Digital twin data transmission optimization method, system and program product

Abstract

The invention belongs to the technical field of digital twinning, and particularly discloses a digital twinning data transmission optimization method and system and a program product, which realize real-time intelligent adjustment of data transmission priority and improve transmission efficiency by constructing a dynamic priority algorithm based on multi-dimensional data characteristics. The accuracy of digital twin data transmission is ensured through a dual guarantee mechanism of data integrity verification and time sequence verification; dynamic balance of transmission efficiency and accuracy is realized by combining bandwidth dynamic allocation and an intelligent retransmission strategy, and the method has extremely high industrial universality; and through dynamic bandwidth allocation and an intelligent compression strategy, the utilization rate of the network bandwidth is remarkably improved, and the data transmission cost of an enterprise is greatly reduced. The industrial problems of low data transmission efficiency and poor accuracy between the physical entity and the digital twinborn body can be effectively solved, and key support is provided for deep application of the digital twinborn technology.

Description

Technical Field

[0001] The present invention belongs to the field of digital twin technology, and specifically relates to a digital twin data transmission optimization method, system and program product. Background Art

[0002] As digital twin technology flourishes, data transmission, as the lifeline for interaction between physical entities and digital twins, directly determines the reliability and practicality of digital twin systems. However, existing digital twin data transmission technology still has the following core flaws: 1. Limitations of static priority transmission mechanisms: Traditional methods use fixed or no priority strategies, which cannot dynamically adjust the transmission order based on the real-time importance and urgency of the data. For example, in smart grid scenarios, equipment failure warning data is transmitted at the same time as regular electricity usage data, resulting in delays in critical warning information and the risk of grid paralysis.

[0003] 2. Limitations of a Single Verification Mode: Traditional methods rely solely on simple parity checks or cyclic redundancy checks (CRCs), making them incapable of addressing issues such as data loss and data disarray in complex network environments. In industrial IoT environments, data transmission error rates can reach as high as 15%-20% due to electromagnetic interference or network congestion, severely disrupting the state consistency between the digital twin and the physical entity.

[0004] 3. Lack of adaptive adjustment capabilities: Traditional solutions are unable to dynamically optimize transmission strategies for different business scenarios and data characteristics, resulting in wasted network resources and low transmission efficiency. For example, in smart city traffic monitoring, real-time video streams and device operating parameter data use the same transmission strategy, resulting in an imbalance in bandwidth resource allocation. Summary of the Invention

[0005] The purpose of the present invention is to provide a digital twin data transmission optimization method, system and program product to solve the above-mentioned problems existing in the prior art.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, a digital twin data transmission optimization method is provided, which is applied to a sending end and includes: Obtaining digital twin data to be transmitted and multi-dimensional characteristic parameters of the digital twin data; The multi-dimensional characteristic parameters of digital twin data are used to perform multi-dimensional dynamic priority allocation calculation to obtain the data priority of digital twin data; Perform dynamic bandwidth allocation calculation on digital twin data according to its data priority to obtain the corresponding allocated bandwidth; Timestamp and encapsulate the digital twin data to obtain the corresponding data packet, and perform hash calculation on the data packet to obtain the corresponding message digest; Based on the allocated bandwidth corresponding to the digital twin data, the data packet and the message digest corresponding to the data packet are transmitted to the receiving end, so that the receiving end uses the message digest to check the data integrity of the data packet, and parses the data packet after the data integrity check passes, and obtains the digital twin data and timestamp, and uses the timestamp to perform time sequence verification, and saves the digital twin data after the time sequence verification passes.

[0007] In one possible design, the multidimensional characteristic parameters include a data importance parameter, a real-time requirement parameter, a data change rate parameter, and a system state parameter. The multidimensional characteristic parameters of the digital twin data are used to perform a multidimensional dynamic priority allocation calculation to obtain the data priority of the digital twin data, including: Substitute the data importance parameter, real-time requirement parameter, data change rate parameter, and system status parameter into the preset multi-dimensional dynamic priority allocation formula to calculate the data priority of the digital twin data. The multi-dimensional dynamic priority allocation formula is:

[0008] Among them, P represents the data priority, I represents the data importance parameter, R represents the real-time demand parameter, C represents the data change rate parameter, S represents the system state parameter, ω1, ω2, ω3 and ω4 are the set first weight coefficient, second weight coefficient, third weight coefficient and fourth weight coefficient respectively.

