User traffic distribution management method and system for traffic pool

Abstract

The invention discloses a user traffic distribution management method and system for a traffic pool, and relates to the field of traffic distribution management, and the main scheme is as follows: generating a process number according to order data; calculating a process priority weight through the process characteristic parameters; calculating a channel quality attenuation factor and a distribution bandwidth through the network performance parameters; calculating a load index value of the equipment by acquiring the equipment state parameters; carrying out comprehensive analysis through the parameters to obtain a dynamic bandwidth allocation quantity; the total bandwidth of the flow pool is allocated according to the dynamic bandwidth allocation quantity; judging whether to execute a shunting evaluation instruction or not through an equipment state parameter load balancing evaluation threshold value; calculating a distribution benefit evaluation value according to the distribution benefit data; and comparing the distribution benefit evaluation value with the distribution benefit evaluation threshold value, and judging whether to execute the distribution instruction, thereby solving the problems that the order data is not associated with the production equipment, so that the resource distribution is extensive, and the flow distribution management is lack of flexibility and dynamic adaptability.

Description

Technical Field

[0001] The present invention relates to the field of traffic allocation management, and specifically to a method and system for user traffic allocation management in a traffic pool. Background Art

[0002] With the continuous expansion of industrial production scale and the increasing improvement of automation degree, the data interaction between production equipment and the demand for network traffic in various production processes show an explosive growth. As a key resource for centralized management and allocation of network traffic, the traffic pool plays a crucial role in the industrial production field. An efficient user traffic allocation management method can ensure that each production equipment can obtain the required network traffic in a timely and stable manner at different production stages, thereby improving production efficiency, optimizing production processes and reducing production costs. This has broad application prospects in emerging fields such as intelligent manufacturing and industrial Internet of Things.

[0003] During the industrial production process, there are significant differences in the workload, priority and network bandwidth requirements of different processes. At the same time, the operating state of production equipment will also change dynamically, affecting its traffic processing capacity and demand level. In addition, the performance and stability of the network itself will also fluctuate over time. In order to ensure the efficient and stable operation of the entire production system, it is necessary to adopt a user traffic allocation management method that comprehensively considers various factors to achieve dynamic and accurate allocation of the traffic pool.

[0004] Existing user traffic allocation management methods for traffic pools have defects. For example, most methods fail to fully combine the relevance between order data and production equipment when allocating traffic, and cannot accurately match equipment according to the production requirements of orders and reasonably plan the initial traffic allocation, resulting in extensive resource allocation and inability to meet the refined traffic requirements of order production processes. In terms of network bandwidth allocation, existing methods usually do not fully consider the channel quality attenuation factor and cannot accurately calculate the reasonable allocated bandwidth of each channel based on real-time network performance, which in turn leads to waste of bandwidth resources or overload of some channels from time to time, affecting the stability and efficiency of network transmission. Existing methods have deficiencies in load balancing and shunt evaluation after traffic allocation, lacking effective dynamic evaluation mechanisms and shunt benefit evaluation means, unable to timely detect load imbalance problems caused by unreasonable traffic allocation, nor accurately judge the actual necessity and benefits of shunt operations, making traffic allocation management lack flexibility and dynamic adaptability and difficult to cope with the complex and changeable traffic demand changes in the industrial production environment. Summary of the Invention

[0005] (I) Technical Problems to be Solved In view of the deficiencies of the prior art, the present invention provides a method for managing user traffic allocation in a traffic pool, which at least solves the problems in the prior art that order data has no association with production equipment, resulting in extensive resource allocation, and the traffic allocation management lacks flexibility and dynamic adaptability.

[0006] (II) Technical Solution To achieve the above objectives, the present invention is realized through the following technical solutions: A method for managing user traffic allocation in a traffic pool includes: Step 1: Obtain order data according to the order management system, match the corresponding production equipment according to the order data, and generate a work order traffic label; Step 2: Obtain process characteristic parameters corresponding to the process number through the manufacturing execution system, and calculate the process priority weight through the process characteristic parameters; Step 3: Obtain network performance parameters through the network management system, calculate the channel quality attenuation factor according to the network performance parameters, and calculate the allocated bandwidth of the channel based on the channel quality attenuation factor; Step 4: Obtain the equipment status parameters of the production equipment corresponding to the process number through the industrial monitoring system; and calculate the load index value of the equipment by analyzing the equipment status parameters; Step 5: Through comprehensive analysis of the allocated bandwidth, load index value, and process priority weight, obtain the dynamic bandwidth allocation amount; and allocate the total bandwidth of the traffic pool according to the dynamic bandwidth allocation amount; Step 6: Set the load balancing evaluation threshold; collect the equipment status parameters in real time, and determine whether to execute the shunt evaluation instruction through the equipment status parameter load balancing evaluation threshold; Step 7: When it is determined to execute the shunt evaluation instruction, obtain the shunt benefit data, and calculate the shunt benefit evaluation value according to the shunt benefit data; set the shunt benefit evaluation threshold, compare the shunt benefit evaluation value with the shunt benefit evaluation threshold, and determine whether to execute the shunt instruction.

