A data transmission method and system for an industrial edge gateway

Abstract

The present invention relates to the technical field of data processing. More specifically, the present invention relates to a data transmission method and system for an industrial edge gateway. The method includes: obtaining industrial production equipment data and constructing a data queue, and obtaining the busy degree of each edge gateway based on the running data of the data queue; according to the busy degree of each edge gateway, obtaining the transmission results after different data queues are transmitted to the cloud server, and calculating the feedback rewards for the edge gateway to select different data queues for transmission; based on the feedback rewards, using the UCB algorithm to calculate the confidence of each queue in transmitting data to the cloud server, and adjusting the data queue through which the edge gateway transmits data to the cloud server according to the confidence. By monitoring the busy degree of the edge gateway and the transmission results of the data queue in real time, the present invention dynamically adjusts the data transmission strategy, better adapts to the rapid changes in task frequency, data volume and network conditions, and thus improves the data transmission efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing. More specifically, the present invention relates to a data transmission method and system for an industrial edge gateway. Background Art

[0002] With the increasing application of short - range wireless communication in industrial edge computing scenarios, the deployment of industrial edge networks is becoming more and more intensive. In the case of ultra - dense deployment of edge networks, during the process of transmitting data to the server, serious signal collision problems are likely to occur in data transmission. Therefore, a data transmission method that can adapt to multi - source heterogeneous devices and high - concurrency scenarios of dense deployment is needed.

[0003] The existing Chinese patent application document with the publication number CN115242774A discloses a data transmission method between an edge gateway and a cloud server, including: the edge gateway sends a heartbeat packet to connect to the cloud server; when the cloud server has data to send to the edge gateway, download the data of the cloud server; when the edge gateway has information to upload to the cloud server, inform when the edge gateway sends a heartbeat packet. If the cloud server has no data to send, the edge gateway uploads information to the cloud server; if the cloud server has data to send, the edge gateway first pauses uploading information, downloads the data of the cloud server, compares the downloaded data with the information to be uploaded. If it is rollback information, the edge gateway stops uploading information; otherwise, the edge gateway uploads information; when there is no data for uploading and downloading, inform when the edge gateway sends a heartbeat packet, and then interrupt the communication connection. It reduces the number of connection times between the edge gateway and the cloud server during data transmission, reduces network traffic, and enables the edge gateway to require less network guarantee time.

[0004] This patent application document solves the problem that the deployment location and position of the edge gateway often have an unstable network environment, resulting in the edge gateway being unable to always maintain the ability to be online, so that the data transmission from the edge gateway to the cloud server cannot be fully guaranteed; currently, it is necessary to transfer data from the edge gateway to data queues adapted to different situations. Traditional data allocation strategies are usually based on simple preset rules, and these rules may not be able to adapt to the rapid changes in task frequency, data volume, and network conditions, resulting in inflexible performance of the allocation strategy in complex environments, thus affecting data processing speed, packet loss, or transmission errors, and affecting data integrity and accuracy. Summary of the Invention

[0005] To solve the problem that data transmission requirements are often dynamically affected by various factors, resulting in affecting data processing speed, packet loss, or transmission errors in complex environments, and affecting data integrity and accuracy, the present invention provides solutions in the following aspects.

[0006] In a first aspect, a data transmission method for an industrial edge gateway includes: obtaining industrial production device data of the edge gateway, constructing a data queue, and obtaining the busyness degree of each edge gateway based on the running data of the data queue; according to the busyness degree of each edge gateway, obtaining the transmission result after different data queues are transmitted to the cloud server, and calculating the feedback reward for the edge gateway to select different data queues for transmission; based on the feedback reward, using the UCB algorithm to calculate the confidence of each data queue for transmitting data to the cloud server, and adjusting the data queue through which the edge gateway transmits data to the cloud server according to the confidence; wherein, the confidence satisfies the following relational expression: , where represents the confidence of the th edge gateway transmitting data to the cloud server through the th data queue at the current moment, represents the average feedback incentive of the th edge gateway transmitting data to the cloud server through the th data queue before the current moment, represents the busyness degree of the th edge gateway at the current moment, represents the number of times the th edge gateway transmits data to the cloud server through the th data queue at the current moment, represents the total number of times all data queues of the th edge gateway transmit data to the cloud server at the current moment, represents the logarithmic function with the natural constant as the base.

