CN112511276B - Data processing method and device - Google Patents
Data processing method and device Download PDFInfo
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- CN112511276B CN112511276B CN202011327916.XA CN202011327916A CN112511276B CN 112511276 B CN112511276 B CN 112511276B CN 202011327916 A CN202011327916 A CN 202011327916A CN 112511276 B CN112511276 B CN 112511276B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/12—Arrangements for detecting or preventing errors in the information received by using return channel
- H04L1/16—Arrangements for detecting or preventing errors in the information received by using return channel in which the return channel carries supervisory signals, e.g. repetition request signals
- H04L1/18—Automatic repetition systems, e.g. Van Duuren systems
- H04L1/1867—Arrangements specially adapted for the transmitter end
Abstract
The embodiment of the application discloses a data processing method and device. According to the technical scheme provided by the embodiment of the application, the retransmission analysis model is constructed according to the historical transmission characteristics and the historical data characteristics, the probability that data needs to be retransmitted when the data is transmitted through the current data transmission channel is analyzed based on the retransmission analysis model, and when the retransmission probability reaches the preset condition, the data is directly transmitted twice, so that the time for transmitting a retransmission request to a transmitting end when the receiving end part detects that the data is lost is saved, the utilization rate of a communication channel is improved, and the time delay of data transmission is reduced.
Description
Technical Field
The embodiment of the application relates to the technical field of data communication, in particular to a data processing method and device.
Background
With the development of the internet, various network applications need to establish data transmission. However, the transmission network of the internet is not always reliable, and data loss occurs due to various instability in the transmission process.
In the prior art, the problem of data packet loss is solved in that a receiving end confirms that packet loss occurs, a request is made to a sending end for retransmitting data, and the sending end retransmits the whole data packet to the receiving end according to the request, so that the memory consumption is high and the transmission efficiency is low.
Disclosure of Invention
The embodiment of the application provides a data processing method and device, which are used for prejudging whether currently transmitted data needs to be retransmitted or not according to an established retransmission analysis model, so that the time delay caused by sending retransmission requests back and forth is reduced.
In a first aspect, an embodiment of the present application provides a data processing method, including:
constructing a retransmission analysis model according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted by the data transmission channel when the transmission channel corresponds to the historical transmission characteristics;
establishing a current data transmission channel with a receiving end, and acquiring the transmission characteristics of the current data transmission channel;
acquiring data characteristics of data to be sent through the current data transmission channel;
inputting the transmission characteristics and the data characteristics into a retransmission analysis model to output retransmission probability;
and when the retransmission probability reaches a preset condition, sending the data for the second time after sending the data.
Further, the method also comprises the following steps:
and when the retransmission probability does not reach the preset condition, sending the data to a receiving end, and when receiving a retransmission request of the receiving end, sending the data to the receiving end again based on the retransmission request.
Furthermore, the data comprises a plurality of continuous data frames, and each data frame is provided with a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes consistent with the number of data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the sequence of the feature codes of all the data frames in the data.
Further, before the receiving end sends the retransmission request, the method includes:
extracting all feature codes in the data, and arranging the feature codes according to the arrangement sequence of the corresponding data frames to form a series of feature codes;
acquiring the difference position between the serial feature codes and the serial random codes so as to determine the lost data frame in the data; the retransmission request includes an identification code of the lost data frame.
Further, the historical transmission characteristics and the historical data characteristics in the time interval are obtained again at preset time intervals so as to periodically update the retransmission analysis model.
Further, when the retransmission probability does not reach the preset condition and a retransmission request fed back from the receiving end is received, the retransmission request is ignored.
Furthermore, the data comprises a plurality of continuous data frames, and each data frame is provided with a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes with the same number as the data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the feature code sequence of all the data frames in the data;
receiving a second retransmission request fed back from a receiving end, wherein the second retransmission request comprises the difference degree between a series of random codes and a series of feature codes, and the series of feature codes are formed by extracting all feature codes in data and arranging the feature codes according to the arrangement sequence of corresponding data frames;
and when the difference degree is larger than the difference threshold value, retransmitting the data to the receiver.