[0009] In one possible design, the bandwidth dynamic allocation calculation for the digital twin data is performed based on the data priority of the digital twin data to obtain the corresponding allocated bandwidth, including: Substitute the data priority of the digital twin data into the preset intelligent bandwidth dynamic allocation formula to calculate the corresponding allocated bandwidth. The intelligent bandwidth dynamic allocation formula is:

[0010] Among them, B p Characterizes the allocated bandwidth corresponding to the digital twin data p, P p Represents the data priority corresponding to the digital twin data p, n is the total number of digital twin data to be transmitted in the same batch, and p∈[1,n], i represents the number of the digital twin data to be transmitted in the same batch, P i Characterizes the data priority corresponding to digital twin data i, B total represents the total transmission bandwidth, α is the set adjustment coefficient, T max is the maximum allowed waiting time threshold, T pThe waiting time for the digital twin data p to be transmitted.

[0011] In one possible design, performing hash calculation on the data packet to obtain the corresponding message digest includes: The SHA-256 algorithm is used to perform hash calculation on the data packet to obtain the corresponding message digest.

[0012] In one possible design, the method further includes: After obtaining the data integrity check failure information or time sequence check failure information fed back by the receiving end, determine the number of retransmissions of the digital twin data; Substitute the number of retransmissions of the digital twin data into the preset retransmission interval time formula to calculate the retransmission interval time of the digital twin data. The retransmission interval time formula is:

[0013] Among them, T retrans Represents the retransmission interval, T0 is the set initial retransmission interval, and n is the number of retransmissions; After the retransmission interval of the digital twin data is reached, the data packet and the message digest corresponding to the data packet are retransmitted to the receiving end based on the allocated bandwidth corresponding to the digital twin data.

[0014] Another digital twin data transmission optimization method is provided, which is applied to the receiving end and includes: Receive the data packet transmitted by the sender and the message digest corresponding to the data packet; Performing data integrity check on the data packet based on the message digest corresponding to the data packet; When the data integrity check passes, the data packet is parsed to obtain the digital twin data and timestamp; Use timestamps to perform time sequence verification. When the time sequence verification passes, the digital twin data is saved.

[0015] In one possible design, performing data integrity verification on a data packet based on a message digest corresponding to the data packet includes: Perform hash calculation on the data packet to obtain the corresponding hash value to be verified; The hash value to be verified is compared with the message digest corresponding to the data packet. When the hash value to be verified is consistent with the message digest corresponding to the data packet, the data integrity check is determined to have passed. Otherwise, the data integrity check is determined to have failed.

[0016] In one possible design, the time sequence verification using a timestamp includes: Determine the time at which the data packet was received; If the time corresponding to the timestamp is not before the receiving time, the time sequence check is determined to have failed; When the time corresponding to the timestamp is before the receiving time, the time difference between the receiving time and the time corresponding to the timestamp is calculated. When the time difference is greater than the set difference threshold, the time sequence check is determined to have failed. When the time difference does not exceed the set difference threshold, the time sequence check is determined to have passed.

[0017] In a second aspect, a digital twin data transmission optimization system is provided, including a transmitting end and a receiving end, wherein: The sending end is used to obtain the digital twin data to be transmitted and the multi-dimensional characteristic parameters of the digital twin data; use the multi-dimensional characteristic parameters of the digital twin data to perform multi-dimensional dynamic priority allocation calculation to obtain the data priority of the digital twin data; perform bandwidth dynamic allocation calculation on the digital twin data according to the data priority of the digital twin data to obtain the corresponding allocated bandwidth; timestamp and encapsulate the digital twin data to obtain the corresponding data packet, and perform hash calculation on the data packet to obtain the corresponding message digest; based on the allocated bandwidth corresponding to the digital twin data, the data packet and the message digest corresponding to the data packet are transmitted to the receiving end; The receiving end is used to receive the data packet transmitted by the sending end and the message digest corresponding to the data packet; perform data integrity verification on the data packet based on the message digest corresponding to the data packet; when the data integrity verification passes, parse the data packet to obtain digital twin data and timestamp; use the timestamp to perform time sequence verification, and when the time sequence verification passes, save the digital twin data.