[0007] The effect is that by real-time monitoring the busyness degree of the edge gateway and the transmission result of the data queue, dynamically adjusting the data transmission strategy, ensuring that data can be transmitted to the cloud server quickly and reliably, reducing packet loss and transmission errors, using the UCB algorithm to calculate the confidence of each data queue, and intelligently selecting the most suitable data queue for data transmission, thereby improving the utilization rate of network resources, reducing network congestion, and balancing the load.

[0008] Preferably, constructing a data queue includes: a high-demand queue, a large-capacity queue, a frequent interaction queue, a small-data queue, and an abnormal data queue;

[0009] Among them, the high-demand queue is for processing a large amount of intensive tasks; the large-capacity queue is for storing a large amount of infrequently interacting data; the frequent interaction queue is for processing a large amount of intensive tasks; the small-data queue is for temporarily storing a small amount of infrequently interacting data; the abnormal data queue is for preferentially processing and responding to abnormal data.

[0010] Preferably, the busyness degree includes:

[0011] Taking any edge gateway as the target gateway and any moment of the target gateway as the marking moment, the product of the normalized number and size of data tasks collected within a preset time before the marking moment is used as the data load intensity.

[0012] Calculating the ratio of the idle time within a preset time before the marking moment to the preset time and performing exponential decay to obtain the exponential decay of idle time.

[0013] Taking the product between the data load intensity and the exponential decay of idle time as the busyness degree of the target gateway at the marking moment.

[0014] Its effect is that by calculating the ratio of idle time to the preset time and applying exponential decay, the idle state of the edge gateway before the marking moment can be dynamically reflected, enabling the calculation of the busyness degree to sensitively respond to changes in idle time.

[0015] Preferably, the busyness degree further includes:

[0016] Taking any edge gateway as the target gateway and any moment of the target gateway as the marking moment, the product of the data packet loss rate and memory usage rate within a period of time before the marking moment is used as the busyness degree.

[0017] Its effect is that the data packet loss rate reflects the network congestion or instability situation, while the memory usage rate reflects the tightness of computing resources. By accurately evaluating the busyness degree of the edge gateway, network resources can be allocated more effectively, improving the overall network resource utilization rate and throughput and reducing resource waste.

[0018] Preferably, the feedback reward includes:

[0019] Taking any edge gateway as the target gateway, calculating the ratio between the total number of data packets received by the server and the number of correctly received data packets to obtain the data transmission success rate of the target gateway through different data queues.

[0020] According to the sending time and receiving time of each data packet recorded between the target gateway and the server, obtaining the transmission delay of the target gateway through different data queues.

[0021] Taking the ratio between the data transmission success rate and the transmission delay as the transmission efficiency, taking the complement of the busyness degree as the idle degree, using a logarithmic function and a correction parameter to correct the idle degree, and taking the product between the transmission efficiency and the corrected idle degree as the feedback incentive of the target gateway.

[0022] The effect is that by calculating the data transmission success rate and transmission delay, the transmission performance of the edge gateway through different data queues can be quantified, and then the feedback incentive of the target gateway can be analyzed, which helps to balance resource utilization, optimize the data transmission strategy, and improve the overall network performance.

[0023] Preferably, the feedback reward further includes:

[0024] Taking any edge gateway as the target gateway, using the complement of the busyness degree of the target gateway as the idle degree, and correcting the idle degree using a logarithmic function and a correction parameter;

[0025] Obtaining the network communication performance parameters of the target gateway, and calculating the percentage of the actually used bandwidth in the total broadband to obtain the broadband utilization rate;

[0026] Taking the ratio of the corrected idle degree to the broadband utilization rate as the feedback incentive of the target gateway.