[0007] In the above method for managing user traffic allocation in a traffic pool, the process characteristic parameters include a delay sensitivity coefficient, a data volume weight, and a process stability factor; Calculate the process priority weight W i , according to the following formula: ; Among them, W i represents the process priority weight of the i-th production process; α i represents the delay sensitivity coefficient of the i-th production process; β i represents the data volume weight of the i-th production process; γ iRepresents the process stability factor of the i-th production process, where i represents the process number of the production process and n represents the total number of production processes.

[0008] In the above user traffic allocation management method for a traffic pool, the network performance parameters include the end-to-end delay δ and the square of the jitter variance σ 2 , and the end-to-end delay δ is obtained by analyzing the timestamps of the transmitted data through the client-server model; the square of the jitter variance σ 2 captures the timestamp sequence through a functional network probe, then calculates the jitter variance of the packet arrival time, and obtains it through square calculation.

[0009] In the above user traffic allocation management method for a traffic pool, the channel quality attenuation factor is calculated according to the network performance parameters, and the formula is as follows: ; Among them, Q ch represents the channel quality attenuation factor of channel ch; δ ch represents the end-to-end delay of channel ch, represents the square of the jitter variance of channel ch, and ch represents the serial number of the channel; Based on the channel quality attenuation factor Q ch calculates the allocated bandwidth B of the channel ch , and the formula is: ; among them, B ch represents the allocated bandwidth of channel ch, Btotal represents the total bandwidth, and K represents the total number of channels.

[0010] In the above user traffic allocation management method for a traffic pool, the device status parameters include CPU utilization rate, TCP retransmission rate, and concurrent connection number; among them, the CPU utilization rate is collected through the gateway built in the production device; the TCP retransmission rate is obtained by calculating the ratio of the number of retransmitted packets to the total number of sent packets through a network traffic monitoring tool, and the formula is: TCP retransmission rate = number of retransmitted packets / total number of sent packets * 100%; the concurrent connection number can be obtained by statistically counting the current active TCP / UDP connection numbers in real time; And the load index value is calculated from the CPU utilization rate, TCP retransmission rate, and concurrent connection number.

[0011] In the above user traffic allocation management method for a traffic pool, combining the allocated bandwidth, load index value, and process priority weight, the dynamic bandwidth allocation amount is calculated, and the formula is: ; Among them, B i (t) represents the dynamic bandwidth allocation amount of the device corresponding to the i-th production process at time t; Bch Represents the reference value of the bandwidth allocation amount; λ i η(i)(t) represents the load index value of the device corresponding to the i-th production process at time t; ch η(ch)(t) represents the bandwidth occupancy rate of the ch-th channel at time t.

[0012] In the above user traffic allocation and management method for a traffic pool, by analyzing the bandwidth occupancy rate η(ch)(t) ch and the load index value η(i)(t), the formula for obtaining the load balancing index L(t) is: λ i ; ; where L(t) represents the load balancing index at time t, λ threshold ηmax is the preset upper limit of device load; threshold ηchmax is the upper limit of bandwidth occupancy rate; Compare the load balancing index L(t) with the load balancing evaluation threshold. When the load balancing index L(t) ≥ the load balancing evaluation threshold, execute the shunt evaluation instruction; when the load balancing index L(t) < the load balancing evaluation threshold, do not execute the shunt evaluation instruction.

[0013] In the above user traffic allocation and management method for a traffic pool, the shunt benefit data includes the original broadband demand Bor i and the saved bandwidth Bsa i ; among them, the original broadband demand is set according to the device specifications; the saved bandwidth is obtained by comparing the port traffic statistics before and after shunt.

[0014] In the above user traffic allocation and management method for a traffic pool, calculate the shunt benefit evaluation value E i according to the original broadband demand Bor i and the saved bandwidth Bsa of , and the formula is: ; where E of represents the shunt benefit evaluation value, Bsa i represents the bandwidth required for the data block of the device corresponding to the i-th production process before shunt; Bor i represents the bandwidth released by the main channel after the data block of the device corresponding to the i-th production process is shunted to the edge node; Qt ch is the target channel quality value; Qe ch is the edge node quality value; Compare the shunt benefit evaluation value E of with the shunt benefit evaluation threshold. When the shunt benefit evaluation value Eof When it is ≥ the shunt benefit evaluation threshold, it is determined that the shunt instruction is valid, and the shunt instruction is executed; when the shunt benefit evaluation value E of < the shunt benefit evaluation threshold, it is determined that the shunt instruction is invalid, and the current allocation is maintained.

[0015] (III) Beneficial effects The present invention provides a method for managing user traffic allocation in a traffic pool, which has the following beneficial effects: (1) By accurately matching orders with production equipment, the generated work order traffic label is like a personalized traffic ID card, providing a reliable basis for subsequent targeted traffic allocation. Compared with the traditional relatively general traffic allocation method, this matching based on order data can effectively avoid the disconnection between traffic allocation and production requirements, and improve production efficiency.