[0018] In a third aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions that, when executed on a computer, cause the computer to perform any one of the methods described in the first aspect. Furthermore, a computer program product is provided that, when executed on a computer, performs any one of the methods described in the first aspect.

[0019] Beneficial effects: 1. The present invention can realize dynamic priority intelligent decision-making: by constructing a dynamic priority algorithm based on multi-dimensional data features, it can realize real-time intelligent adjustment of data transmission priority and improve transmission efficiency.

[0020] 2. The present invention can achieve double verification redundancy protection: through the dual protection mechanism of data integrity verification and time sequence verification, the accuracy of digital twin data transmission is ensured.

[0021] 3. The present invention can achieve adaptive transmission optimization: combining dynamic bandwidth allocation with intelligent retransmission strategy to achieve a dynamic balance between transmission efficiency and accuracy, and has strong industry universality.

[0022] 4. The present invention can achieve efficient utilization of network resources: through dynamic bandwidth allocation and intelligent compression strategy, network bandwidth utilization is significantly improved, greatly reducing enterprise data transmission costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 Schematic diagram of the process of the method in Example 1 of the present invention. DETAILED DESCRIPTION

[0025] It should be noted that the description of these embodiments is intended to help understand the present invention, but does not constitute a limitation of the present invention. The specific structural and functional details disclosed herein are merely intended to describe exemplary embodiments of the present invention. However, the present invention may be embodied in a variety of alternative forms, and should not be construed as being limited to the embodiments set forth herein.

[0026] It should be understood that, unless otherwise expressly specified or limited, the corresponding terms should be understood in a broad sense. For example, "connection" can refer to a fixed connection, a detachable connection, or an integral connection; it can refer to a direct connection, an indirect connection through an intermediate medium, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the embodiments based on specific circumstances.

[0027] In the following description, certain details are provided to facilitate a thorough understanding of the example embodiments. However, one skilled in the art will appreciate that the example embodiments may be practiced without these specific details. For example, devices may be shown in block diagrams to avoid obscuring the examples with unnecessary detail. In other embodiments, well-known processes, structures, and techniques may be shown without unnecessary detail to avoid obscuring the embodiments.

[0028] Example 1: This embodiment provides a digital twin data transmission optimization method, which can be applied to a corresponding data transmission system. The data transmission system includes a transmitter and a receiver. The transmitter corresponds to a physical entity, and the receiver corresponds to a digital twin. Figure 1 As shown, the method includes the following steps: S1. The sender obtains the digital twin data to be transmitted and the multi-dimensional characteristic parameters of the digital twin data.

[0029] In specific implementation, the sending end obtains in advance the digital twin data to be transmitted to the digital twin, as well as the multi-dimensional characteristic parameters corresponding to the digital twin data. The multi-dimensional characteristic parameters include data importance parameters, real-time requirement parameters, data change rate parameters, and system status parameters, where: Data Importance Parameter I: Data Importance measures the criticality of the data itself to the business. In practical applications, its value is determined based on a combination of factors such as the data type and the degree of business impact. For example, in a factory equipment data transmission scenario, equipment fault alarm data can be correlated and judged based on the fault level and the impact of historical accidents. The specific rules are: the Data Importance Parameter I for fatal faults (directly causing downtime) is set to 1; the Data Importance Parameter I for severe faults (requiring manual intervention) is set to 0.7; and the Data Importance Parameter I for routine equipment status reporting data is set to 0.3.

