Parameter determination method and device, electronic equipment, storage medium and program product

Abstract

The invention provides a parameter determination method and device, electronic equipment, a storage medium and a program product, and relates to the technical field of quantum communication. The method comprises the following steps: acquiring historical code rate information and a first preset time length, and determining a historical code rate according to the historical code rate information and the first preset time length; obtaining a current code rate, code rate fluctuation information and a first time interval, wherein the first time interval is a preset parameter evaluation time interval; according to the historical code rate, the current code rate, the code rate fluctuation information and the first time interval, a second time interval is determined, and the second time interval is the difference between the time of next parameter evaluation and the time of current parameter evaluation. The second time interval is determined according to the historical code rate, the current code rate, the code rate fluctuation information and the first time interval, so that the next parameter evaluation time is dynamically adjusted, the low code time is shortened, the long-time average code rate is improved, and the utilization rate of the QKD equipment and the link is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of quantum communication technology, and in particular to a parameter determination method, device, electronic device, computer-readable storage medium, and computer program product. Background Art

[0002] In the field of quantum communication technology, due to the high sensitivity of the Quantum Key Distribution (QKD) system to the environment, channel and device status, the QKD system needs to periodically evaluate the operating status to determine the corresponding operating parameters of the device. However, in the QKD network, due to the periodic parameter evaluation, short-term environmental and device link fluctuations are mistakenly regarded as long-term states by the parameter evaluation process, causing the overall network performance to be in a low coding rate situation for a period of time. Specifically, a single parameter evaluation may incorrectly reflect the long-term state of the line. Even if the operating status is quickly restored, the device continues to operate in an inefficient mode, resulting in a waste of resources.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0004] The present disclosure provides a parameter determination method, apparatus, device, and medium, which improve resource utilization to at least a certain extent.

[0005] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by practice of the present disclosure.

[0006] According to one aspect of the present disclosure, a parameter determination method is provided, the method comprising: obtaining historical coding rate information and a first preset duration; determining the historical coding rate based on the historical coding rate information and the first preset duration; obtaining a current coding rate, coding rate fluctuation information, and a first time interval, the first time interval being a preset parameter evaluation time interval; and determining a second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval, the second time interval being the difference between a time for a next parameter evaluation and a time for a current parameter evaluation.

[0007] In one embodiment of the present disclosure, before obtaining the current coding rate, coding rate fluctuation information and a first time interval, where the first time interval is a preset parameter evaluation time interval, the method further includes: obtaining a recovery duration of a quantum key distribution device, where the recovery duration is the time taken by the quantum key distribution device from the start of the coding process to the recovery of the device coding rate to a value multiple of the preset parameter; and when the recovery duration is less than a second preset duration, calculating a current average coding rate, and using the current average coding rate as the current coding rate.

[0008] In one embodiment of the present disclosure, the method further includes: when the recovery duration is greater than or equal to the second preset duration, acquiring an expected coding rate, and using the expected coding rate as the current coding rate.

[0009] In one embodiment of the present disclosure, before obtaining the current coding rate, coding rate fluctuation information and a first time interval, where the first time interval is a preset parameter evaluation time interval, the method further includes: obtaining an expected coding rate when a service demand is greater than or equal to a service demand threshold, and using the expected coding rate as the current coding rate; or, obtaining an expected coding rate when a coding rate fluctuation value is greater than or equal to a first fluctuation threshold, and using the expected coding rate as the current coding rate; or, obtaining an expected coding rate when a number of times the coding rate fluctuation value is equal to a second fluctuation threshold within a third preset time period is greater than a number threshold, and using the expected coding rate as the current coding rate.

[0010] In one embodiment of the present disclosure, the method further includes: when the business demand is less than the business demand threshold and the coding rate fluctuation value of the quantum key distribution device after the fourth preset time length is less than the third fluctuation threshold, calculating the current average coding rate and using the current average coding rate as the current coding rate.

[0011] In one embodiment of the present disclosure, determining the historical coding rate based on the historical coding rate information and the first preset duration includes: calculating the sliding average coding rate of the first preset duration based on the historical coding rate information, and determining the sliding average coding rate of the first preset duration as the historical coding rate.

