CN115589601B - Parameter processing method, device, equipment and storage medium - Google Patents
Parameter processing method, device, equipment and storage mediumInfo
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Abstract
本发明公开了一种参数处理方法、装置、设备及存储介质。其中，所述方法包括：输入工业参数以及服务等级协议(SLA)指标参数；所述工业参数表征工业拍摄设备的相关参数；所述SLA指标参数表征所述工业拍摄设备采集的图像的检测成功率；对输入的工业参数以及SLA指标参数进行映射，得到网络指标；所述网络指标表征将所述工业拍摄设备采集的图像传输至网络设备所需的网络需求；输出所述网络指标。
The present invention discloses a parameter processing method, apparatus, device, and storage medium. The method includes: inputting industrial parameters and service level agreement (SLA) indicator parameters; the industrial parameters represent relevant parameters of industrial camera equipment; the SLA indicator parameters represent the detection success rate of images captured by the industrial camera equipment; mapping the input industrial parameters and SLA indicator parameters to obtain network indicators; the network indicators represent the network requirements required to transmit images captured by the industrial camera equipment to a network device; and outputting the network indicators.
Description
Technical Field
The present invention relates to the field of wireless technologies, and in particular, to a method, an apparatus, a device, and a storage medium for processing parameters.
Background
With the rapid development of Network slicing technology, service level agreement (SLA, service Level Agreement) requirement decomposition can be implemented by a Communication Service Management Function (CSMF) entity and a Network Slicing Management Function (NSMF) entity in a slicing architecture. The SLA demand decomposing process comprises the steps of firstly inputting a general slicing template into a CSMF entity, then decomposing the SLA demand by the CSMF entity by utilizing the input general slicing template to obtain an end-to-end index configuration file, and sending the end-to-end index configuration file to an NSMF entity, and finally decomposing the received end-to-end index configuration file by the NSMF entity to obtain an index configuration file of a special domain. However, because all network indexes in the universal slice template are manually input, automatic conversion from industrial parameters to network indexes cannot be realized, and SLA (SLA requirement decomposition) cannot be realized in an industrial machine vision scene.
Disclosure of Invention
In view of this, embodiments of the present invention desirably provide a parameter processing method, apparatus, device, and storage medium.
The technical scheme of the embodiment of the invention is realized as follows:
At least one embodiment of the present invention provides a parameter processing method, including:
Inputting industrial parameters and SLA index parameters, wherein the industrial parameters represent related parameters of industrial photographing equipment, and the SLA index parameters represent the detection success rate of images acquired by the industrial photographing equipment;
Mapping the input industrial parameters and SLA index parameters to obtain network indexes, wherein the network indexes represent network requirements required by transmitting images acquired by the industrial shooting equipment to network equipment;
And outputting the network index.
In addition, according to at least one embodiment of the invention, the industrial parameters comprise information source parameters of the industrial photographing equipment and processing capacity parameters of the industrial photographing equipment, and the mapping of the input industrial parameters and SLA index parameters to obtain network indexes comprises the following steps:
quantizing the input information source parameters and SLA index parameters to obtain service indexes;
and mapping the service index into a network index by utilizing the processing capacity parameter.
Furthermore, according to at least one embodiment of the present invention, the quantifying the input source parameters and SLA index parameters to obtain the service index includes:
quantizing input information source parameters to obtain a first service index and a second service index, wherein the first service index represents the data volume of a single-frame image;
and quantifying the SLA index parameter to obtain a third service index, wherein the third service index represents the packet loss rate allowed by the service.
In addition, according to at least one embodiment of the present invention, the source parameters include a first parameter, a second parameter and a third parameter, and the quantizing the input source parameters to obtain a first traffic index and a second traffic index includes:
The method comprises the steps of quantifying a first parameter to obtain a first service index, quantifying a second parameter and a third parameter to obtain a second service index, wherein the first parameter represents the resolution of the industrial photographing equipment, the second parameter represents the time interval of the industrial photographing equipment for collecting images, and the third parameter represents the number of images collected by the industrial photographing equipment in unit time.
Furthermore, according to at least one embodiment of the present invention, the mapping the traffic index to a network index using the processing capability parameter includes:
Mapping the first service index into a first network index by utilizing the processing capacity parameter, wherein the first network index represents a network transmission rate required for transmitting images acquired by the industrial photographing equipment;
Mapping the second service index into a second network index by utilizing the processing capacity parameter, wherein the second network index represents network transmission delay required for transmitting the image acquired by the industrial photographing equipment;
And mapping the third service index into a third network index by utilizing the processing capacity parameter, wherein the third network index represents the network reliability required by transmitting the image acquired by the industrial photographing equipment.
Furthermore, according to at least one embodiment of the present invention, the processing capability parameter includes a bit depth of an image acquired by the industrial photographing apparatus and a compression rate of the image by the industrial photographing apparatus, and the mapping the first traffic index to a first network index using the processing capability parameter includes:
And performing first operation on the bit depth, the compression rate and the numerical value corresponding to the first service index to obtain an operation result, and taking the obtained operation result as the first network index.