[0030] Real-time requirement parameter R: Real-time requirements reflect the requirements for timely transmission of data in business processes, and are usually closely related to the business response threshold. In different business scenarios, the measurement standards for real-time requirements vary. For example, in the factory production line monitoring business, for fault alarm data that may cause equipment shutdown, it is required to respond within 1 second. At this time, the real-time requirement parameter R is set to 1; for general fault alarm data that needs to be responded within 2 seconds, the real-time requirement parameter R is set to 0.8; and for normal status reporting data, a delay of 10 seconds is allowed, and the real-time requirement parameter R is set to 0.3. In addition, real-time requirements also have dynamic adjustment characteristics. When the system finds that a fault response has timed out, the R weight of subsequent similar data may be temporarily increased to ensure the timely transmission of critical data.

[0031] Data change rate parameter C: The data change rate is used to assess the frequency and fluctuation of data updates per unit time. In real-world scenarios, different types of data have different change characteristics. For example, data collected by a device's vibration sensor requires high-frequency acquisition and frequently changes in value, so its data change rate parameter C can be set to 0.8. Static device configuration parameters, on the other hand, tend to remain unchanged over time, so their data change rate parameter C can be set to 0.1. A higher data change rate indicates a higher "freshness" requirement for the data, and thus a higher weight can be assigned in subsequent priority calculations, ensuring that this type of dynamic data is transmitted first.

[0032] System status parameter S: The system status comprehensively reflects the load, health, and other conditions of the data transmission system itself. Specifically, it covers key indicators such as the remaining network bandwidth, server CPU / memory usage, and link stability (such as packet loss rate and latency). In actual calculations, the system status will dynamically generate corresponding values ​​based on the current network and server resource conditions. For example, when the network bandwidth remains at 30%, it indicates that the system is in a relatively congested state. At this time, the system status parameter S is set to 0.3; when the bandwidth remains at 70%, the system state is relatively relaxed, and the system status parameter S is set to 0.8. The evaluation results of the system status parameters will directly affect the data priority. When the system is congested, the algorithm can prioritize the transmission of "small data volume, high value" data; when the system is idle, the priority policy can be appropriately relaxed.

[0033] S2. The sending end uses the multi-dimensional characteristic parameters of the digital twin data to perform multi-dimensional dynamic priority allocation calculations to obtain the data priority of the digital twin data.

[0034] In specific implementation, the sending end substitutes the data importance parameter, real-time requirement parameter, data change rate parameter, and system status parameter into the preset multi-dimensional dynamic priority allocation formula to calculate and obtain the data priority of the digital twin data. The multi-dimensional dynamic priority allocation formula is:

[0035] Among them, P represents the data priority, I represents the data importance parameter, R represents the real-time requirement parameter, C represents the data change rate parameter, S represents the system status parameter, ω1, ω2, ω3, and ω4 are the first weight coefficient, second weight coefficient, third weight coefficient, and fourth weight coefficient respectively. The first weight coefficient, second weight coefficient, third weight coefficient, and fourth weight coefficient determine the importance of each dimension in the priority calculation. There are two main ways to set it: 1. Manual Configuration: In the early stages, when business scenarios are relatively simple and requirements are clear, business experts or engineers can manually configure the weighting coefficients based on their experience. For example, if the business is most concerned with data importance, a higher value (such as 0.4) can be set to emphasize the dominance of data importance in the priority calculation. This method is simple and direct, and can quickly meet basic business needs. However, it is difficult to adapt to complex and changing business scenarios, and may require frequent manual adjustments later.

[0036] 2. Machine Learning Optimization: With a sufficient accumulation of historical data, machine learning algorithms can be used to automatically optimize weight coefficients. By using actual values ​​in historical data and feedback from businesses on whether data priorities are reasonable (for example, when a piece of data is manually marked as prioritized but is not), the machine learning model can iteratively calculate and automatically find the optimal combination of weight coefficients, ensuring that the priority calculation results are more aligned with real business needs. This approach can dynamically adapt to complex scenarios. As data volume increases and the algorithm is trained, the accuracy and intelligence of priority calculations will continue to improve.

[0037] S3. The sending end dynamically calculates the bandwidth allocation for the digital twin data based on the data priority of the digital twin data to obtain the corresponding allocated bandwidth.