[0012] In one embodiment of the present disclosure, determining the historical coding rate according to the historical coding rate information and the first preset duration includes:

[0013] Based on the historical coding rate information, the maximum value of the sliding average coding rate of the first preset duration is calculated, and the maximum value of the sliding average coding rate of the first preset duration is determined as the historical coding rate; or, based on the historical coding rate information, the average value of the sliding average coding rate of the first preset duration is calculated, and the average value of the sliding average coding rate of the first preset duration is determined as the historical coding rate; or, based on the historical coding rate information, the minimum value of the sliding average coding rate of the first preset duration is calculated, and the minimum value of the sliding average coding rate of the first preset duration is determined as the historical coding rate.

[0014] In one embodiment of the present disclosure, the coding rate fluctuation information is a fluctuation value of the coding rate caused by acceptable normal link fluctuations; wherein, determining the second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval includes: determining a first weight value based on the coding rate fluctuation information; calculating the product of the first weight value and the historical coding rate to obtain a historical reference coding rate; determining the first time interval as the second time interval when the current coding rate is greater than or equal to the historical reference coding rate; and shortening the first time interval when the current coding rate is less than the historical reference coding rate, and determining the shortened first time interval as the second time interval.

[0015] In one embodiment of the present disclosure, when the current coding rate is less than the historical reference coding rate, shortening the first time interval and determining the shortened first time interval as the second time interval includes: determining a second weight value based on the historical coding rate, the current coding rate and the coding rate fluctuation information, the second weight value being less than 1; and determining the product of the first time interval and the second weight value as the second time interval.

[0016] In one embodiment of the present disclosure, when the current coding rate is less than the historical reference coding rate, shortening the first time interval and determining the shortened first time interval as the second time interval includes: when the current coding rate is less than a coding rate threshold, shortening the first time interval to 0 seconds and determining the shortened first time interval as the second time interval.

[0017] According to another aspect of the present disclosure, a parameter determination device is provided, including: an acquisition module for acquiring historical coding rate information and a first preset duration; a determination module for determining the historical coding rate based on the historical coding rate information and the first preset duration; the acquisition module is further configured to acquire a current coding rate, coding rate fluctuation information, and a first time interval, wherein the first time interval is a preset parameter evaluation time interval; the determination module is further configured to determine a second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval, wherein the second time interval is the difference between a time for a next parameter evaluation and a time for a current parameter evaluation.

[0018] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform any of the above-mentioned parameter determination methods by executing the executable instructions.

[0019] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, any of the above-mentioned parameter determination methods is implemented.

[0020] According to another aspect of the present disclosure, a computer program product is provided, which includes a computer program or computer instructions, and the computer program or the computer instructions are loaded and executed by a processor to enable a computer to implement any of the above-mentioned parameter determination methods.

[0021] In an embodiment of the present disclosure, historical coding rate information and a first preset duration are obtained, and the historical coding rate is determined based on the historical coding rate information and the first preset duration; the current coding rate, coding rate fluctuation information, and a first time interval are obtained, where the first time interval is a preset parameter evaluation time interval; and a second time interval is determined based on the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval, where the second time interval is the difference between the time of the next parameter evaluation and the time of the current parameter evaluation. The present disclosure determines the second time interval by using the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval, thereby dynamically adjusting the time of the next parameter evaluation, shortening the low coding time, and improving the long-term average coding rate, thereby improving the utilization rate of the QKD device and link.

[0022] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0024] Figure 1 A flow chart of a parameter determination method according to an embodiment of the present disclosure is shown;

[0025] Figure 2 A schematic diagram of coding rate fluctuation is shown;

[0026] Figure 3 A flow chart of a parameter determination method in another embodiment of the present disclosure is shown;

[0027] Figure 4 A schematic diagram illustrating an application scenario of a parameter determination method according to an embodiment of the present disclosure is shown;

[0028] Figure 5 A schematic diagram of a determination method and device according to an embodiment of the present disclosure is shown;

[0029] Figure 6 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown;

[0030] Figure 7 A schematic diagram of a computer-readable storage medium provided in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0031] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0032] In addition, the accompanying drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0033] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0034] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0035] It should be noted that the modifications of "one" and "multiple" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more".