Furthermore, according to at least one embodiment of the present invention, the processing capability parameter includes a first time delay for the industrial photographing apparatus to collect an image, a second time delay for the industrial photographing apparatus to compress the image, and a third time delay for the industrial photographing apparatus to analyze the image, and the mapping the second traffic index to a second network index using the processing capability parameter includes:
and performing a second operation on the first time delay, the second time delay, the third time delay and the numerical value corresponding to the second service index to obtain an operation result, and taking the obtained operation result as a second network index.
Furthermore, according to at least one embodiment of the present invention, the processing capability parameter includes a bit depth of an image acquired by the industrial photographing apparatus, and the mapping the third traffic index to a third network index using the processing capability parameter includes:
Performing third operation on the bit depth and the numerical value corresponding to the third service index to obtain an operation result;
and taking the operation result as a third network index.
At least one embodiment of the present invention provides a parameter processing apparatus including:
The system comprises an input unit, a detection unit and a detection unit, wherein the input unit is used for inputting industrial parameters and SLA index parameters, the industrial parameters represent relevant parameters of industrial shooting equipment, and the SLA index parameters represent the detection success rate of images acquired by the industrial shooting equipment;
the processing unit is used for mapping the input industrial parameters and SLA index parameters to obtain network indexes, wherein the network indexes represent network requirements required by transmitting images acquired by the industrial shooting equipment to network equipment;
and the output unit is used for outputting the network index.
At least one embodiment of the present invention provides a communication device comprising:
the system comprises a communication interface, an industrial photographing device, an SLA index parameter, a detection success rate and a control unit, wherein the communication interface is used for inputting industrial parameters and the SLA index parameter, the industrial parameters represent related parameters of the industrial photographing device, and the SLA index parameter represents the detection success rate of images acquired by the industrial photographing device;
The system comprises a processor, a network index, a network device and an industrial shooting device, wherein the processor is used for mapping input industrial parameters and SLA index parameters to obtain a network index;
The communication interface is further configured to output the network indicator.
At least one embodiment of the present invention provides a communication device including a processor and a memory for storing a computer program capable of running on the processor, wherein the processor is configured to execute the steps of any of the methods on the communication device side when the computer program is run.
At least one embodiment of the present invention provides a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any of the methods described above.
The parameter processing method, the device, the equipment and the storage medium provided by the embodiment of the invention are used for inputting the industrial parameters and the SLA index parameters, wherein the industrial parameters represent the related parameters of the industrial shooting equipment, the SLA index parameters represent the detection success rate of the images acquired by the industrial shooting equipment, the input industrial parameters and the SLA index parameters are mapped to obtain the network index, the network index represents the network requirement required by transmitting the images acquired by the industrial shooting equipment to the network equipment, and the network index is output. By adopting the technical scheme provided by the embodiment of the invention, the input industrial parameters and SLA index parameters are automatically converted, the network index is output, and the network index is not required to be set through manual operation, so that the automatic conversion from the industrial parameters to the network index can be realized, and the SLA demand decomposition can be realized in an industrial machine vision scene.
Drawings
FIG. 1 is a schematic diagram of an implementation flow for decomposing SLA requirements in the related art;
FIG. 2 is a schematic diagram of an implementation flow of a parameter processing method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of mapping input industrial parameters and SLA index parameters to network indices according to an embodiment of the present invention;
FIG. 4 is a flowchart of a specific implementation of a parameter processing method according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of an embodiment of the invention capturing images by an industrial camera;
FIG. 6 is a schematic diagram of an implementation flow chart of quantifying and mapping input industrial parameters and SAL indicator parameters to network indicators according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a parameter processing apparatus according to an embodiment of the present invention;
Fig. 8 is a schematic diagram of a composition structure of a network device according to an embodiment of the present invention.
Detailed Description
Prior to introducing the technical solution of the embodiment of the present invention, a description will be given of related technology.
FIG. 1 is a schematic diagram of SLA requirement decomposition in the related art, and as shown in FIG. 1, the SLA requirement decomposition is implemented by a CSMF entity and an NSMF entity. Specifically, first, network level metrics input to the CSMF entity are constrained based on a Generic Slice Template (GST). The CSMF entity then breaks down the incoming SLA requirements using a GST template to obtain an end-to-end index profile serviceProfile, and inputs serviceProfile profile to the NSMF entity. Finally, the NSMF entity decomposes serviceProfile the configuration file to obtain index configuration file sliceprofile for the subzones (wireless subzone, transport subzone, core network subzone). SLA requirement decomposition by CSMF entity and NSMF entity is essentially a mapping of network requirements to network requirements.