[0038] In specific implementation, the sending end substitutes the data priority of the digital twin data into the preset intelligent bandwidth dynamic allocation formula to calculate and obtain the corresponding allocated bandwidth. The intelligent bandwidth dynamic allocation formula is:

[0039] Among them, B p Characterizes the allocated bandwidth corresponding to the digital twin data p, P p Represents the data priority corresponding to the digital twin data p, n is the total number of digital twin data to be transmitted in the same batch, and p∈[1,n], i represents the number of the digital twin data to be transmitted in the same batch, P i Characterizes the data priority corresponding to digital twin data i, B total represents the total transmission bandwidth, α is the set adjustment coefficient, T max is the maximum allowed waiting time threshold, T p The waiting time for the digital twin data p to be transmitted.

[0040] For example, taking the digital twin application of smart factories as an example: the data importance parameter I is associated with the degree of temperature exceeding the limit and historical faults, and the value is 0.9; the real-time demand parameter R is based on the fault response time requirement, and the value is 0.8; the data change rate parameter C is based on the temperature change rate, and the value is 0.7; the system status parameter S is based on the current busyness of the production line, and the value is 0.6; calculated by the priority formula, the corresponding digital twin data priority (P) is 0.82, which can be judged as an emergency level and transmitted first; emergency data is preferentially allocated 60% of the network bandwidth and can be transmitted using a lossless compression algorithm.

[0041] This intelligent dynamic bandwidth allocation strategy significantly improves the transmission efficiency of digital twin data. In practical applications, it can reduce the transmission delay of urgent data by over 80%, ensuring unimpeded access to critical data channels. For example, in factory equipment fault alarm scenarios, high-priority critical fault alarm data can quickly obtain a large amount of bandwidth resources, enabling transmission within seconds, buying valuable time for fault resolution and effectively reducing production losses caused by equipment failures. Low-priority routine status reporting data, on the other hand, is transmitted when system bandwidth is idle, avoiding competition with high-priority data and achieving rational and efficient utilization of bandwidth resources.

[0042] S4. The sender timestamps and encapsulates the digital twin data to obtain the corresponding data packet, and performs hash calculation on the data packet to obtain the corresponding message digest.

[0043] During specific implementation, the sender can timestamp and encapsulate the digital twin data to obtain the corresponding data packet (including digital twin data, timestamp, device ID and other metadata), and then use the SHA-256 algorithm to hash the data packet to obtain the corresponding message digest.

[0044] S5. The sending end transmits the data packet and the message digest corresponding to the data packet to the receiving end based on the allocated bandwidth corresponding to the digital twin data.

[0045] S6. The receiving end receives the data packet transmitted by the sending end and the message digest corresponding to the data packet.

[0046] S7. The receiving end performs a data integrity check on the data packet based on the message digest corresponding to the data packet.

[0047] During implementation, the receiving end also uses the SHA-256 algorithm to hash the data packet to obtain the corresponding hash value to be verified. The hash value to be verified is then compared with the message digest corresponding to the data packet. When the hash value to be verified and the message digest corresponding to the data packet are consistent, the data integrity check is determined to have passed. Otherwise, the data integrity check is determined to have failed. The data may have encountered the following two anomalies during transmission: 1. Data tampering: For example, due to a network attack, the content of the data packet was illegally modified; 2. Packet loss: Part of the data packet was lost during transmission, resulting in a change in the hash value. Once the receiving end detects a data integrity anomaly, it will immediately send a data integrity check failure message (NACK message) to the sending end, requesting the sending end to retransmit the data packet.