[0036] It should be pointed out that, in the absence of conflict, the embodiments of the present disclosure and the technical features therein may be combined with each other.

[0037] For ease of understanding, the terms used in this disclosure are explained below:

[0038] Quantum key distribution (QKD): A key distribution technology that uses quantum mechanics to ensure security, allowing both communicating parties to generate random and secure keys for encryption.

[0039] Quality of Service (QoS) refers to the control of data flow transmission through various technical means in computer networks to ensure the quality of network services.

[0040] With the continuous iteration and upgrade of QKD equipment and the gradual improvement of network infrastructure, an increasing number of security-sensitive businesses are relying on quantum key distribution technology to ensure the security of data transmission. Paired QKD systems bear greater pressure to generate keys. In high-security applications such as one-time pads, the key generation rate must be kept at the same scale as the data transmission rate to meet business needs. In this case, the QKD system must maintain a high distribution rate during the key generation process. Prolonged inefficiency may cause interruptions in secure encryption services, affecting the stability and security of the entire system.

[0041] Because QKD systems are inherently sensitive to external factors such as channel conditions and device status, channel quality may temporarily degrade when external disturbances occur. Therefore, channel adaptation algorithms have emerged to assess whether the current link and device status are suitable for high-bitrate operation. These algorithms then adjust device operating parameters based on feedback to adapt to the current link state.

[0042] However, since a QKD receiver can only be connected to one QKD transmitter at a time, disturbances in the channel over a short period of time may cause the adaptive algorithm to determine that the line state is not suitable for a high code rate. As a result, even if the disturbance has been eliminated, the device will maintain low code rate operation until the next parameter evaluation. This situation not only wastes network resources, but may also exacerbate fluctuations in network performance. Generally, large fluctuations in the link occur less frequently and for a shorter duration, while smaller fluctuations may last longer and occur more frequently. In related technologies, the parameter evaluation strategy uses periodic evaluation, which can easily amplify the impact of short-term disturbances on the link, thereby affecting the service carrying capacity. Therefore, it is necessary to optimize the parameter evaluation strategy to maximize the utilization of links and equipment and improve the service carrying capacity of the network.

[0043] Based on this, the present disclosure provides a parameter determination method, which is applied in the scenario of quantum key distribution, for example, in a single business scenario with a long-term high key demand, to ensure a stable and continuous supply of keys, and to improve the service capabilities and service limits of a single device. For another example, in scenarios with peak key usage and instantaneous high key demand, it is ensured that the key pool has a high key volume for a long time, and to avoid a single business consuming a large amount of resources in the key pool due to short-term fluctuations. The present disclosure obtains historical coding rate information and a first preset time length, and determines the historical coding rate based on the historical coding rate information and the first preset time length; obtains the current coding rate, coding rate fluctuation information and a first time interval, the first time interval being a preset parameter evaluation time interval; determines a second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information and the first time interval, the second time interval being the time interval for the next parameter evaluation. The present invention determines the second time interval through the historical coding rate, the current coding rate, the coding rate fluctuation information and the first time interval, thereby dynamically adjusting the next parameter evaluation time, shortening the low coding time, and improving the long-term average coding rate, thereby improving the utilization rate of QKD equipment and links.

[0044] This exemplary implementation is described in detail below with reference to the accompanying drawings and examples.

[0045] First, an embodiment of the present disclosure provides a parameter determination method, which can be executed by any electronic device with computing and processing capabilities.

[0046] Figure 1 A flow chart of a parameter determination method according to an embodiment of the present disclosure is shown as follows: Figure 1 As shown, the parameter determination method provided in the embodiment of the present disclosure includes the following S101 to S104.

[0047] S101: Obtain historical bitrate information and a first preset duration.

[0048] In the disclosed embodiment, the value of the first preset duration is not specifically limited and can be set based on actual application scenarios and specific application experience. Historical bitrate information refers to bitrate data recorded at various sampling time points over a period of time.

[0049] S102: Determine a historical coding rate according to historical coding rate information and a first preset duration.