However, in the process of decomposing the SLA requirement, the technical defects are that:
First, the input template GST of the CSMF directly specifies network-level metrics, such as isolation, cell capacity, transmission rate, etc., and cannot translate and decompose requirements based on the original industrial traffic model and industrial traffic requirements.
Second, each network parameter in the GST template is obtained by converting an industrial requirement into a network requirement, and the process of converting the industrial requirement into the network requirement is a manual, offline and static process, that is, automatic conversion from an industrial language to a network language cannot be realized.
Third, the SLA requirement decomposition flow needs to be implemented based on the whole set of slice management architecture, namely, through CSMF entity, NSMF entity and NSSMF entity in subzone in the large network. Because the whole set of slicing system is not mature and is difficult to commercial at present, the requirements of light opening, rapid deployment and service pull-through of local scenes are difficult to meet in a current period of time, and the application of 5G+ industrial Internet is rapid in development, especially in industrial machine vision quality inspection scenes realized by utilizing 5G large bandwidth, so that how to realize the requirement decomposition in the industrial machine vision scenes becomes trend more and more.
Based on the above, in the embodiment of the invention, industrial parameters and SLA index parameters are input, the industrial parameters represent relevant parameters of industrial photographing equipment, the SLA index parameters represent the detection success rate of images acquired by the industrial photographing equipment, the input industrial parameters and SLA index parameters are mapped to obtain network indexes, the network indexes represent network requirements required by transmitting the images acquired by the industrial photographing equipment to network equipment, and the network indexes are output.
The implementation process of the parameter processing method according to the embodiment of the present invention is described below with reference to specific embodiments.
Fig. 2 is a schematic flow chart of an implementation of a parameter processing method according to an embodiment of the present invention, as shown in fig. 2, the method includes steps 201 to 203:
Step 201, inputting industrial parameters and SLA index parameters, wherein the industrial parameters represent relevant parameters of industrial photographing equipment, and the SLA index parameters represent the detection success rate of images acquired by the industrial photographing equipment.
It is understood that the industrial camera device may refer to an industrial camera in a machine vision inspection scene.
It is understood that the relevant parameters of the industrial photographing apparatus, i.e., industrial parameters, may include a camera frame rate, a photographing beat, a camera resolution, an image bit depth, an image compression rate, an image acquisition delay, a compression processing delay, an analysis reasoning delay, and the like.
It can be understood that the detection success rate of the image acquired by the industrial photographing device, namely the SLA index parameter, can be obtained by the following steps:
step one, acquiring a certain number of images through the industrial shooting equipment;
respectively extracting information from a certain number of images acquired by the industrial shooting equipment, and detecting whether the corresponding images are qualified or not by using the extracted information;
And thirdly, counting the duty ratio of the number of qualified images to the total number of images to obtain the detection success rate.
And 202, mapping the input industrial parameters and SLA index parameters to obtain network indexes, wherein the network indexes represent network requirements required by transmitting images acquired by the industrial photographing equipment to network equipment.
It can be appreciated that mapping the input industrial parameters and SLA index parameters to obtain the network index may include the following steps:
step one, quantizing input industrial parameters and SLA index parameters to obtain service indexes;
the service index may refer to an index of a service layer, and specifically may be a service quality parameter presented for a specific service and felt by a user.
And step two, mapping the service index to obtain a network index.
The network index may refer to an index of a network layer, and specifically may be a network requirement required for transmitting an image acquired by the industrial photographing device to a network device.
It will be appreciated that, given that there may be a number of types of industrial parameters that are input, one type of industrial parameter may have a correlation with the industrial photographing apparatus, and another type of industrial parameter may have a correlation with the performance of the industrial photographing apparatus for processing an image, so that the industrial parameters may be divided into two types, one type of industrial parameter is referred to as a source parameter of the industrial photographing apparatus, and the other type of industrial parameter is referred to as a processing capability parameter of the industrial photographing apparatus.
That is, after the input industrial parameters are divided into two types of industrial parameters, the information source parameters and SLA index parameters of the industrial photographing device can be quantized to obtain service indexes, and the obtained service indexes are mapped by utilizing the processing capacity parameters of the industrial photographing device to obtain network indexes, as shown in FIG. 3.
And 203, outputting the network index.
It will be appreciated that the output network metrics may specifically include:
Network transmission rate;
Network transmission delay;
network transmission reliability.
It will be appreciated that the network metrics may be output to the CSMF entity in the sliced architecture for the CSMF entity to implement the resolution SLA requirements.
It should be noted that, the application scenario of the parameter processing method provided by the embodiment of the present invention may be an industrial machine vision detection service scenario. The principle of machine vision is that after an industrial camera shoots and collects images, the images are transmitted to a special image analysis processing system, and the system analyzes and processes key features of the images to guide technical application of object feature recognition and judgment. The method is widely applied to the fields of working condition monitoring, finished product inspection, quality control and the like in industrial Internet scenes.
