A method for fast transmission of wireless network data

Abstract

The present application relates to the technical field of data compression, in particular to a wireless network data fast transmission method, which converts wireless network data into binary data sequence, obtains bit information coincidence degree of each bit position according to distribution condition of binary code of information data segment in binary information data sequence, obtains information correlation coefficient according to correlation degree between data binary set of corresponding bit position between adjacent information data segments, obtains information data compressibility corresponding to each position according to similarity distribution condition of bit information coincidence degree and information correlation coefficient, and completes compression and transmission of wireless network data according to adaptive selection of compression coding window based on information data compressibility. The present application improves hit rate of data matching in compression process and compression effect, and further improves transmission efficiency of network data.

Description

Technical Field

[0001] This invention relates to the field of data compression technology, and more specifically to a method for fast transmission of wireless network data. Background Technology

[0002] With the rapid development of information and communication technologies, network data on the existing Internet is growing explosively. Transmitting large amounts of data in a short period can lead to local network congestion, reducing the transmission efficiency of wireless network data and causing delays in user access to network data, further affecting the timeliness of wireless network data. To improve the transmission efficiency of wireless network data, compressed data is typically transmitted. Existing technology improves the dictionary search window size based on the existing LZ77 algorithm to further enhance data compression efficiency.

[0003] However, because network data has a strong temporal correlation, when using existing compression methods to compress network data, the characteristic information and correlation features of the data itself are ignored, resulting in a low data matching hit rate and poor compression effect, thereby reducing the transmission efficiency of network data. Summary of the Invention

[0004] To address the technical problem that existing compression methods for network data often neglect the data's inherent characteristics and correlation features, resulting in low data matching hit rates and poor compression performance, thereby reducing network data transmission efficiency, this invention aims to provide a method for fast transmission of wireless network data. The specific technical solution adopted is as follows:

[0005] This invention proposes a method for fast data transmission in a wireless network, the method comprising:

[0006] Obtain the binary information data sequence to be transmitted in the wireless network, and divide the binary information data sequence into at least two information data segments with a preset byte length;

[0007] The bit information overlap degree corresponding to each bit position is obtained by the distribution of the subsequent binary code of each bit position in each information data segment. The data binary set of each bit position is obtained by extending the bit information overlap degree of each bit position in each information data segment. In the binary information data sequence, the corresponding information correlation coefficient is obtained according to the correlation degree between each information data segment and the data binary set of the corresponding bit position of the next adjacent information data segment.

[0008] Based on the bit information overlap and information correlation coefficient corresponding to each bit position in each information data segment, a tuple is constructed. Based on the distribution of similarity between each bit position in each information data segment and the tuples of subsequent positions, the information data compressibility of each bit position in each information data segment is obtained.

[0009] Based on the information data compression and the preset buffer length adjustment coefficient, a compression coding window corresponding to each bit position of each information data segment is obtained. The dynamic compression of the binary information data sequence is completed according to the compression coding window, and the dynamically compressed binary information data sequence is transmitted over the network.

[0010] Furthermore, the method for obtaining the bit information overlap includes:

[0011] The binary code following each bit position in the target information data segment is statistically analyzed. Logical operations are performed between the binary code of the target bit position in the target information data segment and the binary code of each subsequent bit position. Based on the results of the logical operations, the bit information overlap of the target bit position in the target information data segment is obtained.

[0012] By changing the target bit position, the bit information overlap of each bit position in the target information data segment is obtained; by changing the target information data segment, the bit information overlap of each bit position in each information data segment is obtained.

[0013] Furthermore, the method for obtaining the binary data set includes:

[0014] The overlap of target bit information corresponding to the target bit position in the target information data segment is statistically analyzed. The length of the bit string corresponding to the target bit position is obtained based on the sum of the overlap of the target bit information and the value 1. Starting with the binary code corresponding to the target bit position, consecutive binary codes are combined to obtain binary bit strings of different lengths. The length of the binary bit string is less than or equal to the bit string length. A corresponding data binary set is constructed based on all the binary bit strings of the target bit position.