[0027] The effect is that by calculating the broadband utilization rate, the ratio of the actually used bandwidth to the total broadband can be quantified, which helps to identify and solve the problems of bandwidth waste or shortage, and optimize the bandwidth usage efficiency. It can adaptively adjust the data transmission strategy according to the current network resources, and improve the system response ability and flexibility.

[0028] Preferably, adjusting the data queue through which the edge gateway transmits data to the cloud server includes:

[0029] Initializing each edge gateway for each data queue, where the initialization means that the feedback incentive for each edge gateway to transmit data through each data queue at the initial moment is 0, then randomly selecting a data queue for data transmission, calculating a new feedback incentive according to the transmission result, repeating the iteration, calculating the average feedback incentive for each edge gateway to transmit data to the cloud server through each data queue, and calculating the confidence level for each edge gateway to transmit data to the cloud server through each data queue, and selecting the data queue with the largest confidence level to transmit data to the cloud server.

[0030] In a second aspect, a data transmission system for an industrial edge gateway includes: a processor and a memory, and the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the data transmission method for the industrial edge gateway described above is implemented.

[0031] The present invention has the following effects:

[0032] 1. The present invention dynamically adjusts the data transmission strategy by monitoring the busyness of the edge gateway and the transmission results of the data queues in real time, so that the adaptive data allocation mechanism can better adapt to the rapid changes in task frequency, data volume, and network conditions, thereby improving the data transmission efficiency, reducing data packet loss or transmission errors, and ensuring the integrity and accuracy of the data.

[0033] 2. The present invention calculates the confidence of each data queue by using the UCB algorithm and adjusts the data queue transmission according to the confidence. Based on the confidence, the flexibility of the system is improved, enabling it to quickly respond to environmental changes and business requirements. At the same time, new data queues and edge gateways can be easily expanded without affecting the stability and efficiency of the existing system.

[0034] 3. The present invention constructs different types of data queues and intelligently selects data queues according to the busyness of the edge gateway and feedback rewards, which can allocate network resources more reasonably, improve bandwidth utilization, reduce network congestion, and thus optimize the overall network performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] By referring to the following detailed description with reference to the accompanying drawings, the above and other objects, features, and advantages of the exemplary embodiments of the present invention will become readily understood. In the drawings, several embodiments of the present invention are shown in an exemplary rather than restrictive manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0036] Figure 1 is a flowchart of the method from step S1 to step S3 in the data transmission method of an industrial edge gateway according to an embodiment of the present invention.

[0037] Figure 2 is a block diagram of the structure of a data transmission system of an industrial edge gateway according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] The following will describe the specific embodiments of the present invention in detail with reference to the accompanying drawings.

[0040] Specific implementation scenario: In the modern industrial automation and intelligent manufacturing environment, the edge gateway plays a crucial role in collecting data from various sensors and devices and needs to divide the data queues for the process of inputting data to the cloud server through the edge gateway.

[0041] Reference Figure 1 , a data transmission method for an industrial edge gateway includes steps S1 - S3, specifically as follows:

[0042] S1: Obtain the industrial production equipment data of the edge gateway, construct a data queue, and obtain the busy degree of each edge gateway based on the running data of the data queue.

[0043] Constructing the data queue includes but is not limited to: high - requirement queue, large - capacity queue, frequent - interaction queue, small - data queue, abnormal - data queue; implementers can construct more queues according to scenario needs.

[0044] Among them, the high - requirement queue is for processing data of a large number of intensive tasks; the large - capacity queue is for storing a large amount of infrequently - interacted data; the frequent - interaction queue is for processing data of a large number of intensive tasks; the small - data queue is for temporarily storing a small amount of infrequently - interacted data; the abnormal - data queue is for preferentially processing and responding to abnormal data.