In the embodiment of the invention, the network index is not required to be set for the input industrial parameters through manual operation, but the input industrial parameters and SLA index parameters are automatically converted, and the network index is output, so that the automatic demand decomposition is realized.
That is, the input industrial parameters and SLA index parameters are used as targets to decompose each service index associated with the input, and each service index is mapped to a corresponding network index.
Fig. 4 is a schematic flow chart of an implementation of a parameter processing method according to an embodiment of the present invention, as shown in fig. 4, the method includes steps 401 to 406:
and step 401, inputting information source parameters of industrial photographing equipment, processing capacity parameters of the industrial photographing equipment and SLA index parameters.
It will be appreciated that the input source parameters of the industrial camera may be determined by the accuracy of the industrial camera and the tact.
Table 1 is a schematic representation of the input source parameters of the industrial photographing apparatus, the processing capacity parameters of the industrial photographing apparatus, and SLA index parameters, as shown in table 1. The input information source parameters of the industrial photographing device comprise a camera frame rate, a period time, a resolution, a bit depth and an image compression rate. The input processing capacity parameters of the industrial photographing equipment comprise image acquisition time delay, compression processing time delay and analysis reasoning time delay. The input SLA index parameters include the success rate of photo detection.
TABLE 1
And step 402, quantizing the input information source parameters to obtain a first service index and a second service index.
It can be understood that the first service index represents the data size of the single-frame image, and the second service index represents the allowed end-to-end service delay of the single-frame image.
The method for quantifying the input information source parameters to obtain a first service index and a second service index comprises the following steps:
Quantifying a first parameter to obtain a first business index, wherein the first parameter characterizes the resolution of the industrial photographing equipment;
And quantifying a second parameter and a third parameter to obtain a second service index, wherein the second parameter represents the time interval of the industrial photographing equipment for collecting images, and the third parameter represents the number of images collected by the industrial photographing equipment in unit time.
It can be understood that the first parameter may be quantized according to the formula (1) to obtain a first traffic index, which is specifically as follows:
Q=Pv×Ph (1)
Wherein, Q represents a first business index, namely the data size of a single frame image, the unit is bytes, and one byte represents one pixel point. Pv×Ph represents the first parameter, i.e., the resolution of the industrial photographing apparatus. The detection accuracy requirement may determine the parameter specification, i.e. resolution, of the industrial photographing device.
It can be understood that the second parameter and the third parameter may be quantized according to the formula (2) to obtain the second service index, which is specifically as follows:
Wherein t E represents a second traffic indicator, i.e. the end-to-end traffic delay allowed by the single frame image. CYCLE TIME denotes the second parameter, i.e. the time interval during which the industrial camera acquires images. f represents the third parameter, namely the number of images acquired by the industrial photographing device in a unit time. CYCLE TIME and f can determine the requirement of detection time, if a certain detection rhythm is to be maintained, this means that the acquisition, transmission, processing and obtaining of analysis results of the images are to be completed within the shooting interval time.
And 403, quantifying the SLA index parameters to obtain a third service index.
It can be understood that the third traffic indicator characterizes the packet loss rate allowed by the traffic.
It can be understood that the SLA index parameter may be quantized according to the formula (3) to obtain a third service index, which is specifically as follows:
L≤n×(1-S) (3)
Wherein L represents a third traffic indicator, i.e. a packet loss rate allowed by traffic. S represents SLA index parameter, namely detection success rate. The photo ratio of detection failure or abnormality is (1-S), assuming that image blurring is caused when n data packets are lost in each frame of image, detection abnormality is considered to occur.
And step 404, mapping the first service index into a first network index by using the processing capacity parameter.
It is understood that the first network indicator characterizes a network transmission rate required to transmit images acquired by the industrial photographing device.
In one embodiment, the processing capability parameter includes a bit depth of an image acquired by the industrial photographing device and a compression rate of the industrial photographing device for performing compression processing on the image, and the mapping the first service index into a first network index by using the processing capability parameter includes:
Performing first operation on the bit depth, the compression rate and the numerical value corresponding to the first service index to obtain an operation result;
And taking the obtained operation result as the first network index.
It can be understood that in order to ensure the detection accuracy, in the industrial machine vision detection scene, an industrial photographing device with more than 500 ten thousand pixels is generally adopted to collect the high-definition image, and high requirements are put on the transmission bandwidth. For convenience in transmission, a compression coding technology is generally adopted to compress and transmit a high-definition image, and when the compression rate is C, the first service index can be mapped into a first network index according to a formula (4), which is specifically as follows:
where v represents a first network indicator, i.e., a network transmission rate required to transmit images acquired by the industrial photographing apparatus. Q represents a first traffic index, i.e., the data size of a single frame image. B represents the bit depth of the image acquired by the industrial photographing device, and C represents the compression rate of the industrial photographing device for compressing the image.
And step 405, mapping the second service index into a second network index by using the processing capacity parameter.
