor nodes, and removing redundant information to the greatest extent, thereby reducing the average energy consumption of nodes and prolonging the life of the sensor network.
[0016] The present invention will be described in further detail below in conjunction with the accompanying drawings.
[0017] Firstly, the relevant terms involved in the adaptive optimal zero-suppressing compression method are given.
[0018] relevant bit : Used to mark equal dat...
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The invention relates to a wireless sensor networks data compression method based on self-adaptive optimal zero suppression. Data in the existing wireless sensor network often presents abundant redundant information, which can waste communication bandwidth, increase network delay and node energy consumption. In the invention, a lossless self-adaptive optimal zero suppression algorithm is introduced, i.e. the zero suppression calculation and coding are carried out on a perceptive data sequence with an increasing sequence through self-adaptive searching an optimal digit factor, so the final coding length of the perceptive data sequence is the shortest, the correlation of the data collected by the sensor nodes can be fully excavated and the redundant information can be deleted to the maximaldegree, thus the average energy consumption of the nodes can be reduced and the service life of the sensor networks can be prolonged. The method in the invention can reduce the required data transmission volume in the network, thereby reducing the average energy consumption of the nodes and the network delay.
Description
technical field [0001] The invention relates to the technical field of data compression of wireless sensor networks, in particular to a wireless sensor network (WSNs) data compression method based on adaptive optimal zero suppression. Background technique [0002] In a monitoring system based on wireless sensor networks, there is a large amount of redundant information in the original data collected by sensor nodes, including the time redundancy of data collected by the same node at adjacent times, and the data collected by adjacent nodes in geographical areas. Spatial redundancy, if the data carrying a large amount of redundant information is directly transmitted to the base station, it will waste communication bandwidth, increase network delay and node energy consumption, and then affect the stability and life of the entire sensor network system. Compressing redundant information before raw data is a mechanism that can effectively reduce energy consumption of nodes. [00...
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IPC IPC(8): H04W28/06H04W84/18H04L1/00
CPCY02B60/50
Inventor 蒋鹏吴建峰董林玺
Owner HANGZHOU DIANZI UNIV