[0048] Retransmission strategy: During the data transmission process, if a retransmission operation is performed immediately upon detecting a data anomaly, when the network is in a congested state, a large number of retransmission requests will further occupy the network bandwidth, or even burst the bandwidth, which will lead to more data loss. The exponential backoff algorithm achieves "off-peak retransmission" by "dynamically extending the retransmission interval time", thereby effectively reducing network pressure and ensuring the stability of data transmission. When the sender obtains the data integrity check failure information feedback from the receiver, it first determines the number of retransmissions of the digital twin data; then substitutes the number of retransmissions of the digital twin data into the preset retransmission interval time formula for calculation to obtain the retransmission interval time of the digital twin data. The retransmission interval time formula is:

[0049] Among them, T retrans It represents the retransmission interval time, T0 is the set initial retransmission interval time, and n is the number of retransmissions (n=1 for the first retransmission, n=2 for the second retransmission, and so on). After the retransmission interval time of the digital twin data is reached, the data packet and the message digest corresponding to the data packet are retransmitted to the receiving end based on the allocated bandwidth corresponding to the digital twin data, so that the receiving end re-checks the data integrity.

[0050] S8. When the data integrity check passes, the receiving end parses the data packet to obtain the digital twin data and timestamp.

[0051] In specific implementation, when the data integrity check passes, the receiving end directly parses the data packet to obtain the digital twin data and timestamp.

[0052] S9. The receiving end uses the timestamp to perform time sequence verification. When the time sequence verification passes, the digital twin data is saved.

[0053] In specific implementations, the receiving end first determines the packet's reception time. If the timestamp corresponds to a time before the reception time, the time sequence check fails, indicating a timing error. This means that later data arrives at the receiving end first, disrupting normal data timing logic and typically caused by out-of-order network transmission. Once the receiving end detects this anomaly, it immediately sends a time sequence check failure message (NACK message) to the sending end, requesting the sending end to retransmit the anomalous packet to ensure data timing accuracy. If the timestamp corresponds to a time before the reception time, the time difference between the reception time and the timestamp is calculated.

[0054] When the time difference is greater than the set difference threshold, the time sequence check is determined to have failed, that is, the time interval has exceeded the limit. For example, in a certain business scenario, the data packet is required to be transmitted every 10ms, but the actual detected interval exceeds 100ms. This indicates that there may be problems such as data leakage and severe delay. Once the receiving end detects this abnormality, it will immediately send a time sequence check failure message (NACK message) to the sending end, requiring the sending end to retransmit the abnormal data packet to ensure the correctness of the data timing. When the sending end obtains the time sequence check failure information fed back by the receiving end, it first determines the number of retransmissions of the digital twin data; then substitutes the number of retransmissions of the digital twin data into the preset retransmission interval time formula for calculation to obtain the retransmission interval time of the digital twin data. The retransmission interval time formula is:

[0055] Among them, T retrans It represents the retransmission interval time, T0 is the set initial retransmission interval time, and n is the number of retransmissions (n=1 for the first retransmission, n=2 for the second retransmission, and so on). After the retransmission interval time of the digital twin data is reached, the data packet and the message digest corresponding to the data packet are retransmitted to the receiving end based on the allocated bandwidth corresponding to the digital twin data, so that the receiving end can re-check the time sequence.

[0056] When the time difference does not exceed the set difference threshold, the time sequence verification is determined to be passed. At this time, the receiving end can save and apply the digital twin data.

[0057] The present invention realizes real-time intelligent adjustment of data transmission priority and improves transmission efficiency by constructing a dynamic priority algorithm based on multi-dimensional data features; ensures the accuracy of digital twin data transmission through the dual protection mechanism of data integrity verification and time sequence verification; combines dynamic bandwidth allocation and intelligent retransmission strategy to achieve a dynamic balance between transmission efficiency and accuracy, and has strong industry universality; through dynamic bandwidth allocation and intelligent compression strategy, network bandwidth utilization is significantly improved, greatly reducing enterprise data transmission costs.

[0058] Example 2: This embodiment provides a digital twin data transmission optimization system, including a transmitting end and a receiving end, wherein: The sending end is used to obtain the digital twin data to be transmitted and the multi-dimensional characteristic parameters of the digital twin data; use the multi-dimensional characteristic parameters of the digital twin data to perform multi-dimensional dynamic priority allocation calculation to obtain the data priority of the digital twin data; perform bandwidth dynamic allocation calculation on the digital twin data according to the data priority of the digital twin data to obtain the corresponding allocated bandwidth; timestamp and encapsulate the digital twin data to obtain the corresponding data packet, and perform hash calculation on the data packet to obtain the corresponding message digest; based on the allocated bandwidth corresponding to the digital twin data, the data packet and the message digest corresponding to the data packet are transmitted to the receiving end; The receiving end is used to receive the data packet transmitted by the sending end and the message digest corresponding to the data packet; perform data integrity verification on the data packet based on the message digest corresponding to the data packet; when the data integrity verification passes, parse the data packet to obtain digital twin data and timestamp; use the timestamp to perform time sequence verification, and when the time sequence verification passes, save the digital twin data.