[0015] By changing the target bit position, we obtain the binary data set of each bit position in the target information data segment; by changing the target information data segment, we obtain the binary data set of each bit position in each information data segment.

[0016] Furthermore, the method for obtaining the information correlation coefficient includes:

[0017] The next adjacent information data segment in the binary information data sequence of the target information data segment is denoted as the target adjacent information data segment. The number of identical bit strings is obtained based on the number of identical binary bit strings between the two binary data sets corresponding to the target bit position. The information correlation coefficient of the target bit position in the target information data segment is obtained based on the ratio of the number of identical bit strings to the total number of binary bit strings in the two binary data sets.

[0018] By changing the target bit position, we obtain the information correlation coefficient of each bit position in the target information data segment. By changing the target information data segment, we obtain the information correlation coefficient of each bit position in each information data segment.

[0019] Furthermore, the method for obtaining the information data compression includes:

[0020] In the target information data segment, the target bit position and the corresponding tuple for each subsequent bit position are counted. The cosine similarity between the target bit position and the corresponding tuple for each subsequent bit position is calculated. The mean of the cosine similarity is calculated to obtain the information data compressibility corresponding to the target bit position in the target information data segment.

[0021] The information data compression ratio of each bit position in the target information data segment is obtained by changing the target bit position. The information data compression ratio of each bit position in each information data segment is obtained by changing the target information data segment.

[0022] Furthermore, the method for obtaining the compression encoding window includes:

[0023] Calculate the product of the information data compression factor and the preset buffer length adjustment factor for each bit position in each information data segment, and round up the product to obtain the compression coding window for each bit position in each information data segment.

[0024] Furthermore, the dynamic compression of the binary information data sequence based on the compression encoding window includes:

[0025] The encoding buffer window corresponding to each bit position in each information data segment in the LZ77 compression algorithm is replaced with the corresponding compression encoding window to complete the dynamic compression of the binary information data sequence.

[0026] The present invention has the following beneficial effects:

[0027] Considering the inherent redundancy and overlap in wireless network data, this invention provides data compressibility by analyzing the bit overlap and correlation coefficient at each bit position within each data segment. This data compressibility characterizes the degree of redundancy and overlap in wireless network data. Furthermore, the invention adaptively compresses the wireless network data based on this data compressibility. This approach balances the redundancy and correlation characteristics of the wireless network data, resulting in higher compression efficiency when data is compressed according to the data compressibility at each position within each data segment. Further, this invention obtains a compression coding window at each position within each data segment based on the data compressibility. By adaptively adjusting the size of this compression coding window, the temporal correlation of the wireless network data is integrated into the compression process, improving the data matching hit rate and compression effect, thereby further enhancing network data transmission efficiency. Attached Figure Description

[0028] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a flowchart of a method for fast transmission of wireless network data provided in one embodiment of the present invention. Detailed Implementation

[0030] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a fast wireless network data transmission method proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0031] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0032] The following description, in conjunction with the accompanying drawings, details a specific scheme for a fast wireless network data transmission method provided by the present invention.

[0033] Please see Figure 1The diagram illustrates a flowchart of a fast wireless network data transmission method according to an embodiment of the present invention, the method comprising:

[0034] Step S1: Obtain the binary information data sequence to be transmitted in the wireless network, and divide the binary information data sequence into at least two information data segments with a preset byte length.

[0035] This invention aims to provide a method for fast transmission of wireless network data. It compresses the wireless network data based on its temporal correlation characteristics, improving compression efficiency and thus further increasing the transmission rate. Therefore, the first step is to acquire the wireless network data to be transmitted.