[0050] In the disclosed embodiment, the historical coding rate is used as reference information for determining the second time interval described below, and is used to determine the next parameter evaluation time based on the historical coding rate, so as to shorten the low coding time and improve the long-term average coding rate of the entire link.

[0051] S103: Obtain the current coding rate, coding rate fluctuation information, and a first time interval, where the first time interval is a preset parameter evaluation time interval.

[0052] In the embodiment of the present disclosure, the coding rate fluctuation information is the value of the coding rate fluctuation caused by the acceptable normal link fluctuation.

[0053] It should be noted that the first time interval is a parameter preset by the device and is also the time interval used for evaluating the current parameters of the device.

[0054] S104: Determine a second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval. The second time interval is the difference between the time of the next parameter evaluation and the time of the current parameter evaluation.

[0055] It should be noted that determining the second time interval also determines the time for the next parameter evaluation. For example, the sum of the current parameter evaluation time and the second time interval is the time for the next parameter evaluation. The device performs parameter evaluation at the time of the next parameter evaluation.

[0056] In the disclosed embodiment, there is no specific limitation on how to determine the second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information and the first time interval. Any method can shorten the next parameter evaluation time when the performance of the overall network is at a low coding rate for a period of time due to short-term environmental and device link fluctuations that are mistakenly regarded as a long-term state by the parameter evaluation process.

[0057] For example, the proportional coefficient of the first time interval is determined according to the historical coding rate, the current coding rate and the coding rate fluctuation information. The product of the proportional coefficient and the first time interval is the second time interval, that is, the second time interval is linearly related to the first time interval.

[0058] For another example, based on actual needs and QKD equipment line fluctuations, the above linear relationship can be converted into mathematical relationships such as exponential relationships, so as to quickly enter the next parameter evaluation.

[0059] Exemplarily, the calculation formula of the second time interval is shown in the following formula 1.

[0060]

[0061] Wherein, T2 is the second time interval; T1 is the first time interval; kr current is the current bit rate; kr history is the historical bit rate; f is the bit rate fluctuation information; γ is the adjustment parameter; γ>0.

[0062] It should be noted that the value of γ can be set according to actual application scenarios and specific application experience. For example, the value of γ is an integer greater than 10.

[0063] For another example, when the current coding rate is less than the coding rate threshold, the next parameter evaluation is directly entered, that is, the second time interval is 0 seconds.

[0064] The embodiment of the present disclosure determines the second time interval through the historical coding rate, the current coding rate, the coding rate fluctuation information and the first time interval, thereby dynamically adjusting the next parameter evaluation time, shortening the low coding time, and improving the long-term average coding rate, thereby improving the utilization rate of the QKD equipment and link.

[0065] The present disclosure is further described below through several exemplary embodiments.

[0066] In an exemplary embodiment, before obtaining the current coding rate, coding rate fluctuation information and a first time interval, where the first time interval is a preset parameter evaluation time interval, the parameter determination method provided by the present disclosure may further include the following steps A1 and A2.

[0067] Step A1: Obtain the recovery time of the quantum key distribution device. The recovery time is the time it takes for the quantum key distribution device to recover to a device coding rate times a preset parameter from the start of the coding process.

[0068] In the disclosed embodiments, the specific settings of the preset parameters are not limited. For example, the preset parameters are any value among 0.5, 0.6, 0.7, 0.8, 0.9, and 1. The device coding rate can be the coding rate of the QKD device in long-term operation.

[0069] It should be noted that the coding process refers to the process of generating and processing quantum bits (quantum signals) from the sending end in the quantum key distribution (QKD) system.

[0070] Step A2: When the recovery time is less than the second preset time, the current average coding rate is calculated and used as the current coding rate.

[0071] In the disclosed embodiment, the value of the second preset duration is not specifically limited and can be set according to actual needs. If the recovery duration is less than the second preset duration, it means that the recovery duration is short, and the current average bit rate (i.e., the current actual running bit rate) can be used as the current bit rate.