[0059] The transmitting end and the receiving end may include, at the hardware level: Data interface, used to establish data connection between the processor and the external data terminal; a memory for storing instructions; A processor is used to read the instructions stored in the memory and execute the corresponding steps of the digital twin data transmission optimization method in Example 1 according to the instructions.

[0060] Optionally, the transmitting end and the receiving end further include an internal bus, and the processor, memory, and data interface can be interconnected via the internal bus. The internal bus can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc.

[0061] The memory may include, but is not limited to, random access memory (RAM), read-only memory (ROM), flash memory, first-in-first-out memory (FIFO) and / or first-in-last-out memory (FILO), etc. The processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0062] Example 4: This embodiment provides a computer-readable storage medium having instructions stored thereon. When the instructions are executed on a computer, the computer is caused to execute the steps of the method for optimizing digital twin data transmission at the transmitting or receiving end in Example 1. The computer-readable storage medium refers to a carrier for storing data, and may include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash drive, and / or a memory stick. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0063] This embodiment further provides a computer program product, which, when executed on a computer, executes the steps of the method for optimizing digital twin data transmission at a transmitting end or a receiving end in Embodiment 1. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0064] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A digital twin data transmission optimization method, applied to the sending end, characterized in that: include: Obtaining digital twin data to be transmitted and multi-dimensional characteristic parameters of the digital twin data; The multi-dimensional characteristic parameters of digital twin data are used to perform multi-dimensional dynamic priority allocation calculation to obtain the data priority of digital twin data; Perform dynamic bandwidth allocation calculation on digital twin data according to its data priority to obtain the corresponding allocated bandwidth; Timestamp and encapsulate the digital twin data to obtain the corresponding data packet, and perform hash calculation on the data packet to obtain the corresponding message digest; Based on the allocated bandwidth corresponding to the digital twin data, the data packet and the message digest corresponding to the data packet are transmitted to the receiving end, so that the receiving end uses the message digest to check the data integrity of the data packet, and parses the data packet after the data integrity check passes, and obtains the digital twin data and timestamp, and uses the timestamp to perform time sequence verification, and saves the digital twin data after the time sequence verification passes.

2. A digital twin data transmission optimization method according to claim 1, characterized in that: The multidimensional characteristic parameters include data importance parameters, real-time demand parameters, data change rate parameters, and system status parameters. The multidimensional characteristic parameters of the digital twin data are used to perform multidimensional dynamic priority allocation calculation to obtain the data priority of the digital twin data, including: Substitute the data importance parameter, real-time requirement parameter, data change rate parameter, and system status parameter into the preset multi-dimensional dynamic priority allocation formula to calculate the data priority of the digital twin data. The multi-dimensional dynamic priority allocation formula is: Among them, P represents the data priority, I represents the data importance parameter, R represents the real-time demand parameter, C represents the data change rate parameter, S represents the system state parameter, ω1, ω2, ω3 and ω4 are the set first weight coefficient, second weight coefficient, third weight coefficient and fourth weight coefficient respectively.

3. A digital twin data transmission optimization method according to claim 1, characterized in that: The dynamic bandwidth allocation calculation of the digital twin data according to the data priority of the digital twin data to obtain the corresponding allocated bandwidth includes: Substitute the data priority of the digital twin data into the preset intelligent bandwidth dynamic allocation formula to calculate the corresponding allocated bandwidth. The intelligent bandwidth dynamic allocation formula is: Among them, B p Characterizes the allocated bandwidth corresponding to the digital twin data p, P p Represents the data priority corresponding to the digital twin data p, n is the total number of digital twin data to be transmitted in the same batch, and p∈[1,n], i represents the number of the digital twin data to be transmitted in the same batch, P i Characterizes the data priority corresponding to digital twin data i, B total represents the total transmission bandwidth, α is the set adjustment coefficient, T max is the maximum allowed waiting time threshold, T p The waiting time for the digital twin data p to be transmitted.