[0016] (2) By collecting device status parameters to calculate the load index value, this provides a real-time reference for the device operation status for dynamic traffic allocation. When the device is running at high load, the traditional traffic allocation method may cause the device to malfunction due to overload. However, with the device load index value, traffic can be reasonably allocated according to the device's bearing capacity, avoiding device failures, extending the service life of the device, and at the same time optimizing the production process to make the entire production system more stable and efficient.

[0017] (3) Obtaining network performance parameters and calculating the channel quality attenuation factor and channel allocation bandwidth can achieve accurate bandwidth allocation in a complex network environment. By calculating the channel quality attenuation factor, the transmission quality of each channel can be quantified, and then the bandwidth can be reasonably allocated. This is like allocating vehicle traffic according to the road conditions of different roads in traffic management, avoiding the situation where some channels are congested while others are idle. In an automated production workshop, this bandwidth allocation method based on network performance can ensure that key production links such as the instruction transmission and real-time data collection of the automated control system can preferentially obtain sufficient bandwidth, ensuring the continuity and accuracy of production, and reducing production delays and product quality degradation caused by network congestion.

[0018] (4) Comprehensive analysis of the allocated bandwidth, load index value, and process priority weight to obtain the dynamic bandwidth allocation amount and based on this for total bandwidth allocation is a highly intelligent traffic management strategy. In modern industrial production, the production process is complex and changeable, and the priority between processes will change dynamically according to various factors such as order urgency and production progress. At the same time, the device load and network bandwidth also fluctuate in real time. Through this comprehensive analysis method, traffic allocation can be adjusted dynamically in real time to meet the production requirements of different processes at different times.

[0019] (5) The load balancing evaluation and shunt evaluation mechanisms further enhance the flexibility and reliability of traffic allocation. When abnormal conditions occur in device load or network bandwidth, they can promptly detect and make adjustments through measures such as shunting, avoiding local problems from affecting the normal operation of the entire production system, thereby improving the stability and efficiency of the entire industrial production and reducing the risks of increased production costs and decreased production efficiency caused by unreasonable traffic allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic diagram of the steps of a method for managing user traffic allocation in a traffic pool according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] Embodiment 1

[0023] Please refer to Figure 1 , the present invention provides a method for managing user traffic allocation in a traffic pool, including: Step 1: Obtain order data according to the order management system, match the corresponding production equipment according to the order data; and generate a process number according to the order data.

[0024] Specifically: The order management system obtains order data, which at least includes product process requirements and process routes, selects the corresponding production equipment according to the process requirements, determines the sequence of each production process and the corresponding required equipment according to the process route, and generates a process number based on each production process.

[0025] It should be noted that the precise docking of order production and process numbers is achieved. The process number provides a clear basis for subsequent traffic allocation, enabling each process to obtain corresponding traffic resources according to its specific role and requirements in order production, improving production efficiency, ensuring product quality, optimizing the production process, and reducing production costs; solving the problem that traditional traffic allocation methods are difficult to accurately allocate traffic according to the specific production requirements of orders, resulting in the disconnection between traffic allocation and actual production needs, and possible problems such as insufficient traffic for key processes or excessive traffic for non-key processes, which affect production efficiency and product quality.

[0026] Step 2: Obtain the process characteristic parameters of the production process corresponding to the process number through the manufacturing execution system, and calculate the process priority weight W i .

[0027] It should be noted that during the calculation of the process priority weight W i , it is necessary to perform normalization parameter preprocessing on all parameters involved in each calculation step to eliminate the dimensions of different parameters for subsequent formula calculations.

[0028] It should be noted that the process characteristic parameters include the delay sensitivity coefficient, data magnitude weight, and process stability factor.

[0029] Step 201: The MES system calculates the delay sensitivity coefficient α of different production processes by parsing the work order process file and integrating PLC control data i . The formula is as follows: , where e is the base of the natural logarithm, JZ is the reference delay value, that is, the maximum allowable delay preset in the process file; SZ is the actual delay, that is, the actual delay value statistically obtained through the PLC control cycle or historical flow log, and k is an adjustment coefficient with a value range of 0 - 1; GY is the process sensitivity coefficient, that is, the sensitivity coefficient preset according to the process type, with a value range of (0, 1], for example, it can take the value of 1 for precision assembly and 0.5 for ordinary spraying, etc.

[0030] It should be noted that in the formula is the S - type function (Logistic function), and its output range is from 0 to 1. When SZ < JZ, the output approaches 0, indicating that the delay is within the allowable range; when SZ > JZ, the output approaches 1, indicating that the delay exceeds the threshold. The larger the k value, the steeper the S - type curve, and the more significant the impact of the delay on α n . For example, when k = 1, for every 0.1 - second increase in SZ, the change in α n may jump from 0.1 to 0.9; when k = 0.3, the change is more gentle. GY, as a multiplier factor, directly amplifies or shrinks the range of α n . For example, when GY = 1 for precision assembly, the value of α n is completely determined by the S - type function; when GY = 0.5 for ordinary spraying, the maximum value of α n is only 0.5, reflecting a higher tolerance for delay. By adjusting k and GY, different production scenarios can be adapted to solve the problem that traditional methods rely on manual experience to judge delays and lack a scientific basis. For example, manual judgment may only rely on vague descriptions such as "long delay" and cannot distinguish the specific impacts of a 1 - second delay and a 2 - second delay. Fixed thresholds cannot meet the sensitivity requirements of different processes. For example, precision assembly requires strict control of delays, while ordinary spraying has a higher tolerance for delays, etc., showing insufficient dynamic adaptability.