[0036] When users receive or send different types of information data using various terminal devices, such as text, images, and videos, these different types of data are converted into corresponding binary codes using character code tables, such as Unicode, and then transmitted in the network as binary sequences. Therefore, this embodiment of the invention first obtains the binary information data sequence to be transmitted in the wireless network. In this embodiment, the transmitted data received or sent by the user is collected by a network data sensor to obtain the corresponding binary information data sequence. In this binary information data sequence, the horizontal axis index is the sensor sampling timestamp, and the vertical axis data is the corresponding binary value, i.e., 0 or 1. It should be noted that Unicode is a technical term well known to those skilled in the art and will not be further elaborated here.

[0037] Because wireless network data exhibits temporal correlation—that is, different types of data in different scenarios show time-related regularities within short time segments—this invention aims to better represent the temporal correlation of wireless network data. The binary information data sequence can be segmented based on its distribution characteristics before and after time changes. In this embodiment, the binary data sequence is divided into at least two information data segments of a preset byte length. Considering that the smallest unit of effective information in a binary information data sequence is a byte (i.e., a sequence of eight binary numbers), the preset byte length is set to 8 bits in this embodiment, meaning each information data segment corresponds to one byte (8 bits). Analyzing the segmented information data segments more clearly reveals the distribution characteristics of the binary information data sequence before and after time changes, further compressing the original data (the binary information data sequence) and improving data transmission speed in the network. It should be noted that since the binary information data sequence is obtained by encoding the data to be transmitted, and the information data segments are divided based on the original binary information data sequence, in order to ensure that the content of the data to be transmitted does not change, each information data segment should have a certain order, that is, all information data segments divided by the binary information data sequence should be arranged in order.

[0038] Step S2: Obtain the bit information overlap degree corresponding to each bit position based on the distribution of the subsequent binary code at each bit position in each information data segment. Extend the data binary set at each bit position by extending the data binary set at each bit position in each information data segment. In the binary information data sequence, obtain the corresponding information correlation coefficient based on the correlation degree between each information data segment and the data binary set at the corresponding bit position of the next adjacent information data segment.

[0039] Because wireless network data transmission exhibits data overlap and redundancy, this characteristic can be used to analyze the overlap features of each data segment, facilitating subsequent compression of the wireless network data. Considering the temporal correlation of wireless network data, the overlap features are analyzed based on the correlation degree of different bits within each data segment, and the changes in bit features before and after each bit in each data segment divided by the binary data sequence are analyzed and calculated. In this embodiment, the bit information overlap degree is obtained for each bit position based on the distribution of subsequent binary codes in each data segment. The bit information overlap degree characterizes the change in the order of binary bit combinations obtained after encoding and conversion of different data in the wireless network data.

[0040] Preferably, the method for obtaining the bit information overlap includes:

[0041] The binary code following each bit position in the target information data segment is statistically analyzed. Logical operations are performed between the binary code of the target bit position in the target information data segment and the binary code of each subsequent bit position. Based on the result of the logical operations, the bit information overlap of the target bit position in the target information data segment is obtained. The bit information overlap of each bit position in the target information data segment is obtained by changing the target bit position. The bit information overlap of each bit position in each information data segment is obtained by changing the target information data segment.

[0042] By performing logical operations on each subsequent bit position of the target bit position, bits with the same binary code as the target bit position are selected. The bit information overlap degree, obtained by accumulating the values ​​after an XNOR operation, reflects the information overlap and redundancy of the target bit position. In other words, it reflects the distribution of the same binary code between the target bit position and each subsequent bit position in the target information data segment. The greater the number of identical binary codes between the target bit position and each subsequent bit position in the target information data segment, the greater the bit information overlap degree of the target bit position in the target information data segment. Further analysis based on the bit information overlap degree facilitates the adjustment of the compression encoding window size for the target position during subsequent compression. In this embodiment of the invention, the logical operation method uses an XNOR operation.