4. A digital twin data transmission optimization method according to claim 1, characterized in that: The hash calculation is performed on the data packet to obtain the corresponding message digest, including: The SHA-256 algorithm is used to perform hash calculation on the data packet to obtain the corresponding message digest.

5. The digital twin data transmission optimization method according to claim 1, characterized in that: The method further comprises: After obtaining the data integrity check failure information or time sequence check failure information fed back by the receiving end, determine the number of retransmissions of the digital twin data; Substitute the number of retransmissions of the digital twin data into the preset retransmission interval time formula to calculate the retransmission interval time of the digital twin data. The retransmission interval time formula is: Among them, T retrans Represents the retransmission interval, T0 is the set initial retransmission interval, and n is the number of retransmissions; After the retransmission interval of the digital twin data is reached, the data packet and the message digest corresponding to the data packet are retransmitted to the receiving end based on the allocated bandwidth corresponding to the digital twin data.

6. A digital twin data transmission optimization method, applied to the receiving end, characterized in that: include: Receive the data packet transmitted by the sender and the message digest corresponding to the data packet; Performing data integrity check on the data packet based on the message digest corresponding to the data packet; When the data integrity check passes, the data packet is parsed to obtain the digital twin data and timestamp; Use timestamps to perform time sequence verification. When the time sequence verification passes, the digital twin data is saved.

7. A digital twin data transmission optimization method according to claim 6, characterized in that: The performing data integrity check on the data packet based on the message digest corresponding to the data packet includes: Perform hash calculation on the data packet to obtain the corresponding hash value to be verified; The hash value to be verified is compared with the message digest corresponding to the data packet. When the hash value to be verified is consistent with the message digest corresponding to the data packet, the data integrity check is determined to have passed. Otherwise, the data integrity check is determined to have failed.

8. A digital twin data transmission optimization method according to claim 6, characterized in that: The time sequence verification using the timestamp includes: Determine the time at which the data packet was received; If the time corresponding to the timestamp is not before the receiving time, the time sequence check is determined to have failed; When the time corresponding to the timestamp is before the receiving time, the time difference between the receiving time and the time corresponding to the timestamp is calculated. When the time difference is greater than the set difference threshold, the time sequence check is determined to have failed. When the time difference does not exceed the set difference threshold, the time sequence check is determined to have passed.

9. A digital twin data transmission optimization system, characterized in that: It includes a sending end and a receiving end, where: The sending end is used to obtain the digital twin data to be transmitted and the multi-dimensional characteristic parameters of the digital twin data; use the multi-dimensional characteristic parameters of the digital twin data to perform multi-dimensional dynamic priority allocation calculation to obtain the data priority of the digital twin data; perform bandwidth dynamic allocation calculation on the digital twin data according to the data priority of the digital twin data to obtain the corresponding allocated bandwidth; timestamp and encapsulate the digital twin data to obtain the corresponding data packet, and perform hash calculation on the data packet to obtain the corresponding message digest; based on the allocated bandwidth corresponding to the digital twin data, the data packet and the message digest corresponding to the data packet are transmitted to the receiving end; The receiving end is used to receive the data packet transmitted by the sending end and the message digest corresponding to the data packet; perform data integrity verification on the data packet based on the message digest corresponding to the data packet; when the data integrity verification passes, parse the data packet to obtain digital twin data and timestamp; use the timestamp to perform time sequence verification, and when the time sequence verification passes, save the digital twin data.

10. A computer program product, characterized in that When the computer program product runs on a computer, the digital twin data transmission optimization method described in any one of claims 1 to 5 is executed, or the digital twin data transmission optimization method described in any one of claims 6 to 8 is executed.

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