[0072] In the embodiments of the present disclosure, there is no specific limitation on how to calculate the current average coding rate. For example, the coding rate of n seconds after the current QKD device stabilizes is obtained as a reference to calculate the current coding rate, where n is an integer greater than 0. For example, n is 5 seconds, once per second, and the sampling values ​​are 5Mbps (million bits per second), 6Mbps, 5.5Mbps, 5.8Mbps, and 5Mbps, respectively. The current average coding rate = (5+6+5.5+5.8+5) / 5 = 5.46Mbps. The current coding rate is 5.46Mbps.

[0073] Exemplarily, the preset parameter is 1, the second preset time is 20s (seconds), and the QKD device can recover to the long-term operating coding rate (device coding rate) under the link conditions within 10s after the link is established. The recovery time is 10s, which is less than 20s. The value after 10s can be used to calculate the current coding rate.

[0074] For example, if the QKD device has a long recovery time, the percentage of the long-term operating rate that it typically recovers to after n seconds can be calculated to estimate the long-term operating rate. For example, if the preset parameter is 0.8 and the second preset time is 20 seconds, and the device typically recovers to 80% of the long-term operating rate after 10 seconds, then the short-term rate after 10 seconds can be used to estimate the expected encoding rate during normal operation.

[0075] It should be noted that since the initial coding rate of the coding process is different from the stable coding rate, the speed at which the QKD device returns to normal operating levels (such as recovery time) and user settings (such as preset parameters) are used to determine whether to use the current actual coding rate of the device as the current coding rate. The current coding rate can be used as a reference.

[0076] In one embodiment, the parameter determination method may further include: when the recovery duration is greater than or equal to a second preset duration, obtaining an expected coding rate, and using the expected coding rate as the current coding rate.

[0077] In the disclosed embodiment, if the recovery duration is greater than or equal to the second preset duration, it indicates that the device will take a long time to restore a stable bitrate. There is no need to wait for the recovery duration to be determined, and the acquired expected bitrate is used as the current bitrate. For example, if the second preset duration is 20 seconds, and the bitrate is still unstable after 20 seconds, it indicates that the recovery duration is greater than or equal to the second preset duration. There is no need to wait for 5 hours (the time required to restore to a stable state) to determine the current bitrate. Instead, the expected bitrate is used as the current bitrate.

[0078] It should be noted that the condition for determining whether it is stable is that the current device coding rate is relatively close to the average coding rate of the device within the normal operating parameter evaluation interval (such as the first time interval), or the device coding rate no longer increases significantly.

[0079] It should be noted that the expected bitrate is calculated by the device itself using the protocol's secure bitrate formula based on the existing parameters after parameter evaluation. This process can be performed internally on the device and is calculable within the protocol itself. The present disclosure allows for direct access to the expected bitrate.

[0080] The disclosed embodiment determines the current coding rate based on the relationship between the recovery time and the second preset time, thereby quickly determining the current coding rate, and then quickly determining the second time interval, realizing the dynamic control parameter evaluation time interval, and quickly repairing the impact of short-term and relatively rare link status fluctuations on the coding rate, shortening the inefficient coding time to ensure efficient link resource utilization.

[0081] In another exemplary embodiment, before obtaining the current coding rate, coding rate fluctuation information and a first time interval, where the first time interval is a preset parameter evaluation time interval, the parameter determination method provided by the present disclosure may further include: when the business demand is greater than or equal to a business demand threshold, obtaining the expected coding rate, and using the expected coding rate as the current coding rate; or, when the coding rate fluctuation value is greater than or equal to a first fluctuation threshold, obtaining the expected coding rate, and using the expected coding rate as the current coding rate; or, when the number of times the coding rate fluctuation value is equal to the second fluctuation threshold within a third preset time length is greater than a number threshold, obtaining the expected coding rate, and using the expected coding rate as the current coding rate.

[0082] In the embodiment of the present disclosure, if the business demand is greater than or equal to the business demand threshold, it means that the amount of keys required is large and the device needs to quickly end its operation in the inefficient mode. The embodiment of the present disclosure uses the expected coding rate as the current coding rate, and can quickly perform the next parameter evaluation to achieve a stable device key generation rate, thereby providing stronger support for business peak periods.