In a second aspect, an embodiment of the present application provides a data processing apparatus, including:
a model construction module: the retransmission analysis model is constructed according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted by the data transmission channel when the transmission channel corresponds to the historical transmission characteristics;
a channel establishing module: the system comprises a receiving end, a data transmission channel and a data transmission device, wherein the receiving end is used for receiving current data transmitted by a receiving end;
a feature acquisition module: the data transmission device is used for acquiring data characteristics of data to be transmitted through the current data transmission channel;
a retransmission analysis module: for inputting the transmission characteristics and data characteristics into a retransmission analysis model to output a retransmission probability;
a probability comparison module: and the data transmitting unit is used for transmitting the data for the second time after transmitting the data when the retransmission probability reaches a preset condition.
Further, the system also comprises the following modules:
a retransmission request module: and the data sending module is used for sending the data to the receiving end when the retransmission probability does not reach the preset condition, and sending the data to the receiving end again based on the retransmission request when receiving the retransmission request of the receiving end.
Furthermore, the data comprises a plurality of continuous data frames, and each data frame is provided with a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes consistent with the number of data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the sequence of the feature codes of all the data frames in the data.
Further, before the receiving end sends the retransmission request, the method includes:
extracting all feature codes in the data, and arranging the feature codes according to the arrangement sequence of the corresponding data frames to form a series of feature codes;
acquiring the difference position between the serial feature codes and the serial random codes so as to determine the lost data frame in the data; the retransmission request includes an identification code of the lost data frame.
Further, the historical transmission characteristics and the historical data characteristics in the time interval are obtained again at preset time intervals so as to periodically update the retransmission analysis model.
Further, when the retransmission probability does not reach the preset condition and a retransmission request fed back from the receiving end is received, the retransmission request is ignored.
Furthermore, the data comprises a plurality of continuous data frames, and each data frame is provided with a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes with the same number as the data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the feature code sequence of all the data frames in the data;
the data processing apparatus further includes:
a secondary retransmission module: the second retransmission request is used for receiving feedback from the receiving end; the second retransmission request comprises the difference degree between a series of random codes and a series of feature codes, and the series of feature codes are formed by extracting all feature codes in data and arranging the feature codes according to the arrangement sequence of corresponding data frames;
a difference comparison module: and the data retransmission device is used for retransmitting the data to the receiving end when the difference degree is larger than the difference threshold value.
In a third aspect, an embodiment of the present application provides a computer device, including: a memory and one or more processors;
the memory for storing one or more programs;
when the one or more programs are executed by the one or more processors, cause the one or more processors to implement the data processing method of the first aspect.
In a fourth aspect, embodiments of the present application provide a storage medium containing computer-executable instructions for performing the data processing method according to the first aspect when executed by a computer processor.
According to the embodiment of the application, the retransmission analysis model is built according to the historical transmission characteristics and the historical data characteristics, the probability that data needs to be retransmitted when data are transmitted through the current data transmission channel is analyzed based on the retransmission analysis model, and when the retransmission probability reaches the preset condition, the data are directly transmitted twice, so that the time for transmitting a retransmission request to a transmitting end when the receiving end part detects that the data are lost is saved, the utilization rate of a communication channel is improved, and the time delay of data transmission is reduced.
Drawings
Fig. 1 is a flowchart of a data processing method provided in an embodiment of the present application;
FIG. 2 is a flow chart of another data processing method provided by an embodiment of the present application;
FIG. 3 is a flow chart of another data processing method provided by an embodiment of the present application;
fig. 4 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
The embodiment of the application provides a data processing method and device, a retransmission analysis model is built according to historical transmission characteristics and historical data characteristics, the probability that data needs to be retransmitted when data are transmitted through a current data transmission channel is analyzed based on the retransmission analysis model, and when the retransmission probability reaches a preset condition, the data are directly transmitted twice, so that the time for transmitting a retransmission request to a transmitting end when the receiving end detects that the data are lost is saved, the utilization rate of a communication channel is improved, and the time delay of data transmission is reduced.