It will be appreciated that the second network indicator characterizes a network transmission delay required to transmit images acquired by the industrial photographing device.
In one embodiment, the processing capability parameter includes a first time delay for the industrial photographing device to collect an image, a second time delay for the industrial photographing device to compress the image, and a third time delay for the industrial photographing device to analyze the image, and the mapping the second business index to a second network index by using the processing capability parameter includes:
Performing a second operation on the first time delay, the second time delay, the third time delay and the numerical value corresponding to the second service index to obtain an operation result;
And taking the obtained operation result as a second network index.
It can be understood that the complete machine vision detection flow includes image acquisition, image compression, network transmission, image receiving and recognition processing links, the end-to-end delay t E of a service segment of a single frame image is decomposed into an image acquisition delay t 1 +an image compression processing delay t 2 +a network transmission delay t+an analysis reasoning delay t 3, and a second service index can be mapped into a second network index according to the formula (5), which is specifically as follows:
Wherein t represents a second network index, namely network transmission delay required for transmitting the image acquired by the industrial photographing device. t E represents a second traffic indicator, i.e. the allowed end-to-end traffic delay of a single frame image. t 1 denotes the first delay, t 2 denotes the first delay, and t 3 denotes the third delay.
And step 406, mapping the third service index into a third network index by using the processing capacity parameter.
It will be appreciated that the third network indicator characterizes the network reliability required to transmit the images acquired by the industrial photographing device.
As one embodiment, the processing capability parameter includes a bit depth of an image acquired by the industrial photographing device; the mapping the third service index to a third network index by using the processing capability parameter includes:
Performing third operation on the bit depth and the numerical value corresponding to the third service index to obtain an operation result;
and taking the operation result as a third network index.
It can be understood that the image file size Q is packetized according to mtu=1500 bytes, and split into Q/1500=m data packets altogether, where each packet loss results in 1500 pixels being lost, and the third traffic index may be mapped to the third network index according to the formula (6), which is specifically as follows:
Where r represents a third network indicator, i.e. the network reliability required for transmitting the image acquired by the industrial photographing device. L represents a third traffic indicator, i.e. a packet loss rate allowed by the traffic. B represents the bit depth of the image acquired by the industrial photographing device.
In the embodiment of the present invention, the input industrial parameters and SAL index parameters are quantized and mapped into network indexes, and the present invention has the following advantages:
(1) The mapping from the industrial language to the network language can be directly realized, and compared with the mode of carrying out a large amount of demand communication and decomposition work under the artificial line and deploying CSMF-NSMF-NSSMF end-to-end systems in a large scale in the related technology, the method can realize automatic and real-time demand decomposition, and acquire the demands of the industry on the network more quickly and at lower cost:
(2) The calculation and the acquisition of the industrial demand on the network realize an online automatic process, improve the efficiency of demand acquisition and reduce the artificial communication cost and the calculation complexity.
(3) In addition, the requirement of the industry on the network is acquired in real time, thereby being beneficial to realizing real-time network guarantee and enabling the network to be more agile.
Taking a two-dimensional code traceability detection scene as an example, the implementation principle of the parameter processing method is explained in detail.
And (3) a service model, namely using a 5M (500 w pixel) industrial camera to carry out photographing detection, wherein the resolution of the camera is 2448 multiplied by 2048, the bit depth of 8bit is 8bit, and a picture in BMP format is photographed every second for non-compression transmission. As shown in fig. 5, if a packet loss occurs, black line filling occurs, resulting in false leak detection. If one packet is lost per frame in this scenario (n=1), it is determined that detection is abnormal. The success rate of detection is required to reach 99.99%.
The process of quantifying and mapping the input industrial parameters and SAL index parameters to network indices, as shown in fig. 6, comprises the steps of:
Step 601, inputting industrial parameters and SAL index parameters, wherein the industrial parameters comprise information source parameters of the industrial photographing equipment and processing capacity parameters of the industrial photographing equipment.
The first parameter, i.e., the resolution pv×ph=2448×2048 of the industrial photographing apparatus, is determined according to the detection accuracy of the industrial camera.
According to the detection time of the industrial camera, the second parameter, namely the time interval CYCLE TIME =1s=1000 ms for the industrial shooting device to acquire images, is determined, and the third parameter, namely the number f=1fps of images acquired by the industrial shooting device in unit time, is determined.
According to the detection success rate requirement of the industrial camera, the detection success rate S=99.99% is determined.
Step 602, quantifying input information source parameters and SLA index parameters to obtain service indexes;
It is understood that the traffic index may refer to a key quality index (KQI, key Quality Indicator) of a traffic layer.
The first traffic index, i.e. the data size of a single frame image:
Q=Pv×Ph=2448×2048=5013504bytes。
The second service index, namely the end-to-end service time delay allowed by the single frame image:
third traffic indicator, i.e. packet loss rate allowed by traffic:
L=n×(1-S)=0.0001。
and 603, mapping the service index into a network index by utilizing the processing capacity parameter.