[0031] Step 202 uses the statistical analysis function of the MES system's historical flow logs to calculate the data volume weight βi. The calculation formula is as follows: ; where HD is the moving window mean, which is extracted from the historical flow logs by the MES system, sampled every 5 seconds, and calculates the average data volume of the current process; BD is the data fluctuation coefficient, and the calculation method is: data fluctuation coefficient BD = moving window standard deviation / moving window mean * 100%; ZS represents the reference data volume, and the average data volume of the same process for a period of time under the past normal working conditions automatically counted by the MES system can be used as the reference data volume.

[0032] It should be noted that: in the formula reflects the impact of data volatility on the weight. For example, when BD = 0% (no volatility), 1 + 0 / 100 = 1, β i = HD / ZS; when BD = 20% (high volatility), 1 + 20 / 100 = 1.2, β i = 1.2×(HD / ZS); to avoid the problem that the impact of volatility on resource allocation is ignored; through automated cleaning and multi-window averaging, ZS is closer to the true stable value. Avoiding the influence of manual setting of ZS by experience deviation, through the synergistic effect of dynamic weight calculation, volatility sensitivity adjustment, and reference data automation, the core problems such as weight distortion, resource rigidity, and reference subjectivity in traditional flow allocation are solved. HD in the formula reflects the real-time load, BD quantifies the volatility risk, and ZS provides a standardized reference. The combination of the three realizes the scientificity, flexibility, and stability of resource allocation.

[0033] Step 203: The MES system directly associates with production quality data and generates a process stability factor γ through the comparison of the qualified product rate with the reference value i , and the calculation method is γ = current process qualified product rate / production line reference qualified product rate.

[0034] It should be noted that γi dynamically reflects the stability of flow processing. For example, when γi = 1, it means that the current quality meets the standard; when γi < 1, it prompts that the processing strategy needs to be optimized Step 204: Calculate the process priority weight W through process characteristic parameters i , and the formula is as follows: ; where W i represents the process priority weight of the i-th production process; α i represents the delay sensitivity coefficient of the i-th production process; β i represents the data volume weight of the i-th production process; γ iDenote the process stability factor of the \(i\)-th production process, where \(i\) represents the process number of the production process, taking positive integer values, and \(n\) represents the total number of production processes.

[0035] It should be noted that the α in the numerator i can be used to adjust the weight of delay-sensitive traffic, perform a logarithmic transformation on βi to mitigate the excessive influence of large traffic on the weight. For example, when βi = 10, ln(11) = 2.4; when βi = 100, ln(101) = 4.6, to avoid small traffic being completely ignored due to data magnitude differences; the denominator normalization compresses the weights of all traffic into the interval [0, 1] for easy direct comparison. For example, if the sum is 100, then a certain traffic's W i = 0.1 means it occupies 10% of the resource quota. The α i , β i , γ i in the formula correspond to delay sensitivity, data magnitude, and stability respectively. Combining logarithmic transformation and normalization processing realizes dynamic and accurate traffic scheduling.

[0036] Step 3: Obtain network performance parameters through the network management system, and calculate the channel quality attenuation factor Q ch based on the channel quality attenuation factor Q ch calculate the allocated bandwidth B ch of the channel.

[0037] It should be noted that during the process of calculating the allocated bandwidth B ch , it is necessary to perform normalized parameter preprocessing on all parameters involved in each calculation step to eliminate the dimension of different parameters for subsequent formula calculation.

[0038] It should be noted that the network performance parameters include the end-to-end delay δ and the square of the jitter variance σ 2 .

[0039] Step 301: The end-to-end delay δ represents the end-to-end delay of the two-way transmission delay from the production end to the device end. The end-to-end delay δ can be calculated through the client-server model of the TWAMP protocol (RFC5357) by calculating four timestamps. The formula is: ; where t1 is the sending time of the Sender, t1' is the receiving time of the Reflector, t2' is the response time of the Reflector, and t2 is the receiving time of the Sender. Calculating the difference of the four timestamps eliminates the one-way delay error, which is applicable to scenarios such as dynamic routing and load balancing to ensure the stability and reliability of the delay measurement results.

[0040] Step 302: Use a functional network probe (such as PLC-Recorder), TWAMP or UDP protocol to capture the timestamp sequence, and calculate the mean μ of the packet arrival time intervals within the time period; and calculate the square σ of the jitter variance of the packet arrival time. The formula is as follows: 2 , the formula is: ; where t m represents the arrival timestamp of the m-th packet, m represents the packet sequence number, taking positive integer values, and M represents the total number of packets.

[0041] Step 303: Calculate the channel quality attenuation factor Q of the channel according to the network performance parameters ch , and the formula is as follows: ; Among them, Q ch represents the channel quality attenuation factor of channel ch; δ ch represents the end-to-end delay of channel ch, represents the square of the jitter variance of channel ch, and ch represents the channel sequence number, taking positive integer values. Dynamically adjust the traffic allocation weight according to Q ch .