Example one
Fig. 1 shows a flowchart provided in an embodiment of the present application, and a data processing method provided in an embodiment of the present application may be executed by a data processing apparatus, which may be implemented by hardware and/or software and integrated in a computer device.
The data processing method provided by the embodiment of the invention can be applied between the sending end and the receiving end. The transmitting end and the receiving end communicate with each other through a communication network. The network may be a wide area network, a local area network. The server can be an independent physical server, can also be a server cluster or a distributed system formed by a plurality of physical servers, and can also provide cloud servers of basic cloud computing servers such as a cloud server, a cloud database, cloud computing, cloud communication, a big database, an artificial intelligence platform and the like. The terminal device can be an intelligent device such as a smart phone, a tablet computer, a notebook computer, a desktop computer and an intelligent watch. The connection between the sending end and the receiving end can be through wired network connection or wireless network communication, and can be direct communication or indirect communication. As an application scenario, for example, the sending end may be a terminal device or a server, and when the sending end is a terminal device, the receiving end is a server, and when the sending end is a server, the receiving end is a terminal device. For example, when a user transmits data with another user through a client of the communication software installed on the terminal device, the client sends data input by the user to the server, where the terminal device is a sending end and the server is a receiving end. In another scenario, when a user watches a video through social software installed on a terminal device, a server sends the video to a client of the user, and at this time, a sending end is a receiving end and the server is a sending end.
The following description will be given taking an example in which the data processing apparatus executes a data processing method. Referring to fig. 1, the cable monitoring method based on the smart device includes:
s101: and constructing a retransmission analysis model according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted by the data transmission channel when the transmission channel corresponds to the historical transmission characteristics.
In the embodiment of the present application, the transmission characteristics mainly include network characteristics of a data transmission channel, network signal strength, channel coding, and the like. The data characteristics mainly include data type, data length, coding mode, and the like. A sufficient number of data transmission channels and a sufficient number of data transmitted on the same data transmission channel during a time period are selected as sample capacities, having been taken as a reference. The retransmission analysis model is trained by acquiring the historical transmission characteristics and the historical data characteristics, the trained retransmission analysis model can cover various characteristics, and the analysis requirements of data transmission channels with different transmission characteristics and data with different data characteristics can be met.
S102: and establishing a current data transmission channel with a receiving end, and acquiring the transmission characteristics of the current data transmission channel.
In this step, the transmitting end transmits data to the receiving end. The method comprises the steps that a sending end and a receiving end are connected, namely a current data transmission channel between the sending end and the receiving end is established, and transmission characteristics are obtained according to the characteristics of the data transmission channel.
S103: and acquiring data characteristics of data to be sent through the current data transmission channel.
After the data transmission channel is established, the sending end sends data to the receiving end, and the data characteristics of the data can be acquired.
S104: and inputting the transmission characteristics and the data characteristics into a retransmission analysis model to output retransmission probability.
And inputting the current transmission characteristics and data characteristics into a retransmission analysis model constructed in advance, and outputting retransmission probability by the retransmission analysis model.
S105: and when the retransmission probability reaches a preset condition, sending the data for the second time after sending the data.
The preset condition of the embodiment of the invention is usually a preset numerical value, when the retransmission probability reaches the numerical value, the retransmission probability is high, in order to avoid the time required by the process of waiting for the receiving end to receive the data, then comparing and verifying the data, confirming the data packet loss and then sending the retransmission request, the data is continuously transmitted twice in advance, so that the time for waiting for the receiving end to send the retransmission request can be avoided, the time delay of data transmission is further reduced, and the utilization rate of a communication channel is improved.
Example two
As shown in fig. 2, the present embodiment provides a data processing method, including:
s201: and constructing a retransmission analysis model according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted by the data transmission channel when the transmission channel corresponds to the historical transmission characteristics.
S202: and establishing a current data transmission channel with a receiving end, and acquiring the transmission characteristics of the current data transmission channel.
S203: acquiring data characteristics of data to be sent through the current data transmission channel;
s204: inputting the transmission characteristics and the data characteristics into a retransmission analysis model to output retransmission probability;
s205: judging whether the retransmission probability reaches a preset condition, and when the retransmission probability reaches the preset condition, sending the data for the second time after sending the data; and when the retransmission probability does not reach the preset condition, sending the data to a receiving end, and when receiving a retransmission request of the receiving end, sending the data to the receiving end again based on the retransmission request.