It is understood that the network metrics may refer to key performance metrics (KPIs, key Performance Indicator) at the network level.
A first network indicator, namely a network transmission rate required for transmitting images acquired by the industrial photographing device:
a second network indicator, namely network transmission delay required for transmitting the image acquired by the industrial photographing device:
t=tE-t1-t2-t3≤960ms
A third network indicator, namely the network reliability required to transmit the images acquired by the industrial photographing device:
by adopting the technical scheme provided by the embodiment of the invention, the input industrial parameters and SLA index parameters are automatically converted, the network index is output, and the network index is not required to be set by manual operation, so that the automatic conversion from the industrial parameters to the network index can be realized, and the SLA demand decomposition can be realized in an industrial machine vision scene
In order to implement the parameter processing method according to the embodiment of the present invention, the embodiment of the present invention further provides a parameter processing device, and fig. 7 is a schematic diagram of a composition structure of the parameter processing device according to the embodiment of the present invention, where, as shown in fig. 7, the device includes:
an input unit 71 for inputting industrial parameters and SLA index parameters, wherein the industrial parameters represent related parameters of the industrial photographing equipment;
A processing unit 72, configured to map the input industrial parameters and SLA index parameters to obtain a network index, where the network index characterizes a network requirement required for transmitting an image acquired by the industrial photographing device to a network device;
an output unit 73 for outputting the network index.
In an embodiment, the industrial parameters include a source parameter of the industrial photographing apparatus and a processing capability parameter of the industrial photographing apparatus, and the processing unit 72 is specifically configured to:
quantizing the input information source parameters and SLA index parameters to obtain service indexes;
and mapping the service index into a network index by utilizing the processing capacity parameter.
In one embodiment, the processing unit 72 is specifically configured to:
quantizing input information source parameters to obtain a first service index and a second service index, wherein the first service index represents the data volume of a single-frame image;
and quantifying the SLA index parameter to obtain a third service index, wherein the third service index represents the packet loss rate allowed by the service.
In one embodiment, the source parameters include a first parameter, a second parameter, and a third parameter, and the processing unit 72 is specifically configured to:
Quantifying a first parameter to obtain a first business index, wherein the first parameter characterizes the resolution of the industrial photographing equipment;
And quantifying a second parameter and a third parameter to obtain a second service index, wherein the second parameter represents the time interval of the industrial photographing equipment for collecting images, and the third parameter represents the number of images collected by the industrial photographing equipment in unit time.
In one embodiment, the processing unit 72 is specifically configured to:
Mapping the first service index into a first network index by utilizing the processing capacity parameter, wherein the first network index represents a network transmission rate required for transmitting images acquired by the industrial photographing equipment;
Mapping the second service index into a second network index by utilizing the processing capacity parameter, wherein the second network index represents network transmission delay required for transmitting the image acquired by the industrial photographing equipment;
And mapping the third service index into a third network index by utilizing the processing capacity parameter, wherein the third network index represents the network reliability required by transmitting the image acquired by the industrial photographing equipment.
In one embodiment, the processing capability parameter includes a bit depth of an image acquired by the industrial photographing device and a compression rate of the industrial photographing device for performing compression processing on the image, and the processing unit 72 is specifically configured to:
Performing first operation on the bit depth, the compression rate and the numerical value corresponding to the first service index to obtain an operation result;
And taking the obtained operation result as the first network index.
In one embodiment, the processing capability parameter includes a first time delay for the industrial photographing device to collect an image, a second time delay for the industrial photographing device to compress the image, and a third time delay for the industrial photographing device to analyze the image, and the processing unit 72 is specifically configured to:
Performing a second operation on the first time delay, the second time delay, the third time delay and the numerical value corresponding to the second service index to obtain an operation result;
And taking the obtained operation result as a second network index.
In one embodiment, the processing capability parameter includes a bit depth of an image acquired by the industrial photographing device, and the processing unit 72 is specifically configured to:
Performing third operation on the bit depth and the numerical value corresponding to the third service index to obtain an operation result;
and taking the operation result as a third network index.
In practical applications, the input unit 71 and the output unit 73 may be implemented by a communication interface in the parameter processing device, and the processing unit 72 may be implemented by a processor in the parameter processing device.
It should be noted that, when the parameter processing apparatus provided in the foregoing embodiment performs parameter processing, only the division of each program module is used for illustration, and in practical application, the processing allocation may be performed by different program modules according to needs, that is, the internal structure of the apparatus is divided into different program modules to complete all or part of the processing described above. In addition, the parameter processing device and the parameter processing method provided in the foregoing embodiments belong to the same concept, and specific implementation processes thereof are detailed in the method embodiments and are not described herein again.
The embodiment of the invention also provides a network device, as shown in fig. 8, including:
a communication interface 81 capable of information interaction with other devices;
and the processor 82 is connected with the communication interface 81 and is used for executing the method provided by one or more technical schemes on the intelligent equipment side when running the computer program. And the computer program is stored on the memory 83.