[0043] When using the XOR operation, the method for obtaining the corresponding bit information overlap is expressed in the formula as follows:

[0044]

[0045] Among them, pw i，k B represents the bit overlap at the k-th bit position of the i-th information data segment in the binary information data sequence. k B represents the binary code corresponding to the k-th bit position in the i-th information data segment. s This represents the binary code corresponding to the s-th bit position in the i-th information data segment, where N is the length of the information data segment, i.e., the number of binary codes in the information data segment. In this embodiment of the invention, the length of the information data segment is set to 8, meaning that each information data segment contains 8 binary codes. ⊙ represents the XOR operator, B... k ⊙B s B k With B s Perform the XOR operation, i.e., B k With B s If they are the same, output 1; B k With B s If different, output 0.

[0046] It should be noted that logical operations can also employ different methods such as XOR, the essential purpose of which is to filter out bit positions that have the same binary code as the target bit position. For example, when XOR is used, the XOR sign in the formula for obtaining bit information overlap during XNOR can be changed to the XOR sign, and the content after the summation sign can be negatively correlated. The corresponding modified formula is as follows:

[0047]

[0048] in, The XOR operator. B k With B s Perform an XOR operation, i.e., B k With B s If the values ​​are the same, output 0; B k With B s If the values ​​are different, output 1. The values ​​represented by the other parameters are the same as those obtained by the formula for obtaining the bit information overlap when using the XOR operation, and will not be elaborated further here.

[0049] For example, when the binary code corresponding to the i-th information data segment is 01101110, calculate the bit information overlap at its second bit position. Since the binary code corresponding to the second bit position is 1, and there are four 1s and two 0s in all subsequent bit positions, perform an XOR operation between the second bit position and the binary code of each subsequent bit position. Since the XOR operation of binary codes 1 and 1 results in 1, while the XOR operation of 1 and 0 results in 0, the sum of the XOR operation results in a bit information overlap of 4. Similarly, for the first bit position, the corresponding binary code is 0, and there are five 1s and two 0s in all subsequent bit positions. Perform an XOR operation between the first bit position and the binary code of each subsequent bit position. The XOR operation of binary codes 0 and 0 results in 1, while the XOR operation of 0 and 1 results in 0, the sum of the XOR operation results in a bit information overlap of 2.

[0050] Furthermore, data in a network is typically transmitted using binary encoding. While individual binary codes cannot represent actual data information, a string of binary bits composed of several binary codes may possess certain informational meaning. If the binary information data sequence corresponding to wireless network data is compressed without considering the specific meaning of the corresponding binary code sequence, and the compression is based solely on the distribution of the binary codes, the temporal correlation characteristics of the wireless network data itself will be ignored. This results in a low data matching hit rate during compression, leading to poor compression performance. Therefore, a comparative analysis can be performed based on the binary bit strings composed of the binary codes of adjacent information data segments, thereby introducing the temporal correlation inherent in the wireless network data itself. In this embodiment of the invention, the data binary set for each bit position is obtained by extending backward based on the overlap of bit information at each bit position in each information data segment. In the binary information data sequence, the corresponding information correlation coefficient is obtained based on the degree of correlation between each information data segment and the data binary set at the corresponding bit position of the next adjacent information data segment. The higher the degree of correlation between the corresponding information data segment and the data binary set at the corresponding bit position of the next information data segment, the larger the corresponding information correlation coefficient, indicating a higher semantic similarity between the two information data segments.

[0051] Preferably, the method for obtaining the binary data set includes:

[0052] The overlap of target bit information at target bit positions in the target information data segment is statistically analyzed. The length of the bit string corresponding to the target bit position is obtained based on the sum of the overlap and the value 1. Starting with the binary code corresponding to the target bit position, consecutive binary codes are combined to obtain binary bit strings of different lengths. The length of the binary bit string is less than or equal to the bit string length. A corresponding data binary set is constructed based on all binary bit strings at the target bit position. Changing the target bit position yields the data binary set for each bit position in the target information data segment. Changing the target information data segment yields the data binary set for each bit position in each information data segment.

[0053] The binary data set can characterize the distribution characteristics of binary codes in the binary bit string corresponding to the target bit position in the target information data segment. Furthermore, the bit string length is obtained through bit information overlap, allowing the binary data set to represent both the distribution characteristics of binary codes and the overlap information of information data segments. This ensures that the subsequently obtained information correlation coefficients possess both the overlap and redundancy characteristics of wireless network data and certain semantic features, making the semantic similarity representation between different information data segments more accurate and improving subsequent compression performance.