In this embodiment, the data includes a plurality of consecutive data frames, each data frame having a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes consistent with the number of data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the sequence of the feature codes of all the data frames in the data. Where the series of random codes is, for example, ABCDE, the exemplary series has 5 signatures, so it will be appreciated that the data has five data frames, and each data frame is, for example, XXXX-Y, where Y represents a signature, then the data is: XXXXXX-A XXXX-B XXXX-C XXXX-D XXXX-E, ABCDE of series random codes and feature codes of data frames are arranged in a one-to-one correspondence.
Based on the characteristics of the data of the embodiment of the invention, before the receiving end sends the retransmission request, the following steps are executed after the receiving end receives the retransmission request:
and extracting all feature codes in the data, and arranging the feature codes according to the arrangement sequence of the corresponding data frames to form a series of feature codes.
Acquiring the difference position between the serial feature codes and the serial random codes so as to determine the lost data frame in the data; the retransmission request includes an identification code of the lost data frame.
Also described above as an example, all feature codes in the data are extracted, i.e., the "ABCDE" in XXXXX-A XXXX-B XXXXX-C XXXXXX-D XXXXXX-E is extracted, and the "ABCDE" is compared to determine whether it is consistent with the series of random codes. When the data frames are inconsistent, the feature codes are all arranged in sequence in a one-to-one correspondence mode, and therefore missing data frames can be reflected quickly. For example, the extracted feature code of the data is ACDE, the series random code is ABCDE, and the difference position between the extracted feature code and the ABCDE is compared, so that the feature code at the second position in the sequence is missing, that is, the data frame corresponding to the feature code is true, and when a retransmission request is sent, the identification code of the data frame is sent to the sending end, so that the sending end sends the data frame to the receiving end without uploading all data again, thereby avoiding increasing the network transmission pressure.
As a preferred implementation manner of this embodiment, the historical transmission features and the historical data features in the time interval are obtained again at preset time intervals, so as to periodically update the retransmission analysis model. By regularly updating and refining the retransmission analysis model, the accuracy and the adaptability of the retransmission analysis model can be improved.
EXAMPLE III
Referring to fig. 3, an embodiment of the present invention further provides another data processing method, including the following steps:
s301: and constructing a retransmission analysis model according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted by the data transmission channel when the transmission channel corresponds to the historical transmission characteristics.
S302: and establishing a current data transmission channel with a receiving end, and acquiring the transmission characteristics of the current data transmission channel.
S303: acquiring data characteristics of data to be sent through the current data transmission channel;
s304: inputting the transmission characteristics and the data characteristics into a retransmission analysis model to output retransmission probability;
s305: and judging whether the retransmission probability reaches a preset condition, when the retransmission probability reaches the preset condition, sending the data for the second time after sending the data, and when the retransmission probability does not reach the preset condition and a retransmission request fed back from a receiving end is received, ignoring the retransmission request.
The difference between this embodiment and the second embodiment is that, when it is determined that the predetermined condition is not met according to the retransmission probability, the transmitting end does not theoretically wait for the retransmission request of the receiving end, because the retransmission probability is low, the transmitting end theoretically considers that no retransmission is needed or the receiving end erroneously transmits the retransmission request, and therefore ignores the retransmission request.
But further, the data comprises a plurality of continuous data frames, and each data frame is provided with a characteristic code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes consistent with the number of data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the sequence of the feature codes of all the data frames in the data.
When the retransmission request sent by the receiving end for the first time is ignored by the sending end and the receiving end insists on the condition that the retransmission is needed, the second retransmission request is sent. At a sending end, receiving a second retransmission request fed back from a receiving end, wherein the second retransmission request comprises the difference degree between a series of random codes and a series of feature codes, and the series of feature codes are formed by extracting all feature codes in data and arranging the feature codes according to the arrangement sequence of corresponding data frames; the sending end further compares the difference degree with a preset difference threshold value, and resends the data to the receiving end when the difference degree is greater than the difference threshold value. When the difference degree is lower than the difference threshold value, the sending end considers that the receiving end has the capability of recovering the data, so that the channel utilization rate is improved in order to avoid occupying a communication channel, and the sending end defaults that the data is not retransmitted.