[0045] Further analysis shows that since the devices accessed by different edge gateways are different, the pressure on the server when their collected data is transmitted to the server is also different. In order to balance the use of resources, it is necessary to perform load analysis on the edge gateways connected to the server. Therefore, calculate the busy degree of each edge gateway according to the running data of each edge gateway, and the specific steps are as follows:

[0046] Take any edge gateway as the target gateway, take any moment of the target gateway as the marking moment, and use the product of the normalized number of data tasks and the size of the data volume collected within the preset time before the marking moment as the data load intensity;

[0047] Calculate the exponential decay of the ratio of the idle time within the preset time before the marking moment to the preset time to obtain the idle - time exponential decay;

[0048] Take the product between the data load intensity and the idle - time exponential decay as the busy degree of the target gateway at the marking moment.

[0049] Specifically, the busy degree satisfies the following relational expression:

[0050] ;

[0051] In the formula, represents the busy degree of the th edge gateway at any moment, represents the idle time within the preset time before any moment of the th edge gateway, represents the length of the preset time, represents the The number of data tasks received by any edge gateway within a preset time before any moment represents the amount of data received by the th edge gateway within a preset time before any moment, represents the exponential function with the natural constant as the base,

[0052] In this embodiment, the preset time is 100 milliseconds, and the implementer can select the length of this time period according to the actual situation;

[0053] That is to say, represents the proportion of idle time of the edge gateway within a preset time before any moment. The larger the value, the lower the task load and the less busy the edge gateway; on the contrary, the smaller the value, the higher the task load and the busier the edge gateway.

[0054] reflects the request density processed by the edge gateway. The larger the value, the denser the requests processed by the edge gateway, and the busier the edge gateway. The greater the busyness of the edge gateway. The smaller the value, the sparser the requests processed by the edge gateway, and the edge gateway may be more idle, and the busyness of the edge gateway is smaller.

[0055] reflects the load level of each task and the consumption of communication resources. The larger the value, the greater the load of the edge gateway and the consumption of communication resources, and the busier the edge gateway. The greater the busyness of the edge gateway. The smaller the value, the smaller the load of the edge gateway and the consumption of communication resources, and the smaller the busyness of the edge gateway.

[0056] In addition, in another embodiment, it further includes:

[0057] Taking any edge gateway as the target gateway and any moment of the target gateway as the marking moment, the product of the data packet loss rate and the memory usage rate within a period of time before the marking moment is used as the busyness level.

[0058] Specifically, the busyness level satisfies the following relational expression:

[0059] ;

[0060] In the formula, represents the busyness level of the th edge gateway at any moment, represents the data packet loss rate of the th edge gateway within a period of time before any moment, represents the memory usage rate of the

[0061] That is to say, the data packet loss rate reflects network congestion or instability to a certain extent, which may be caused by excessive network load. The memory usage rate means that the edge gateway is processing a large amount of data. The above calculations reflect the pressure on the edge gateway in processing data and maintaining network connections, which helps to ensure that the edge gateway can efficiently process data and maintain a stable network connection, thereby improving the performance and reliability of the entire system.

[0062] Further analysis shows that due to the different degrees of busyness and task loads of different edge gateways, when the edge gateway selects different data queues to transmit data to the cloud server, there will be certain differences in the transmission effects. To optimize the transmission efficiency and resource allocation, it is necessary to evaluate the quality of data transmission from different edge gateways in different states to the cloud server through different data queues. Therefore, it is necessary to calculate the feedback rewards for the edge gateway to select different data queues to transmit data according to the degree of busyness of each edge gateway and the transmission results when the gateway selects different data queues to transmit data to the server. The specific steps are as follows.

[0063] S2: According to the degree of busyness of each edge gateway, obtain the transmission results after different data queues are transmitted to the cloud server, and calculate the feedback rewards for the edge gateway to select different data queues for transmission.

[0064] Among them, the transmission results include but are not limited to: data transmission success rate, transmission delay, data packet loss rate, transmission rate, etc.