[0054] For example, if the binary code corresponding to the target information data segment is 01101110, then the bit information overlap of the second bit position is 4, that is, the length of the corresponding bit string is 5. Starting from the binary code corresponding to the second bit position, we can obtain five different binary bit strings: 1, 11, 110, 1101, and 11011. The corresponding binary data set is {1, 11, 110, 1101, 11011}.

[0055] Preferably, the method for obtaining the information correlation coefficient includes:

[0056] The next adjacent information data segment in the binary information data sequence of the target information data segment is denoted as the target adjacent information data segment. The purpose of obtaining the target adjacent information data segment is to further compare the two adjacent information data segments to reflect the temporal correlation characteristics of information data segments in the binary information data sequence, that is, the temporal correlation characteristics of wireless network data.

[0057] The number of identical bit strings is obtained by counting the number of identical binary bit strings between the target information data segment and the target adjacent information data segment at the target bit position in the two data binary sets. The information correlation coefficient of the target bit position in the target information data segment is obtained by the ratio of the number of identical bit strings to the total number of binary bit strings in the two data binary sets. The ratio between the number of identical bit strings and the total number of bit strings characterizes the similarity between data binary sets. Furthermore, the similarity between data binary sets characterizes the semantic similarity between information data segments, making the characterization of the correlation features between information data segments more accurate. The more consecutive identical bits are in the subsequent binary codes at the corresponding bit positions of the target information data segment and the target adjacent information data segment, the higher the similarity between the corresponding data binary sets, that is, the more similar the semantic features of the target information data segment and the target adjacent information data segment, and the larger the information correlation coefficient corresponding to the target information data segment.

[0058] By changing the target bit position, we obtain the information correlation coefficient of each bit position in the target information data segment. By changing the target information data segment, we obtain the information correlation coefficient of each bit position in each information data segment.

[0059] By analyzing the correlation characteristics between the binary sets of data corresponding to the bit positions of adjacent information data segments, the temporal correlation characteristics of different adjacent data segments can be characterized, thus reflecting the temporal correlation characteristics of wireless network data. Furthermore, because the acquisition process of the binary data set considers the semantic features of each information data segment, the acquisition of the information correlation coefficient more accurately represents the similarity between different information data segments. This results in a higher data matching hit rate and better compression effect when compressing overlapping data.

[0060] The method for obtaining the information correlation coefficient is expressed in the formula as follows:

[0061]

[0062] Among them, pm i，k A represents the information correlation coefficient corresponding to the k-th bit position of the i-th information data segment in a binary information data sequence. i Let A represent the set of binary data corresponding to the k-th bit position of the i-th information data segment. i+1 Let A represent the set of binary data corresponding to the k-th bit position of the (i+1)-th information data segment. i ∩A i+1 A represents the number of identical bit strings between the binary sets of the data at the k-th bit position of the i-th and (i+1)-th information data segments. i ∪A i+1 This represents the total number of binary bit strings in the two binary sets of data at the k-th bit position of the i-th and (i+1)-th information data segments.

[0063] For example, when the data binary set A corresponding to the k-th bit position of the i-th information data segment in the binary information data sequence... i Let {1, 11, 110, 1101, 11011} be the set of binary data A corresponding to the k-th bit position of the (i+1)-th information data segment in the binary information data sequence. i+1 Let {1, 11, 111, 1110, 11101} be the binary set of data A. i and binary data set A i+1 The total number of binary bits in the string is 10, that is, A i ∪A i+1 The value is 10; the binary data set A i and binary data set A i+1 The number of identical bit strings between them is 3, that is, 3 pairs of identical bit strings, corresponding to A. i ∩A i+1The value is 3. Further calculations can be performed to determine the information correlation coefficient pm at the k-th bit position of the i-th information data segment in the binary information data sequence. i，k for When the binary data set A i and binary data set A i+1 When they are completely identical, the corresponding information correlation coefficient reaches its maximum value, that is...