[0083] In the disclosed embodiment, the bitrate fluctuation value represents the fluctuation of the current device bitrate, and the first fluctuation threshold is a preset value. When the bitrate fluctuation value is greater than or equal to the first fluctuation threshold, it indicates a significant bitrate fluctuation. When the fluctuation is significant, using the expected bitrate as the current bitrate allows for faster parameter evaluation, avoiding sudden performance degradation of the network and improving the stability and reliability of the entire system.

[0084] In the disclosed embodiment, if the number of times the bitrate fluctuation value equals the second fluctuation threshold within the third preset duration exceeds the number threshold, it indicates that fluctuations are frequent. When fluctuations occur frequently, using the expected bitrate as the current bitrate allows for faster parameter evaluation, improving the stability and reliability of the entire system.

[0085] The disclosed embodiments utilize a method of predicting bit rates to help communication systems better prevent performance issues, optimize resource allocation, and ensure stable and efficient system operation when faced with large fluctuations, frequent fluctuations, or high demand.

[0086] The disclosed embodiment can also compare the coding rate corresponding to the current parameter evaluation result with the historical coding rate to timely discover the jitter of the current link status.

[0087] In one embodiment, the parameter determination method provided by the present disclosure may also include: when the business demand is less than the business demand threshold and the coding rate fluctuation value of the quantum key distribution device after the fourth preset time length is less than the third fluctuation threshold, calculating the current average coding rate and using the current average coding rate as the current coding rate.

[0088] In the disclosed embodiment, if the service demand is less than the service demand threshold, then the service demand is low. If the coding rate fluctuation value of the quantum key distribution device after the fourth preset time period is less than the third fluctuation threshold, then the coding rate fluctuation is small. If the service demand is low and the coding rate fluctuation is small, the current average coding rate is used as the current coding rate.

[0089] For example, assuming that the device recovery time is short (seconds) and the fluctuation is small (the short-term coding rate will not be affected by sudden fluctuations), the real coding rate (current average coding rate) can be used.

[0090] In one embodiment, when the expected coding rate calculated by the device often does not match the actual coding rate due to external uncertain factors, the actual coding rate (current average coding rate) is used.

[0091] In one embodiment, if the external prediction is inconsistent and short-term fluctuations often occur, the average bit rate over a slightly longer period can be used as the actual bit rate. For example, if the bit rate of a device no longer increases significantly and stabilizes after 20 seconds, the average bit rate over 20 seconds to 80 seconds can be used as the actual bit rate (the current average bit rate) to smooth out short-term fluctuations.

[0092] The disclosed embodiment dynamically adjusts the next parameter evaluation time by determining the current coding rate, thereby shortening the low coding time and improving the long-term average coding rate, thereby improving the utilization rate of QKD equipment and links.

[0093] In another exemplary embodiment, the historical coding rate is determined according to the historical coding rate information and the first preset duration, including: calculating the sliding average coding rate of the first preset duration based on the historical coding rate information, and determining the sliding average coding rate of the first preset duration as the historical coding rate.

[0094] In the embodiment of the present disclosure, the historical coding rate information includes multiple coding rate data of devices collected in chronological order before the current time, and the range of the collection time is the distribution time of the historical coding rate information. Regarding the distribution time range of the historical coding rate information, the embodiment of the present disclosure does not make any specific restrictions, and the size of the distribution time of the historical coding rate information can be set as needed. It should be noted that the first preset time range slides within the above-mentioned time range. For example, the distribution time range of the historical coding rate information is 10 days, the first preset time range is 1 hour, and the average coding rate of any 1 hour in 10 days is taken as the historical coding rate.

[0095] In one embodiment, the parameter determination method provided by the present disclosure may include determining the historical coding rate based on historical coding rate information and a first preset duration, and may include: calculating the maximum value of the sliding average coding rate of the first preset duration based on the historical coding rate information, and determining the maximum value of the sliding average coding rate of the first preset duration as the historical coding rate; or, calculating the average value of the sliding average coding rate of the first preset duration based on the historical coding rate information, and determining the average value of the sliding average coding rate of the first preset duration as the historical coding rate; or, calculating the minimum value of the sliding average coding rate of the first preset duration based on the historical coding rate information, and determining the minimum value of the sliding average coding rate of the first preset duration as the historical coding rate.