[0065] Taking any edge gateway as the target gateway, calculate the ratio between the total number of data packets received by the server and the number of correctly received data packets to obtain the data transmission success rate of the target gateway through different data queues;

[0066] According to the sending time and receiving time of each data packet recorded between the target gateway and the server, obtain the transmission delay of the target gateway through different data queues;

[0067] Take the ratio between the data transmission success rate and the transmission delay as the transmission efficiency, take the complement of the degree of busyness as the degree of idleness, use the logarithmic function and correction parameters to correct the degree of idleness, and take the product of the transmission efficiency and the corrected degree of idleness as the feedback incentive of the target gateway.

[0068] Specifically, the feedback reward satisfies the following relational expression:

[0069] ;

[0070] In the formula, represents the feedback incentive for the th edge gateway to transmit data to the cloud server through the th data queue at any moment, denote the data transmission success rate of the th edge gateway transmitting data to the cloud server through the th data queue at any moment, denote the transmission delay of the th edge gateway transmitting data to the cloud server through the th data queue at any moment, denote the busy degree of the th edge gateway at any moment, denote the correction parameter for adjusting the busy degree of the edge gateway, denote the logarithmic function with the natural constant as the base.

[0071] In this embodiment, the correction parameter , and the implementer can select according to the actual situation.

[0072] That is to say, the greater the data transmission success rate of the edge gateway transmitting data to the cloud server through different data queues , the higher the reliability of the edge gateway transmitting data to the cloud server through the data queue. In order to make the algorithm tend to select the data queue that can ensure the reliability of data transmission and improve the overall system performance, the feedback incentive for the th edge gateway transmitting data to the cloud server through the th data queue should be greater. The smaller the data transmission success rate of the edge gateway transmitting data to the cloud server through different data queues , it indicates a high data loss rate and more data retransmission is required, and the system burden and network congestion risk are greater; in order to guide the algorithm to explore better choices, the feedback incentive for the th edge gateway transmitting data to the cloud server through the th data queue should be smaller.

[0073] The greater the transmission delay of the edge gateway transmitting data to the cloud server through different data queues , the slower the th edge gateway transmits data to the cloud server through the th data queue, and the greater the impact on data tasks with high real-time requirements. In order to avoid further increasing the load and guide the algorithm to select a more efficient data queue, the feedback incentive for the th edge gateway transmitting data to the cloud server through the th data queue should be smaller; the smaller the transmission delay of the edge gateway transmitting data to the cloud server through different data queues , the th edge gateway transmits data to the cloud server through the The more timely the data transmission of a data queue to the cloud server is, the more it can meet the real-time requirements of data transmission. To optimize the completion effect of real-time tasks, the th edge gateway should have a greater feedback incentive for data transmission to the cloud server through the th data queue.

[0074] The busyness of the edge gateway reflects the current load pressure and resource availability of the gateway, which will directly affect the quality and efficiency of data received by the cloud server. When the gateway is busy, problems such as increased transmission delay, increased packet loss rate, and decreased data integrity may occur during data transmission. At this time, the success rate and transmission delay of data transmission from the edge gateway to the server through different data queues may be at a similar level. If only the success rate and transmission delay of data transmission are used to calculate the feedback incentive, it may not be possible to guide the algorithm to select a more efficient data queue. Therefore, it is necessary to calculate the feedback incentive in combination with the busyness of the edge gateway. When the edge busyness is greater, the gateway's resources are tense, and the performance of data transmission through the data queue may be poor. It is necessary to carefully select the data queue, and the feedback incentive for the edge gateway to transmit data to the cloud server through each data queue should be reduced. When the busyness of the edge gateway is smaller, the gateway resources are sufficient and the quality of data transmission is more guaranteed. There is no need to overly restrict the data queue selection, and the feedback incentive for the edge gateway to transmit data to the cloud server through each data queue should be increased. Therefore, through to is corrected.