It should be noted that, the specific processing procedures of the processor 82 and the communication interface 81 are detailed in the method embodiment, and are not described herein.
Of course, in actual practice, the various components in network device 80 are coupled together by bus system 84. It is understood that the bus system 84 is used to enable connected communications between these components. The bus system 104 includes a power bus, a control bus, and a status signal bus in addition to the data bus. But for clarity of illustration the various buses are labeled as bus system 84 in fig. 8.
The memory 83 in the embodiment of the present application is used to store various types of data to support the operation of the network device 80. Examples of such data include any computer program for operation on network device 80.
The method disclosed in the above embodiment of the present application may be applied to the processor 82 or implemented by the processor 82. The processor 82 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuitry of hardware in the processor 82 or by instructions in the form of software. The Processor 82 described above may be a general purpose Processor, a digital data Processor (DSP, digital Signal Processor), or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. The processor 102 may implement or perform the methods, steps, and logic blocks disclosed in embodiments of the present application. The general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the method disclosed in the embodiment of the application can be directly embodied in the hardware of the decoding processor or can be implemented by combining hardware and software modules in the decoding processor. The software modules may be located in a storage medium located in the memory 103, and the processor 102 reads information in the memory 103, in combination with its hardware, to perform the steps of the method as described above.
In an exemplary embodiment, the network device 80 may be implemented by one or more Application Specific Integrated Circuits (ASICs), DSPs, programmable logic devices (PLDs, programmable Logic Device), complex Programmable logic devices (CPLDs, complex Programmable Logic Device), field-Programmable gate arrays (FPGAs), general purpose processors, controllers, microcontrollers (MCUs, micro Controller Unit), microprocessors (microprocessors), or other electronic elements for performing the aforementioned methods.
It will be appreciated that the memory (memory 83) of embodiments of the application can be either volatile memory or nonvolatile memory, and can include both volatile and nonvolatile memory. the non-volatile Memory may be, among other things, a Read Only Memory (ROM), a programmable Read Only Memory (PROM, programmable Read-Only Memory), erasable programmable Read-Only Memory (EPROM, erasable Programmable Read-Only Memory), electrically erasable programmable Read-Only Memory (EEPROM, ELECTRICALLY ERASABLE PROGRAMMABLE READ-Only Memory), Magnetic random access Memory (FRAM, ferromagnetic random access Memory), flash Memory (Flash Memory), magnetic surface Memory, optical disk, or compact disk-Only Memory (CD-ROM, compact Disc Read-Only Memory), which may be disk Memory or tape Memory. the volatile memory may be random access memory (RAM, random Access Memory) which acts as external cache memory. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM, static Random Access Memory), synchronous static random access memory (SSRAM, synchronous Static Random Access Memory), dynamic random access memory (DRAM, dynamic Random Access Memory), synchronous dynamic random access memory (SDRAM, synchronous Dynamic Random Access Memory), and, Double data rate synchronous dynamic random access memory (DDRSDRAM, double Data Rate Synchronous Dynamic Random Access Memory), enhanced synchronous dynamic random access memory (ESDRAM, enhanced Synchronous Dynamic Random Access Memory), synchronous link dynamic random access memory (SLDRAM, syncLink Dynamic Random Access Memory), Direct memory bus random access memory (DRRAM, direct Rambus Random Access Memory). The memory described by embodiments of the present application is intended to comprise, without being limited to, these and any other suitable types of memory.
In an exemplary embodiment, the present invention further provides a storage medium, i.e. a computer storage medium, in particular a computer readable storage medium, for example comprising a first memory 81 storing a computer program executable by the first processor 102 of the terminal 100 for performing the steps of the aforementioned terminal-side method. The computer readable storage medium may be FRAM, ROM, PROM, EPROM, EEPROM, flash Memory, magnetic surface Memory, optical disk, or CD-ROM.
It should be noted that "first," "second," etc. are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
In addition, the embodiments of the present invention may be arbitrarily combined without any collision.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention.
Claims (11)
1. A method of parameter processing, the method comprising:
inputting industrial parameters and Service Level Agreement (SLA) index parameters, wherein the industrial parameters represent relevant parameters of industrial photographing equipment;
Mapping the input industrial parameters and SLA index parameters to obtain network indexes, wherein the network indexes represent network requirements required by transmitting images acquired by the industrial shooting equipment to network equipment;
Outputting the network index;
Wherein the industrial parameters comprise information source parameters of the industrial photographing equipment and processing capacity parameters of the industrial photographing equipment; mapping the input industrial parameters and SLA index parameters to obtain network indexes, including:
quantizing the input information source parameters and SLA index parameters to obtain service indexes;
and mapping the service index into a network index by utilizing the processing capacity parameter.