[0064] Step S3: Construct a tuple based on the bit information overlap and information correlation coefficient corresponding to each bit position in each information data segment. Based on the distribution of similarity between each bit position in each information data segment and the tuples of subsequent positions, obtain the information data compressibility of each bit position in each information data segment.

[0065] Thus, the bit information overlap and information correlation coefficient of each bit position in each information data segment are obtained, representing the overlap and redundancy characteristics and temporal correlation characteristics of wireless network data, respectively. Further analysis of the bit information overlap and information correlation coefficient ensures that these characteristics are considered during compression, improving the encoding and compression efficiency of wireless network data. Considering that the essence of encoding compression is to replace repeated data or characters using indexes, i.e., analyzing data repetition, and that the encoding compression order is usually the same as the binary code order, the bit information overlap and information correlation coefficient can be used to characterize the information repetition characteristics corresponding to each bit position in each information data segment. Furthermore, the similarity between the information repetition characteristics of each bit position in each information data segment and subsequent bit positions is calculated to characterize the compression degree of each bit position. In this embodiment, a binary tuple is constructed based on the bit information overlap and information correlation coefficient corresponding to each bit position in each information data segment. Based on the distribution of similarity between the binary tuples of each bit position in each information data segment and subsequent positions, the information data compressibility of each bit position in each information data segment is obtained.

[0066] Preferably, the method for obtaining information data compressibility includes:

[0067] In the target information data segment, the target bit position and the corresponding binary pair for each subsequent bit position are counted. The binary pair can combine the bit information overlap degree and the information correlation coefficient, which facilitates subsequent similarity analysis.

[0068] Calculate the cosine similarity between the target bit position and the corresponding tuple for each subsequent bit position, and calculate the mean of the cosine similarity to obtain the information data compressibility corresponding to the target bit position in the target information data segment; change the target bit position to obtain the information data compressibility of each bit position in the target information data segment, and change the target information data segment to obtain the information data compressibility of each bit position in each information data segment.

[0069] Since the number of data following the target bit position is always greater than the number of data following subsequent bit positions, the corresponding bit information overlap and information correlation coefficient will differ. However, there is a correlation between the information correlation coefficient and the degree of bit information overlap. Therefore, by calculating the cosine similarity between the target bit position and the corresponding tuples of each subsequent bit position in the same information data segment to characterize the similarity, the influence of individual data values ​​in the tuples can be avoided, making the similarity calculation more accurate. Furthermore, using the mean of the cosine similarity as the corresponding information data compressibility can avoid the influence of different bit positions on the compression calculation, further providing a basis for subsequent compression calculations. Moreover, the higher the cosine similarity between the tuple corresponding to the target bit position and the tuple corresponding to the subsequent bit positions, the greater the information data compressibility of the target bit position, indicating a greater correlation between the current information data segment and the next information data segment, i.e., a higher compressibility of the target bit position.

[0070] A binary tuple is represented in the formula as follows:

[0071] Tu i，k =(pw i，k pm i，k )

[0072] Among them, Tu i，k pw is the tuple corresponding to the k-th bit position in the i-th information data segment of the binary information data sequence. i，k pm represents the bit overlap at the k-th bit position in the i-th information data segment of the binary information data sequence. i，k It is the information correlation coefficient corresponding to the k-th bit position in the i-th information data segment of the binary information data sequence.

[0073] Information data compressibility is expressed in the formula as follows:

[0074]

[0075] Among them, E i，k Tu represents the compressibility of the information data at the k-th bit position in the i-th information data segment of a binary information data sequence. i，kTu represents the tuple at the k-th bit position in the i-th information data segment of the binary information data sequence. i，j This represents the tuple located at the j-th position after the k-th bit position in the i-th information data segment of the binary information data sequence. N is the length of the information data segment, i.e., the number of binary codes in the information data segment. In this embodiment of the invention, the length of the information data segment is set to 8, meaning that each information data segment contains 8 binary codes. `sim()` is a cosine similarity calculation function used to calculate the cosine similarity between different data within the parentheses.