[0042] This solution solves the core problems such as inaccurate channel quality assessment in the traffic pool, strong subjectivity in resource allocation, and unquantified influence of jitter through the three-stage linkage of end-to-end delay measurement, jitter quantization analysis, and comprehensive channel quality assessment. δ, σ², and Q in the formula ch correspond to delay, jitter, and quality score respectively, and realize dynamic weight allocation by combining the exponential function and the fractional function, which can improve the accuracy of channel quality assessment and optimize resource utilization.

[0043] Step 304: Calculate the allocated bandwidth B of the channel based on the channel quality attenuation factor Q ch , and the formula is as follows: ch ; where B represents the allocated bandwidth of channel ch, Btotal represents the total bandwidth, and K represents the total number of channels. ch

[0044] Step 4: Obtain the equipment status parameters of the production equipment corresponding to the process number through the industrial monitoring system; and calculate the load index value of the equipment by analyzing the equipment status parameters λ i .

[0045] It should be noted that in the process of calculating the load index value λ i , it is necessary to perform normalized parameter preprocessing on all parameters involved in each calculation step to eliminate the dimension of different parameters for subsequent formula calculation. ​

[0046] It should be noted that the device status parameters include CPU utilization rate, TCP retransmission rate, and concurrent connection count; Step 401: The CPU utilization rate can be collected through sensors built into the production device or industrial gateways (such as PLCs, industrial PCs); the TCP retransmission rate can be calculated by counting the number of retransmitted packets and the total number of sent packets through the logs of network traffic monitoring tools (such as Wireshark, NetFlow) or network devices (such as switches, routers). The formula for calculating the TCP retransmission rate is: TCP retransmission rate = number of retransmitted packets / total number of sent packets * 100%; The NetFlow or sFlow protocol is used to count the current active TCP / UDP connection count in real time.

[0047] Step 402: Calculate the load index value based on the CPU utilization rate, TCP retransmission rate, and concurrent connection count. The formula used is: λ = 0.4 * CPU utilization rate + 0.3 * TCP retransmission rate + 0.3 * concurrent connection count.

[0048] Step Five: Through comprehensive analysis of the allocated bandwidth B ch , the load index value λ i and the process priority weight W i , obtain the dynamic bandwidth allocation amount B i (t), and allocate the total bandwidth of the traffic pool according to the dynamic bandwidth allocation amount B i .

[0049] It should be noted that during the process of calculating the dynamic bandwidth allocation amount B i (t), it is necessary to perform normalized parameter preprocessing on all parameters involved in each calculation step to eliminate the dimensions of different parameters for subsequent formula calculations.

[0050] Specifically: Combining the allocated bandwidth B ch , the load index value λ i and the process priority weight W i , obtain the dynamic bandwidth allocation amount through comprehensive calculation. The formula used is: ; where B i (t) represents the dynamic bandwidth allocation amount of the device corresponding to the i-th production process at time t; B ch represents the reference value of the bandwidth allocation amount; λ i (t) represents the load index value of the device corresponding to the i-th production process at time t; η ch (t) represents the bandwidth occupancy rate of the ch-th channel at time t.

[0051] It should be noted that each production process i corresponds to one of the channels ch; for example, the channel ch is divided into a low-latency channel L0, a high-bandwidth channel L1, and an edge channel L2; when the delay sensitivity coefficient α i is greater than the set threshold, such as α i ≥0.9, the low-latency channel L0 is selected; when the data volume weight is greater than that of the medium-latency channel and the high-latency channel, such as β i ≥0.8, the high-bandwidth channel L1 is selected; otherwise, the edge channel L2 is selected; all processes are corresponded to the corresponding channels, so that a mapping relationship is formed between the production process i and the channel number ch; during the calculation process, when the value of the production process i is 1, it corresponds to the robotic arm control instruction, corresponding to a highly sensitive process, associated with the serial number channel 1 of the low-latency channel, and the B value of the low-latency channel L0 is selected. ch Value.

[0052] It should be noted that through the three-way linkage of the dynamic bandwidth allocation formula, parameter normalization processing, and real-time comprehensive analysis, problems such as rigid resource allocation in the traffic pool, priority and load conflicts, and calculation distortion are solved. B, W, η(t), in the formula respectively correspond to the reference bandwidth, priority, remaining bandwidth, and load index. Combined with the square root and normalization processing, flexible and precise bandwidth management is achieved. ch 、W i 、η ch (t)、 λ i (t) correspond to the reference bandwidth, priority, remaining bandwidth, and load index respectively. Combined with the square root and normalization processing, flexible and precise bandwidth management is achieved.

[0053] Step 6: Set the load balancing evaluation threshold; collect the bandwidth occupancy rate η ch (t) and the load index value λ i (t) in real time, and analyze the bandwidth occupancy rate η ch (t) and the load index value λ i (t) to obtain the load balancing index L(t); compare the load balancing index L(t) with the load balancing evaluation threshold to determine whether to execute the shunt evaluation instruction.