For example, the data sent by the sending end is: XXXXXX-A XXXX-B XXXX-C XXXX-D XXXX-E, and the data received by the receiving end is: XXXXXX-A XXXX-C XXXX-D XXXX-E. Extracting the feature code of the data received by the receiving end as ACDE, and the series random code as ABCDE, comparing the difference degree between the ACDE and the ABCDE, wherein the visible difference is the data frame corresponding to the missing feature code B, and the missing rate can be calculated to be one fifth, namely the difference degree is one fifth.
Example four
As shown in fig. 4, the present embodiment further provides a data processing apparatus, which includes a model building module 401, a channel building module 402, a feature obtaining module 403, a retransmission analyzing module 404, and a probability comparing module 405. The model construction module 401 is configured to construct a retransmission analysis model according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted through the data transmission channel when the transmission channel corresponds to the historical transmission characteristics; the channel establishing module 402 is configured to establish a current data transmission channel with a receiving end, and obtain a transmission characteristic of the current data transmission channel; the characteristic obtaining module 403 is configured to obtain data characteristics of data to be sent through the current data transmission channel; the retransmission analysis module 404 is configured to input the transmission characteristics and the data characteristics into a retransmission analysis model to output a retransmission probability; the probability comparison module 405 is configured to send the data for the second time after sending the data when the retransmission probability reaches a preset condition.
Preferably, the system further comprises a retransmission request module: and the data sending module is used for sending the data to the receiving end when the retransmission probability does not reach the preset condition, and sending the data to the receiving end again based on the retransmission request when receiving the retransmission request of the receiving end.
In a further preferred embodiment, the data comprises a plurality of consecutive data frames, and each data frame has a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes consistent with the number of data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the sequence of the feature codes of all the data frames in the data. Therefore, the receiving end may perform the following operations before sending the retransmission request:
extracting all feature codes in the data, and arranging the feature codes according to the arrangement sequence of the corresponding data frames to form a series of feature codes; acquiring the difference position between the serial feature codes and the serial random codes so as to determine the lost data frame in the data; the retransmission request includes an identification code of the lost data frame.
In the prior art, the data processing apparatus and the data processing method provided in the embodiments of the present invention correspond to each other, and the historical transmission characteristics and the historical data characteristics in the time interval are obtained again at preset time intervals, so as to periodically update the retransmission analysis model.
In another implementation aspect, when the retransmission probability does not reach the preset condition and a retransmission request fed back from the receiving end is received, the retransmission request is ignored.
In more detail, the data comprises a plurality of continuous data frames, and each data frame is provided with a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes consistent with the number of data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the sequence of the feature codes of all the data frames in the data.
Based on this, the data processing apparatus further includes: the secondary retransmission module is used for receiving a secondary retransmission request fed back from the receiving end; the second retransmission request comprises the difference degree between a series of random codes and a series of feature codes, and the series of feature codes are formed by extracting all feature codes in data and arranging the feature codes according to the arrangement sequence of corresponding data frames; and the difference comparison module is used for retransmitting the data to the receiving end when the difference degree is greater than the difference threshold value.
EXAMPLE five
An embodiment of the present invention further provides a computer device, including: a memory and one or more processors;
the memory for storing one or more programs;
when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the data processing method according to the first aspect, the data processing method includes constructing a retransmission analysis model according to historical transmission characteristics of a data transmission channel and historical data characteristics of data transmitted through the data transmission channel when the transmission channel corresponds to the historical transmission characteristics; establishing a current data transmission channel with a receiving end, and acquiring the transmission characteristics of the current data transmission channel; acquiring data characteristics of data to be sent through the current data transmission channel; inputting the transmission characteristics and the data characteristics into a retransmission analysis model to output retransmission probability; and when the retransmission probability reaches a preset condition, sending the data for the second time after sending the data.