[0076] Step S4: Based on the information data compressibility and the preset buffer length adjustment coefficient, obtain the compression coding window corresponding to each bit position of each information data segment, complete the dynamic compression of the binary information data sequence according to the compression coding window, and transmit the dynamically compressed binary information data sequence over the network.

[0077] Step S3 obtains the compressibility of information data at each bit position in each information data segment, i.e., the compressibility at each position in the binary information data sequence. Further, the binary information data sequence is adaptively compressed based on the compressibility at each position. Considering that the traditional LZ77 compression algorithm typically selects a fixed-length encoding buffer window at each position and compares it with the data in the dictionary region to complete the data encoding compression, this invention can adaptively adjust the length of the encoding buffer window according to the information data compressibility at each bit position to complete the data encoding compression. In this embodiment of the invention, the compressed encoding window corresponding to each bit position of each information data segment is obtained based on the information data compressibility and a preset buffer length adjustment coefficient. The compressed encoding window is the adjusted encoding buffer window. The purpose of setting the preset buffer length adjustment coefficient is to ensure that the information data compressibility matches the compressed encoding window length in a numerical dimension. It should be noted that the LZ77 compression algorithm is a well-known prior art and will not be further limited or described here.

[0078] Preferably, the method for obtaining the compression encoding window includes:

[0079] Calculate the product of the information data compressibility at each bit position in each information data segment and the preset buffer length adjustment coefficient. Round the product up to obtain the window length, which is the compression coding window for each bit position in each information data segment. Adjust the information data compressibility using the preset buffer length adjustment coefficient through multiplication, so that the information data compressibility is positively correlated with the length of the compression coding window.

[0080] The method for obtaining the compression encoding window length is expressed in the formula as follows:

[0081]

[0082] Among them, Z i，k E represents the length of the compression coding window at the k-th position of the i-th information data segment in the binary information data sequence. i，k S represents the compressibility of the information data at the k-th position of the i-th information data segment in the binary information data sequence, and S is a preset buffer length adjustment coefficient. In this embodiment of the invention, the preset buffer length adjustment coefficient is set to 8, which is the length of one information data segment. This is a rounding function, designed to ensure that the resulting compressed encoding window length is meaningful.

[0083] Furthermore, dynamic compression of the binary information data sequence is completed based on the compression encoding window.

[0084] Preferably, the dynamic compression process includes:

[0085] The LZ77 compression algorithm replaces the encoding buffer window corresponding to each bit position in each information data segment with the corresponding compression encoding window to achieve dynamic compression of the binary information data sequence. By adaptively adjusting the size of the compression encoding window based on the temporal correlation and redundancy characteristics of the binary information data sequence, the compression encoding window is larger when the information data at a given position has higher compressibility. This results in a longer encoding buffer window, improving the pairing degree between different data and further enhancing the compression efficiency of wireless network data.

[0086] Finally, the dynamically compressed binary information data sequence is transmitted over the network. Because the compression method of this invention has a higher data matching hit rate and better compression effect compared to traditional data compression algorithms, the compressed binary information data transmission efficiency of this invention is higher.

[0087] This invention is now complete.

[0088] In summary, this invention converts wireless network data into a binary data sequence. Based on the distribution of binary codes in the information data segments within the binary data sequence, it obtains the bit information overlap degree at each bit position. Based on the correlation between the data binary sets of corresponding bit positions between adjacent information data segments, it obtains the information correlation coefficient. Based on the similarity distribution of the bit information overlap degree and the information correlation coefficient, it obtains the information data compressibility corresponding to each position. Based on the information data compressibility, it adaptively selects a compression coding window to complete the compression and transmission of the wireless network data. This invention's process of adaptively selecting a compression coding window based on information data compressibility improves the data matching hit rate and compression effect during the compression process, further enhancing the transmission efficiency of network data.