[0054] It should be noted that during the calculation of L(t), it is necessary to perform normalization parameter preprocessing on all parameters involved in each calculation step to eliminate the dimensions of different parameters for the convenience of subsequent formula calculation.

[0055] Step 601: Set the load balancing evaluation threshold. The load balancing index L(t) is used to represent the dual overrun risk index of device load and bandwidth occupancy. When L(t)>1, it means the load index value λ i (t) or the bandwidth occupancy rate η iWhen any index exceeds the preset safety upper limit, the system needs to immediately determine whether to divert to avoid risks. Therefore, the load balancing evaluation threshold can be set to 1, and a safety factor φ can be superimposed on the basis of the threshold 1. φ can take values from 0.1 to 0.2. The diversion execution condition is L(t)>1 + φ to prevent the risk of false triggering due to instantaneous fluctuations.

[0056] Step 602: By analyzing the bandwidth occupancy rate η ch (t) and the load index value λ i (t), the formula for obtaining the load balancing index L(t) is: ; where L(t) represents the load balancing index at time t, λ threshold is the preset upper limit of device load; η threshold is the upper limit of bandwidth occupancy rate.

[0057] Step 603: Compare the load balancing index L(t) with the load balancing evaluation threshold. When the load balancing index L(t) ≥ the load balancing evaluation threshold, execute the diversion evaluation instruction; when the load balancing index L(t) < the load balancing evaluation threshold, do not execute the diversion evaluation instruction.

[0058] Step Seven, when it is determined to execute the diversion evaluation instruction, obtain the diversion benefit data, and calculate the diversion benefit evaluation value E of , set the diversion benefit evaluation threshold, and compare the diversion benefit evaluation value E of with the diversion benefit evaluation threshold to determine whether to execute the diversion instruction.

[0059] It should be noted that Calculate the average load index of all n devices to reflect the overall device load status. Divide by λ threshold represents the degree to which the device load approaches the threshold. For example, if the average load is 70% and the threshold is 80%, the ratio is 0.875, indicating that the device load is approaching overload. Calculate the average bandwidth occupancy rate of all K channels to reflect the overall channel load status. Divide by η thresholdIndicates the degree to which the channel bandwidth approaches the threshold. For example, if the average bandwidth is 65% and the threshold is 70%, the ratio is 0.928, indicating that the channel is approaching overload. By taking the maximum ratio of device load and channel bandwidth, it is ensured that any dimension overload can trigger adjustment. For example, when the device load ratio is 0.9 (close to the threshold) and the channel bandwidth ratio is 0.8, L(t)=0.9, indicating that the device load needs to be optimized first. L(t) directly reflects the critical state of system load, providing a quantitative basis for subsequent traffic splitting decisions. For example, when L(t)≥1, it indicates that at least one dimension is overloaded and traffic splitting needs to be performed.

[0060] The comparison between the load balancing index L(t) and the evaluation threshold and the execution of the traffic splitting evaluation instruction solve the problems that the fixed allocation rule cannot cope with dynamic load changes, excessive resource reservation reduces utilization, and insufficient resources lead to a decline in service quality. It dynamically responds to load fluctuations. When L(t)≥1, traffic splitting evaluation is immediately initiated (such as directing traffic to a backup channel or a low-load device) to avoid system crashes. For example, if the channel bandwidth ratio is 1.2 (exceeding the threshold), the bandwidth ratio drops to 0.9 after traffic splitting. When L(t)<1, the current allocation strategy is maintained to reduce unnecessary resource consumption (such as avoiding energy consumption waste of idle channels).

[0061] The solution solves the problems of incomplete evaluation of device / channel load in the traffic pool and rigid resource allocation through the linkage of the calculation of the load balancing index L(t) and dynamic traffic splitting decisions. The device load ratio and channel bandwidth ratio in the formula quantify the load status of two key dimensions respectively, and the maximum value logic ensures the highest priority of system risks. The dynamic comparison mechanism realizes "adjustment on demand", performs traffic splitting in a timely manner when the load is high, and maintains efficient utilization when the load is low, ultimately improving system stability and service quality.

[0062] It should be noted that during the calculation of the traffic splitting benefit evaluation value E of , all parameters involved in each calculation step need to be preprocessed with normalized parameters to eliminate the dimensions of different parameters for subsequent formula calculations.

[0063] It should be noted that the traffic splitting benefit data includes the original broadband demand Bor i and the saved bandwidth Bsa i ; Step 701: The original broadband demand Bor i can be set according to the device specifications; the saved bandwidth Bsa i can be obtained by comparing the port traffic statistics before and after traffic splitting. The calculation formula is: Bsa g =Bor g - (1 - the occupancy rate of the main channel after traffic splitting); where, the occupancy rate of the main channel after traffic splitting = (original bandwidth - cache bandwidth) / original bandwidth.