[0075] In addition, in another embodiment, it further includes:

[0076] Taking any edge gateway as the target gateway, using the complement of the busyness of the target gateway as the idle degree, and correcting the idle degree using a logarithmic function and a correction parameter;

[0077] Obtaining the network communication performance parameters of the target gateway, and calculating the percentage of the actual used bandwidth in the total broadband to obtain the broadband utilization rate;

[0078] Taking the ratio of the corrected idle degree to the broadband utilization rate as the feedback incentive of the target gateway.

[0079] Specifically, the feedback reward satisfies the following relational expression:

[0080] ;

[0081] In the formula, represents the feedback incentive for the th edge gateway to transmit data to the cloud server through the th data queue at any moment, represents the busyness of the th edge gateway at any moment, A correction parameter indicating the busy degree of the edge gateway Indicates at any moment the th edge gateway transmits data to the cloud server through the th data queue, the broadband utilization rate Indicates the logarithmic function with the natural constant as the base

[0082] In this embodiment, the correction parameter , and the implementer can select according to the actual situation

[0083] That is to say, the above calculation method reflects the network efficiency and resource utilization of the edge gateway when transmitting data. A high feedback incentive value indicates that the current data queue is a good choice for transmitting data, while a low feedback incentive value may indicate that other data queues need to be considered to optimize the transmission performance

[0084] Furthermore, since different data queues have different characteristics, the transmission effects of the edge gateway transmitting data to the cloud server through different data queues are also different when the edge gateway is in different states. In order to select the most suitable data queue for each edge gateway to make the data transmission effect better, the present invention selects the data queue through which the edge gateway transmits data to the server according to the feedback reward of the gateway selecting different data queues to transmit data. The specific analysis is as follows

[0085] S3: Based on the feedback reward, use the UCB algorithm to calculate the confidence of each data queue transmitting data to the cloud server, and adjust the data queue through which the edge gateway transmits data to the cloud server according to the confidence

[0086] It should be noted that the UCB algorithm is a well-known technology in the art and will not be described in detail

[0087] Specifically, the confidence satisfies the following relational expression

[0088] ;

[0089] In the formula Indicates the confidence of the th edge gateway transmitting data to the cloud server through the th data queue at the current moment Indicates the average feedback incentive of the th edge gateway transmitting data to the cloud server through the th data queue before the current moment Indicates the busy degree of the th edge gateway at the current moment Indicates the th edge gateway at the current moment transmits data through the The number of times a data queue transmits data to the cloud server Indicates the Total number of times all data queues of the th edge gateway transmit data to the cloud server at the current moment Represents the logarithmic function with the natural constant as the base

[0090] That is to say Indicates the Average feedback incentive for the th edge gateway to transmit data to the cloud server through the th data queue. The larger the value, the better the transmission effect of the th edge gateway transmitting data to the cloud server through the th data queue before the current moment. Then the confidence that the th edge gateway transmits data to the cloud server through the th data queue is greater; conversely, the smaller the value, the worse the transmission effect of the th edge gateway transmitting data to the cloud server through the th data queue before the current moment. Then it is less advisable to continue transmitting data to the cloud server for the th edge gateway through the th data queue. Then the confidence that the th edge gateway transmits data to the cloud server through the

[0091] Indicates the Uncertainty estimation value of the value estimation of the th edge gateway through the th data queue. The larger the value, the more exploration of the th edge gateway through the th data queue. Then the uncertainty of selecting the th data queue is smaller. Thus, the confidence increase for the th edge gateway through the th data queue should be reduced, enabling the edge gateway to explore data queues with greater uncertainty to select more suitable data queues for data transmission; The smaller the value, the less exploration of the th edge gateway through the th data queue. Then the uncertainty of selecting the th data queue is larger. At this time, the confidence increase for the th edge gateway through the th data queue should be increased, enabling the edge gateway to explore the A data queue to determine the th data queue is a data queue suitable for data transmission.