[0089] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0090] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for fast transmission of wireless network data, characterized in that, The method comprises: obtaining a binary information data sequence to be transmitted in a wireless network, and dividing the binary information data sequence into at least two information data segments with a preset byte length; obtaining a bit information coincidence degree corresponding to each bit position according to a distribution of subsequent binary codes of each bit position in each information data segment, and extending the bit information coincidence degree backward according to each bit position in each information data segment to obtain a data binary set of each bit position; in the binary information data sequence, obtaining a corresponding information correlation coefficient according to a correlation degree between the data binary set of the corresponding bit position of each information data segment and the adjacent next information data segment; constructing a binary tuple according to the bit information coincidence degree corresponding to each bit position in each information data segment and the information correlation coefficient, and obtaining an information data compressibility of each bit position in each information data segment according to a distribution of a similarity between the binary tuple of each bit position and each subsequent position in each information data segment; obtaining a compression encoding window corresponding to each bit position in each information data segment according to the information data compressibility and a preset buffer length adjustment coefficient, and completing dynamic compression of the binary information data sequence according to the compression encoding window, and performing network transmission on the binary information data sequence after dynamic compression; The method for obtaining the bit information coincidence degree comprises: counting subsequent binary codes of each bit position in a target information data segment, performing logical operation on the binary code of a target bit position in the target information data segment and the binary codes of each subsequent bit position, and obtaining a bit information coincidence degree of the target bit position in the target information data segment according to a logical operation result; changing the target bit position to obtain the bit information coincidence degree of each bit position in the target information data segment, and changing the target information data segment to obtain the bit information coincidence degree of each bit position in each information data segment; The method for obtaining the data binary set comprises: counting a target bit information coincidence degree corresponding to a target bit position in a target information data segment, obtaining a bit string length corresponding to the target bit position according to a sum of the target bit information coincidence degree and a numerical value 1, combining continuous binary codes to obtain binary bit strings with different lengths with the binary code corresponding to the target bit position as a starting point, and constructing a corresponding data binary set according to all binary bit strings of the target bit position; changing the target bit position to obtain the data binary set of each bit position in the target information data segment, and changing the target information data segment to obtain the data binary set of each bit position in each information data segment; The method for obtaining the information correlation coefficient comprises: The next information data segment adjacent to the target information data segment in the binary information data sequence is recorded as a target adjacent information data segment, the number of identical binary bit strings between two data binary sets corresponding to the target bit position of the target information data segment and the target adjacent information data segment is obtained as an identical bit string number, and an information correlation coefficient of the target bit position in the target information data segment is obtained according to a ratio of the identical bit string number to a total number of binary bit strings in the two data binary sets; The information correlation coefficient of each bit position in the target information data segment is obtained by changing the target bit position, and the information correlation coefficient of each bit position in each information data segment is obtained by changing the target information data segment; The information data compressibility obtaining method comprises: The binary pairs corresponding to the target bit position and each subsequent bit position in the target information data segment are counted, the cosine similarity between the binary pairs corresponding to the target bit position and each subsequent bit position is calculated, and the average of the cosine similarity is calculated to obtain the information data compressibility corresponding to the target bit position in the target information data segment; The information data compressibility of each bit position in the target information data segment is obtained by changing the target bit position, and the information data compressibility of each bit position in each information data segment is obtained by changing the target information data segment; The compression encoding window obtaining method comprises: The product of the information data compressibility corresponding to each bit position in each information data segment and a preset buffer length adjustment coefficient is calculated, the product is rounded up as a window length to obtain the compression encoding window corresponding to each bit position in each information data segment.

2. The method of claim 1, wherein, The dynamic compression of the binary information data sequence according to the compression encoding window comprises: The encoding buffer window corresponding to each bit position in each information data segment in the LZ77 compression algorithm is replaced by the corresponding compression encoding window, and the dynamic compression of the binary information data sequence is completed.

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