[0064] Step 702: Calculate the shunt benefit evaluation value E based on the original broadband demand Bor i and the bandwidth savings Bsa i The formula used is: of , and the formula is: ; where E of represents the shunt benefit evaluation value, Bsa i represents the bandwidth required for the data block of the device corresponding to the i-th production process before shunting; Bor i represents the bandwidth released by the main channel after the data block of the device corresponding to the i-th production process is shunted to the edge node; Qt ch is the target channel quality value, which can be expressed as the minimum quality benchmark that the channel ch needs to reach, and the value range is (0, 1]. The calculation formula is: target channel quality value Qt ch = benchmark good product rate / current good product rate; Qe ch is the edge node quality value, which is used to quantify the effectiveness of the edge node cache service. The calculation method is: Qe ch = amount of successfully transmitted data / total amount of data in the edge cache.

[0065] It should be noted that the E of formula combines bandwidth savings (Bsa i ), channel quality (Qt ch ), and edge node efficiency (Qe ch ) to provide multi-dimensional evaluation. The solution solves the core problems such as the ambiguity of resource allocation in the traffic pool, the difficulty in quantifying the shunt effect, and the lack of multi-dimensional benefit evaluation through the coordination of the original broadband demand and the calculation of bandwidth savings and the comprehensive evaluation of shunt benefits. Through Bor and Bsa, the scientific setting of bandwidth demand and the accurate quantification of savings are realized. Through the Eof formula, which synthesizes bandwidth savings, channel quality, and edge node efficiency, it is ensured that the shunt strategy can save resources while guaranteeing service quality.

[0066] Step 703: Set the shunt benefit evaluation threshold. When the shunt benefit evaluation value is 1, it reaches the balance point. To ensure that the shunt operation has a significant net benefit, a safety factor θ can be set. The shunt benefit evaluation threshold = 1.0 + θ, and the safety factor θ can take values in the range (0, 1), which can be adjusted according to actual needs but cannot be less than 0.

[0067] Step 704: Compare the shunt benefit evaluation value E of with the shunt benefit evaluation threshold. When the shunt benefit evaluation value E of ≥ the shunt benefit evaluation threshold, it is determined that the shunt instruction is valid and the shunt instruction is executed; when the shunt benefit evaluation value E ofWhen the value is less than the diversion benefit evaluation threshold, the diversion instruction is judged to be invalid and the current allocation is maintained.

[0068] It should be noted that the formula is used to quantify the diversion benefit benchmark to ensure that the decision is based on objective data. For example, when the threshold is 1.2, only E of Only when the value of θ is ≥1.2 will the diversion operation be executed, avoiding invalid diversion of "barely balanced". The introduction of θ raises the profit threshold of diversion operation and reduces the risk of misjudgment caused by small fluctuations. For example, in the scenario of network jitter, θ=0.1 can filter out low-efficiency diversion caused by short-term jitter. The adjustability of θ enables the solution to adapt to different business needs. For example, during peak hours, θ=0.3 (threshold=1.3) is set to ensure that the diversion operation significantly improves resource utilization; during off-peak hours, θ=0.1 (threshold=1.1) is set to allow more flexible diversion. The scientific nature of the diversion operation is ensured through quantitative comparison. For example, a diversion operation E of =1.5 (higher than the threshold of 1.2), indicating that its benefits are significant and can be executed first; if E of = 1.05 (below the threshold), avoid execution. of Execute diversion when the value is ≥ the threshold to maximize resource utilization efficiency. Maintain the current allocation strategy to avoid low-efficiency operations and reduce system jitter. The solution solves the three core problems of subjective decision-making, resource waste, and system instability in traffic pool allocation by linking the diversion benefit evaluation threshold setting and the benefit value comparison mechanism.

[0069] Example 2 A user traffic allocation management system for a traffic pool, used to implement the above-mentioned user traffic allocation management method for a traffic pool.

[0070] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented using software, the above embodiments may be implemented in whole or in part in the form of a computer program product. A person of ordinary skill in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented in electronic hardware or in combination with computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution.

[0071] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0072] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application.

Claims

1. A user traffic allocation and management method for a traffic pool, characterized in that, Including: Step 1: Obtain order data according to the order management system, match the corresponding production equipment according to the order data, and generate work order traffic tags; Step 2: Obtain process characteristic parameters corresponding to the process number through the manufacturing execution system, and calculate the process priority weight through the process characteristic parameters; Step 3: Obtain network performance parameters through the network management system, calculate the channel quality attenuation factor according to the network performance parameters, and calculate the allocated bandwidth of the channel based on the channel quality attenuation factor; Step 4: Obtain the equipment status parameters of the production equipment corresponding to the process number through the industrial monitoring system; and calculate the load index value of the equipment by analyzing the equipment status parameters; Step 5: Through comprehensive analysis of the allocated bandwidth, load index value, and process priority weight, obtain the dynamic bandwidth allocation amount; and allocate the total bandwidth of the traffic pool according to the dynamic bandwidth allocation amount; Step 6: Set the load balancing evaluation threshold; Collect equipment status parameters in real time, and judge whether to execute the shunt evaluation instruction through the equipment status parameter load balancing evaluation threshold; Step 7: When it is judged to execute the shunt evaluation instruction, obtain the shunt benefit data, and calculate the shunt benefit evaluation value according to the shunt benefit data; Set the shunt benefit evaluation threshold, compare the shunt benefit evaluation value with the shunt benefit evaluation threshold, and judge whether to execute the shunt instruction.