[0092] On the other hand, when remains unchanged, The larger it is, the more the th edge gateway explores data queues other than the th data queue. Then, relatively speaking, the th edge gateway explores the th data queue less. The uncertainty of selecting the th data queue is greater. At this time, the confidence level of the th edge gateway passing through the th data queue should be increased so that the edge gateway can explore the th data queue to determine whether the th data queue is a data queue suitable for data transmission; The smaller it is, the less the th edge gateway explores data queues other than the th data queue. Then, relatively speaking, the th edge gateway explores the th data queue more. The uncertainty of selecting the th data queue is smaller. At this time, the confidence level of the th edge gateway passing through the th data queue should be decreased so that the edge gateway can explore data queues with greater uncertainty to select a more suitable data queue for data transmission.

[0093] A regulation value representing the uncertainty measure of the value estimation of the data queue, The larger it is, the greater the data transmission pressure at the current moment. Since the high-load environment may not be able to truly reflect the performance of the data queue, resulting in a higher cost for exploring new data queues, it is necessary to reduce the exploration effort for data queues and select more known data queues with better performance. The smaller it is, the smaller the data transmission pressure at the current moment. The transmission performance of different data queues is more stable, and the actual performance of the data queue is closer to its true potential. In this case, the cost of exploring new data queues is lower, and it is more suitable to try data queues that are not fully utilized. Therefore, it is necessary to increase the exploration effort for data queues and increase the attempt for data queues that have not been fully evaluated to select a more suitable data queue for data transmission.

[0094] Obtaining the data queue through which the edge gateway transfers data to the cloud server includes the steps of:

[0095] Initialize each edge gateway for each data queue such that the feedback incentive for each edge gateway to perform data transmission through each data queue at the initial moment is 0. Then randomly select a data queue for data transmission, calculate the new feedback incentive based on the transmission result, repeat the iteration, calculate the average feedback incentive for the edge gateway to transmit data to the cloud server through each data queue, calculate the confidence level for each edge gateway to transmit data to the cloud server through each data queue, and select the data queue with the highest confidence level to transmit data to the cloud server.

[0096] It should be noted that when the system starts or a new data queue is introduced, the feedback incentive for each edge gateway through each data queue is initialized to 0. This means that in the absence of historical data, all data queues are considered to have the same transmission performance. After each data transmission, the system calculates the new feedback incentive based on the transmission result (such as transmission success rate, latency, etc.). This helps the system evaluate the performance of each data queue. Over time, the system continuously repeats the process of data transmission, result collection, and feedback incentive update.

[0097] The present invention also provides a data transmission system for an industrial edge gateway. As Figure 2 shown, the system includes a processor and a memory. The memory stores computer program instructions, and when the computer program instructions are executed by the processor, it implements a data transmission method for an industrial edge gateway according to the first aspect of the present invention.

[0098] The system also includes other components well-known to those skilled in the art such as a communication bus and a communication interface. Their settings and functions are known in the art, so they will not be elaborated here.

[0099] In the present invention, the aforementioned memory may be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device. For example, a computer-readable storage medium may be any suitable magnetic storage medium or magneto-optical storage medium, such as a resistive random access memory (RRAM), a dynamic random access memory (DRAM), a static random access memory (SRAM), an enhanced dynamic random access memory (EDRAM), a high-bandwidth memory (HBM), a hybrid memory cube (HMC), etc., or any other medium that can be used to store the required information and can be accessed by an application program, a module, or both. Any such computer storage medium may be part of the device or accessible or connectable to the device. Any application or module described in the present invention may be implemented using computer-readable / executable instructions that can be stored or otherwise held by such a computer-readable medium.

[0100] In the description of this specification, the meanings of "a plurality of" and "several" are at least two, such as two, three, or more, etc., unless otherwise specifically defined.

[0101] Although this specification has shown and described multiple embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will think of many changes, alterations, and alternative ways without departing from the spirit and concept of the present invention. It should be understood that various alternatives to the embodiments of the present invention described herein may be employed in the practice of the present invention.