EXAMPLE six
Embodiments of the present application further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the data processing method provided in the foregoing embodiments, the data processing method including: constructing a retransmission analysis model according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted by the data transmission channel when the transmission channel corresponds to the historical transmission characteristics; establishing a current data transmission channel with a receiving end, and acquiring the transmission characteristics of the current data transmission channel; acquiring data characteristics of data to be sent through the current data transmission channel; inputting the transmission characteristics and the data characteristics into a retransmission analysis model to output retransmission probability; and when the retransmission probability reaches a preset condition, sending the data for the second time after sending the data.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in a first computer system in which the program is executed, or may be located in a different second computer system connected to the first computer system through a network (such as the internet). The second computer system may provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium provided in the embodiments of the present application contains computer-executable instructions, and the computer-executable instructions are not limited to the data processing method described above, and may also perform related operations in the data retransmission provided in any embodiments of the present application.
The data processing apparatus, the device, and the storage medium provided in the foregoing embodiments may execute the data processing method provided in any embodiment of the present application, and refer to the data processing method provided in any embodiment of the present application without detailed technical details described in the foregoing embodiments.
The foregoing is considered as illustrative of the preferred embodiments of the invention and the technical principles employed. The present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.
Claims (7)
1. A data processing method, comprising:
constructing a retransmission analysis model according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted by the data transmission channel when the transmission channel corresponds to the historical transmission characteristics; the data comprises a plurality of continuous data frames, and each data frame is provided with a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes with the same number as the data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the feature code sequence of all the data frames in the data;
establishing a current data transmission channel with a receiving end, and acquiring the transmission characteristics of the current data transmission channel;
acquiring data characteristics of data to be sent through the current data transmission channel;
inputting the transmission characteristics and the data characteristics into a retransmission analysis model to output retransmission probability;
when the retransmission probability reaches a preset condition, after the data is sent, sending the data for the second time;
when the retransmission probability does not reach the preset condition, sending the data to the receiving end, and when receiving the retransmission request of the receiving end, sending the data to the receiving end again based on the retransmission request,
before the receiving end sends the retransmission request, the method comprises the following steps:
extracting all feature codes in the data, and arranging the feature codes according to the arrangement sequence of the corresponding data frames to form a series of feature codes;
acquiring the difference position between the serial feature codes and the serial random codes so as to determine the lost data frame in the data; the retransmission request includes an identification code of the lost data frame.
2. The data processing method of claim 1, wherein the historical transmission characteristics and the historical data characteristics in the time interval are obtained again at preset time intervals so as to periodically update the retransmission analysis model.
3. The data processing method of claim 1, wherein when the retransmission probability does not meet a predetermined condition and a retransmission request fed back from a receiving end is received, the retransmission request is ignored.
4. A data processing method according to claim 3, wherein the data comprises a plurality of consecutive data frames, each data frame having a signature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes with the same number as the data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the feature code sequence of all the data frames in the data;
receiving a second retransmission request fed back from a receiving end, wherein the second retransmission request comprises the difference degree between a series of random codes and a series of feature codes, and the series of feature codes are formed by extracting all feature codes in data and arranging the feature codes according to the arrangement sequence of corresponding data frames;
and when the difference degree is larger than the difference threshold value, retransmitting the data to the receiving end.