2. The user traffic allocation management method for a traffic pool according to claim 1, wherein The process characteristic parameters include a delay sensitivity coefficient, a data volume weight, and a process stability factor; A user traffic allocation management method for a traffic pool, characterized in that the process characteristic parameters include a delay sensitivity coefficient, a data volume weight, and a process stability factor; Calculate the process priority weight W based on process characteristic parameters i , and the formula is as follows: ； Among them, W i represents the process priority weight of the i-th production process; α i represents the delay sensitivity coefficient of the i-th production process; β i represents the data volume level weight of the i-th production process; γ i represents the process stability factor of the i-th production process, where i represents the process number of the production process and n represents the total number of production processes.

3. The user traffic allocation management method for a traffic pool according to claim 2, characterized in that The network performance parameters include the end-to-end delay δ and the square of the jitter variance σ 2 , the end-to-end delay δ is obtained by analyzing the timestamps of the transmitted data through the client-server model; the square of the jitter variance σ 2 is obtained by capturing the timestamp sequence through the functional network probe, then calculating the jitter variance of the packet arrival time, and performing a square calculation.

4. The user traffic allocation management method for a traffic pool according to claim 3, characterized in that Calculate the channel quality attenuation factor according to the network performance parameters, and the formula is as follows: Among them, Q ch represents the channel quality attenuation factor of channel ch; δ ch represents the end-to-end delay of channel ch, represents the square of the jitter variance of channel ch, where ch represents the channel number; Based on the channel quality attenuation factor Q ch Calculate the allocated bandwidth B of the channel ch , and the formula is as follows: ; Among them, B ch represents the allocated bandwidth of channel ch, Btotal represents the total bandwidth, and K represents the total number of channels.

5. A user traffic allocation management method for a traffic pool according to claim 4, characterized in that The equipment status parameters include CPU utilization rate, TCP retransmission rate, and concurrent connection number; Among them, the CPU utilization rate is collected through the gateway built in the production equipment; The TCP retransmission rate is obtained by calculating the number of retransmitted packets and the total number of sent packets through a network traffic monitoring tool, and the formula is: TCP retransmission rate = number of retransmitted packets / total number of sent packets * 100%; The concurrent connection number can be obtained by real-time statistics of the current active TCP / UDP connection number; And calculate the load index value from the CPU utilization rate, TCP retransmission rate, and concurrent connection number.

6. A user traffic allocation management method for a traffic pool according to claim 5, characterized in that, Combined with the allocated bandwidth, load index value, and process priority weight, calculate the dynamic bandwidth allocation amount, and the formula is: ； Among them, B i (t) represents the dynamic bandwidth allocation amount of the device corresponding to the i-th production process at time t; B ch represents the reference value of the bandwidth allocation amount; λ i (t) represents the load index value of the device corresponding to the i-th production process at time t; η ch (t) represents the bandwidth occupancy rate of the ch-th channel at time t.

7. A user traffic allocation management method for a traffic pool according to claim 6, characterized in that, By analyzing the bandwidth occupancy rate η ch (t) and the load index value λ i (t), the formula for obtaining the load balancing index L(t) is as follows: ； where, L(t) represents the load balancing index at time t, λ threshold is the preset upper limit of device load; η threshold is the upper limit of bandwidth occupancy rate; Compare the load balancing index L(t) with the load balancing evaluation threshold. When the load balancing index L(t) ≥ the load balancing evaluation threshold, execute the shunt evaluation instruction; when the load balancing index L(t) < the load balancing evaluation threshold, do not execute the shunt evaluation instruction.

8. A user traffic allocation management method for a traffic pool according to claim 7, characterized in that, The shunt benefit data includes the original broadband demand Bor i and the bandwidth savings Bsa i ; among them, the original broadband demand is set according to the device specifications; the bandwidth savings are obtained by comparing the port traffic statistics before and after shunting.

9. A user traffic allocation management method for a traffic pool according to claim 8, characterized in that, According to the original broadband requirement Bor i and the bandwidth saving Bsa i calculate the shunt benefit evaluation value E of , and the formula based on is as follows: ； Among them, E of represents the shunt benefit evaluation value, Bsa i represents the bandwidth required for the data block of the device corresponding to the i-th production process before shunting; Bor i represents the bandwidth released by the main channel after the data block of the device corresponding to the i-th production process is shunted to the edge node; Qt ch is the target channel quality value; Qe ch is the edge node quality value; Compare the shunt benefit evaluation value E of with the shunt benefit evaluation threshold. When the shunt benefit evaluation value E of ≥ the shunt benefit evaluation threshold, it is determined that the shunt instruction is valid and the shunt instruction is executed; when the shunt benefit evaluation value E of < the shunt benefit evaluation threshold, it is determined that the shunt instruction is invalid and the current allocation is maintained.

10. A user traffic allocation and management system for a traffic pool, characterized in that, A user traffic allocation management method for a traffic pool for implementing any one of the above claims 1-9.

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