Claims

1. A data transmission method for an industrial edge gateway, characterized in that: include: Obtain industrial production equipment data from edge gateways, build data queues, and obtain the busyness of each edge gateway based on the operating data of the data queues; The busyness includes: taking any edge gateway as the target gateway, taking any moment of the target gateway as the marking moment, and taking the product of the number of data tasks and the amount of data collected within the preset time before the marking moment after normalization as the data load intensity; calculating the ratio of the idle time within the preset time before the marking moment to the preset time for exponential decay, and obtaining the idle time exponential decay; taking the product of the data load intensity and the idle time exponential decay as the busyness of the target gateway at the marking moment; According to the busyness of each edge gateway, the transmission results of different data queues after being transmitted to the cloud server are obtained, and the feedback reward of the edge gateway for selecting different data queues for transmission is calculated; Based on the feedback reward, the UCB algorithm is used to calculate the confidence of each data queue in transmitting data to the cloud server, and the data queue through which the edge gateway transmits data to the cloud server is adjusted according to the confidence; The confidence level satisfies the following relationship: , where Indicates the current moment The edge gateway passes The confidence level of each data queue transmitting data to the cloud server, Indicates the number before the current time The edge gateway passes The average feedback incentive for each data queue to transmit data to the cloud server, Indicates The current busyness of the edge gateway, Indicates the current moment The edge gateway passes The number of times a data queue transmits data to the cloud server. Indicates the current moment The total number of times all data queues of the edge gateway transmit data to the cloud server, Expressed as a natural constant The logarithmic function of the base.

2. The data transmission method of an industrial edge gateway according to claim 1, characterized in that: Build data queues, including high-demand queues, large-capacity queues, frequent interaction queues, small data queues, and abnormal data queues; Among them, the high-requirement queue is for processing data of large-scale, intensive tasks; the large-capacity queue is for storing data of large-scale, infrequent interactions; the frequent interaction queue is for processing data of large-scale, intensive tasks; the small data queue is for temporarily storing small-scale, infrequently interacted data; and the abnormal data queue is for giving priority to processing and responding to abnormal data.

3. The data transmission method of an industrial edge gateway according to claim 1, characterized in that: The feedback reward includes: Taking any edge gateway as the target gateway, the ratio between the total number of data packets received by the server and the number of data packets correctly received is calculated to obtain the data transmission success rate of the target gateway through different data queues; According to the sending time and receiving time of each data packet recorded between the target gateway and the server, the transmission delay of the target gateway through different data queues is obtained; The ratio of the data transmission success rate to the transmission delay is used as the transmission efficiency, the complement of the busyness is used as the idleness, the idleness is corrected using a logarithmic function and a correction parameter, and the product of the transmission efficiency and the corrected idleness is used as the feedback incentive of the target gateway.

4. The data transmission method of an industrial edge gateway according to claim 1, characterized in that: The feedback reward also includes: Taking any edge gateway as the target gateway, taking the complement of the target gateway's busyness as the idleness, and using the logarithmic function and correction parameter to correct the idleness; Obtain the network communication performance parameters of the target gateway, and calculate the percentage of the actual bandwidth used to the total bandwidth to obtain the bandwidth utilization rate; The ratio of the corrected idle level to the bandwidth utilization is used as the feedback incentive of the target gateway.

5. The data transmission method of an industrial edge gateway according to claim 1, characterized in that: The step of adjusting the data queue through which the edge gateway transmits data to the cloud server includes: Each edge gateway initializes each data queue. The initialization is that at the initial moment, the feedback incentive for each edge gateway to transmit data through each data queue is 0, then a data queue is randomly selected for data transmission, and a new feedback incentive is calculated according to the transmission result. Repeat the iteration to calculate the average feedback incentive for the edge gateway to transmit data to the cloud server through each data queue, and calculate the confidence of each edge gateway to transmit data to the cloud server through each data queue, and select the data queue with the largest confidence to transmit data to the cloud server.

6. A data transmission system for an industrial edge gateway, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the data transmission method of the industrial edge gateway according to any one of claims 1 to 5 is implemented.

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