Context-adaptive quotient and remainder encoding method used for sensing data of wireless sensing nodes

A technology of wireless sensor nodes and sensing data, which is applied in the field of data compression, and can solve the problems of loss of original data accuracy, failure of lossy compression algorithm, discarding, etc.

Inactive Publication Date: 2012-07-18
NORTHWEST UNIV
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Problems solved by technology

[0011] Although lossy compression techniques can significantly improve the compression ratio, it is often at the expense of discarding a large amount of original data and/or losing the accuracy of the original data...

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  • Context-adaptive quotient and remainder encoding method used for sensing data of wireless sensing nodes
  • Context-adaptive quotient and remainder encoding method used for sensing data of wireless sensing nodes
  • Context-adaptive quotient and remainder encoding method used for sensing data of wireless sensing nodes

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Embodiment Construction

[0032] The invention divides the sensing data of the wireless sensor nodes into two types: slowly changing data and non-slowly changing data. Among them, the slow-varying data refers to the data whose standard deviation of the difference sequence of the sensor node perception data is less than or equal to 3, and the fluctuation degree of the slowly-varying data is small; Variable data, non-slowly variable data fluctuate greatly.

[0033] The analysis of the probability distribution characteristics of sensor node perception data is as follows:

[0034] The data to be collected by sensor nodes is a function that changes with time. For each specific moment, due to the influence of factors such as various interferences and node acquisition accuracy, there is a slight error between the actually collected data and the real value. Obviously, the data collected by the sensor d i and the real collected volume m i have d i =m i +ε i , ε i ~N(0,σ i 2 ), where ε i is the error, σ...

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Abstract

The invention discloses a context- adaptive quotient and remainder encoding method used for sensing data of wireless sensing nodes. The method comprises the following steps of orderly calculating differences of N sensing data to be encoded to obtain original difference values; respectively converting the original difference values to obtain the difference data, wherein the initial data digit D is 1, and i is equal to 1; using 2D as a divisor to obtain a quotient Q and a remainder R when the present difference data is used as a dividend; carrying out fixed-length encoding to the quotient, and carrying out length-variable encoding to the remainder; enabling the data digit D to be equal to the digit of the present difference data; and judging whether the next uncoded different data exists or not, if so, i is equal to i plus one, and executing the step 3, and if not, accomplishing the encoding to obtain the quotient and remainder codes of the difference data. The context- adaptive quotient and remainder encoding method used for sensing data of wireless sensing node has high compression ratio on both slowly changed data and non-slowly changed data, and can be smoothly operated among sensing nodes to realize lossless data compression. The context-adaptive quotient and remainder encoding algorithm used for sensing data of wireless sensing nodes has the advantages of low operation complexity and small occupied storage space.

Description

technical field [0001] The invention belongs to the technical field of data compression, and in particular relates to a context adaptive quotient encoding method for sensing data of wireless sensor nodes. Background technique [0002] The application of wireless sensor network (WSN) is more and more extensive. However, the energy consumption of wireless sensor nodes is one of the bottlenecks restricting its application. Studies have shown that the energy of sensor nodes is mainly consumed in the process of wireless data transmission, so the research of various data compression algorithms has quickly become a new hot spot in wireless sensor networks. [0003] At present, there have been many studies on lossy data compression in sensor networks, but there are only a few algorithms for lossless data compression based on sensor nodes. In 2006, Sadler C.M. and Martonosi M. proposed a dictionary-based lossless data compression algorithm called S-LZW algorithm, which is an improve...

Claims

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Application Information

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IPC IPC(8): H04W28/06H04W84/18H04L1/00
Inventor 房鼎益任学军陈晓江陈少峰赵康王薇邢天璋张远刘晨王举尹小燕
Owner NORTHWEST UNIV
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