2. The method of claim 1, wherein the quantifying the input source parameters and SLA indicator parameters to obtain the traffic indicator comprises:
quantizing input information source parameters to obtain a first service index and a second service index, wherein the first service index represents the data volume of a single-frame image;
and quantifying the SLA index parameter to obtain a third service index, wherein the third service index represents the packet loss rate allowed by the service.
3. The method of claim 2, wherein the source parameters include a first parameter, a second parameter, and a third parameter, and wherein quantizing the input source parameters to obtain the first traffic indicator and the second traffic indicator comprises:
Quantifying a first parameter to obtain a first business index, wherein the first parameter characterizes the resolution of the industrial photographing equipment;
And quantifying a second parameter and a third parameter to obtain a second service index, wherein the second parameter represents the time interval of the industrial photographing equipment for collecting images, and the third parameter represents the number of images collected by the industrial photographing equipment in unit time.
4. A method according to claim 2 or 3, wherein said mapping said traffic index to a network index using said processing capability parameter comprises:
Mapping the first service index into a first network index by utilizing the processing capacity parameter, wherein the first network index represents a network transmission rate required for transmitting images acquired by the industrial photographing equipment;
Mapping the second service index into a second network index by utilizing the processing capacity parameter, wherein the second network index represents network transmission delay required for transmitting the image acquired by the industrial photographing equipment;
And mapping the third service index into a third network index by utilizing the processing capacity parameter, wherein the third network index represents the network reliability required by transmitting the image acquired by the industrial photographing equipment.
5. The method of claim 4, wherein the processing capability parameter comprises a bit depth of an image captured by the industrial photographing device and a compression rate of the image compressed by the industrial photographing device, wherein mapping the first traffic index to a first network index using the processing capability parameter comprises:
Performing first operation on the bit depth, the compression rate and the numerical value corresponding to the first service index to obtain an operation result;
And taking the obtained operation result as the first network index.
6. The method of claim 4, wherein the processing capability parameter comprises a first time delay for the industrial photographing device to collect an image, a second time delay for the industrial photographing device to compress the image, and a third time delay for the industrial photographing device to analyze the image, wherein mapping the second traffic index to a second network index using the processing capability parameter comprises:
Performing a second operation on the first time delay, the second time delay, the third time delay and the numerical value corresponding to the second service index to obtain an operation result;
And taking the obtained operation result as a second network index.
7. The method of claim 4, wherein the processing capability parameter comprises a bit depth of an image captured by the industrial capture device, and wherein mapping the third business index to a third network index using the processing capability parameter comprises:
Performing third operation on the bit depth and the numerical value corresponding to the third service index to obtain an operation result;
and taking the operation result as a third network index.
8. A parameter processing apparatus, comprising:
The system comprises an input unit, a detection unit and a detection unit, wherein the input unit is used for inputting industrial parameters and SLA index parameters, the industrial parameters represent relevant parameters of industrial shooting equipment, and the SLA index parameters represent the detection success rate of images acquired by the industrial shooting equipment;
the processing unit is used for mapping the input industrial parameters and SLA index parameters to obtain network indexes, wherein the network indexes represent network requirements required by transmitting images acquired by the industrial shooting equipment to network equipment;
the output unit is used for outputting the network index;
The industrial parameters comprise information source parameters of the industrial photographing equipment and processing capacity parameters of the industrial photographing equipment, and the processing unit is specifically used for quantifying the input information source parameters and SLA index parameters to obtain service indexes, and mapping the service indexes into network indexes by utilizing the processing capacity parameters.
9. A network device, comprising:
the system comprises a communication interface, an industrial photographing device, an SLA index parameter, a detection success rate and a control unit, wherein the communication interface is used for inputting industrial parameters and the SLA index parameter, the industrial parameters represent related parameters of the industrial photographing device, and the SLA index parameter represents the detection success rate of images acquired by the industrial photographing device;
The system comprises a processor, a network index, a network device and an industrial shooting device, wherein the processor is used for mapping input industrial parameters and SLA index parameters to obtain a network index;
the communication interface is further used for outputting the network index;
The industrial parameters comprise information source parameters of the industrial photographing equipment and processing capacity parameters of the industrial photographing equipment, and the processor is specifically used for quantifying the input information source parameters and SLA index parameters to obtain service indexes, and mapping the service indexes into network indexes by utilizing the processing capacity parameters.
10. A network device comprising a processor and a memory for storing a computer program capable of running on the processor,
Wherein the processor is adapted to perform the steps of the method of any of claims 1 to 7 when the computer program is run.
11. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method according to any one of claims 1 to 7.
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| CN108462596B (en) * | 2017-02-21 | 2021-02-23 | 华为技术有限公司 | SLA decomposition method, equipment and system |
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| CN110460880B (en) * | 2019-08-09 | 2021-08-31 | 东北大学 | Adaptive Transmission Method of Industrial Wireless Streaming Media Based on Particle Swarm and Neural Network |
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