5. A data processing apparatus, comprising:
a model construction module: the retransmission analysis model is constructed according to the historical transmission characteristics of the data transmission channel and the historical data characteristics of the data transmitted by the data transmission channel when the transmission channel corresponds to the historical transmission characteristics; the data comprises a plurality of continuous data frames, and each data frame is provided with a feature code and an identification code; when data is sent to a receiving end every time, a series of random codes corresponding to the data are sent at the same time, the series of random codes are formed by arranging a plurality of feature codes with the same number as the data frames in the data, and the feature codes in the series of random codes are arranged in a one-to-one correspondence mode according to the feature code sequence of all the data frames in the data;
a channel establishing module: the system comprises a receiving end, a data transmission channel and a data transmission device, wherein the receiving end is used for receiving current data transmitted by a receiving end;
a feature acquisition module: the data transmission device is used for acquiring data characteristics of data to be transmitted through the current data transmission channel;
a retransmission analysis module: for inputting the transmission characteristics and data characteristics into a retransmission analysis model to output a retransmission probability;
a probability comparison module: the data retransmission method comprises the steps of sending the data for the second time after sending the data when the retransmission probability reaches a preset condition;
when the retransmission probability does not reach the preset condition, sending the data to the receiving end, and when receiving the retransmission request of the receiving end, sending the data to the receiving end again based on the retransmission request,
before the receiving end sends the retransmission request, the method comprises the following steps:
extracting all feature codes in the data, and arranging the feature codes according to the arrangement sequence of the corresponding data frames to form a series of feature codes;
acquiring the difference position between the serial feature codes and the serial random codes so as to determine the lost data frame in the data; the retransmission request includes an identification code of the lost data frame.
6. A computer device, comprising: a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement a data processing method as claimed in any one of claims 1-4.
7. A storage medium containing computer-executable instructions for performing the data processing method of any one of claims 1 to 4 when executed by a computer processor.
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Family Cites Families (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8730825B2 (en) * | 2009-05-26 | 2014-05-20 | Indian Institute Of Science | Packet retransmission optimization in wireless network |
| CN103533045B (en) * | 2013-10-12 | 2017-12-29 | 丁贤根 | A kind of method fault-tolerant for PCIE data link layer high-performance |
| CN104219170B (en) * | 2014-09-04 | 2017-08-08 | 暨南大学 | The bag dispatching method retransmitted in wireless network based on probability |
| CN108155967B (en) * | 2016-12-05 | 2020-04-14 | 中国移动通信有限公司研究院 | Method and device for transmitting sensing data, sensor, gateway and system |
| CN109428688B (en) * | 2017-09-04 | 2021-11-09 | 中国移动通信有限公司研究院 | HARQ retransmission time dynamic configuration method, device and medium |
| CN109547169B (en) * | 2017-09-22 | 2021-12-21 | 珠海市魅族科技有限公司 | Data retransmission request method, request device, site equipment and access point equipment |
| CN108880753A (en) * | 2018-06-20 | 2018-11-23 | 深圳无线电检测技术研究院 | A kind of acquisition methods and system of grid equipment operation data |
| CN109194674A (en) * | 2018-09-20 | 2019-01-11 | 浪潮电子信息产业股份有限公司 | A kind of processing method and processing device of communication data |
| CN109302395A (en) * | 2018-10-09 | 2019-02-01 | 深圳市亿联智能有限公司 | It is a kind of for improving the error correction method of correcting data error efficiency under high bit-error environment |
| CN111182644B (en) * | 2019-12-24 | 2022-02-08 | 北京邮电大学 | Joint retransmission URLLC resource scheduling method based on deep reinforcement learning |
| CN116996173A (en) * | 2019-12-27 | 2023-11-03 | 南京中感微电子有限公司 | Data transmission method, device and system |
| CN111510259B (en) * | 2020-03-19 | 2021-07-13 | 西安电子科技大学 | Novel retransmission method based on ultra-reliable low-delay communication and NOMA (non-orthogonal multiple Access) technology |
| CN111371534B (en) * | 2020-06-01 | 2020-09-18 | 腾讯科技（深圳）有限公司 | Data retransmission method and device, electronic equipment and storage medium |
| CN111935550B (en) * | 2020-08-06 | 2021-10-12 | 北京邮电大学 | Data packet scheduling method and device based on timeliness and electronic equipment |
-
2020
- 2020-11-24 CN CN202011327916.XA patent/CN112511276B/en active Active
Non-Patent Citations (2)
| Title |
|---|
| "Prototype of radio signal retransmission system of digital satellite TV broadcasting in 11 GHz band to be used in higher education training";G. L. Avdeyenko;《2012 22nd International Crimean Conference "Microwave & Telecommunication Technology"》;20121231;全文 * |
| "下一代移动通信系统中混合自动重传机制的研究 ";谢刚;《中国博士学位论文全文数据库信息科技辑》;20070423;全文 * |
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