[0096] It should be noted that, assuming the maximum value of the sliding average coding rate is used, the historical maximum hourly average coding rate is considered the expected value, and any value below this value has room for improvement. This is applicable to cases where the link is unstable and there are long periods of low coding rate operation, which have a significant negative impact on the average value of the sliding average coding rate. In this case, using the average value of the sliding average coding rate as the benchmark would greatly reduce the ability of this disclosure to constrain the coding rate.

[0097] It should be noted that if the sliding average bit rate is used, the system is considered to be relatively stable, that is, the standard deviation of the sliding average bit rate is small, and there is no long-term low bit rate operation. The average value of the sliding average bit rate can reflect the performance of the equipment under a more efficient operating state.

[0098] It should be noted that, assuming a minimum moving average bitrate, the system can tolerate large fluctuations, but a lower limit is desirable. Any fluctuation above this lower limit is considered acceptable. The goal is to ensure that the equipment can operate, and as long as no major anomalies occur, this is acceptable.

[0099] In another exemplary embodiment, the coding rate fluctuation information is the fluctuation value of the coding rate caused by acceptable normal link fluctuations; wherein, determining the second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information and the first time interval may include steps B1 to B4.

[0100] Step B1: Determine a first weight value according to the bit rate fluctuation information.

[0101] In the embodiment of the present disclosure, there is no specific limitation on how to determine the first weight value according to the coding rate fluctuation information. For example, the first weight value is the difference between 1 and the coding rate fluctuation information.

[0102] Step B2: Calculate the product of the first weight value and the historical coding rate to obtain the historical reference coding rate.

[0103] Step B3: When the current coding rate is greater than or equal to the historical reference coding rate, the first time interval is determined as the second time interval.

[0104] Step B4: When the current coding rate is lower than the historical reference coding rate, shorten the first time interval, and determine the shortened first time interval as the second time interval.

[0105] In the disclosed embodiment, if the current coding rate is lower than the historical reference coding rate, it indicates that due to periodic parameter evaluation, short-term environmental and device link fluctuations are mistakenly interpreted as long-term states by the parameter evaluation process, causing the overall network performance to be at a low coding rate for a period of time. It is necessary to shorten the fixed evaluation period. In the above case, shortening the fixed evaluation period can improve the long-term average coding rate, provide stronger support for business peaks, and increase the lower limit of the QKD link to meet more business needs.

[0106] In one embodiment, in the parameter determination method provided by the present disclosure, when the current coding rate is less than the historical reference coding rate, shortening the first time interval and determining the shortened first time interval as the second time interval may include: determining a second weight value based on the historical coding rate, the current coding rate and coding rate fluctuation information, the second weight value being less than 1; and determining the product of the first time interval and the second weight value as the second time interval.

[0107] The embodiment of the present disclosure determines a second weight value less than 1 through historical coding rate, current coding rate and coding rate fluctuation information, thereby shortening the low coding time and improving the long-term average coding rate, thereby improving the utilization rate of QKD equipment and links.

[0108] In another embodiment, the parameter determination method provided by the present disclosure may include shortening the first time interval when the current coding rate is less than the historical reference coding rate and determining the shortened first time interval as the second time interval, which may include: shortening the first time interval to 0 seconds when the current coding rate is less than the coding rate threshold, and determining the shortened first time interval as the second time interval.

[0109] In the embodiment of the present disclosure, when the current coding rate is less than the coding rate threshold, the next parameter evaluation is directly started, that is, the second time interval is 0 seconds.

[0110] The disclosed embodiment can quickly enter the next parameter evaluation when the current coding rate is less than the coding rate threshold, thereby shortening the low coding time and improving the long-term average coding rate, thereby improving the utilization rate of QKD equipment and links.

[0111] It should be noted that for backbone network nodes or nodes with high business demands, if a node occupies the central node for low-coding rate communication for a long time, it is a waste of coding equipment and channels. For network resource planning, it will reduce the QKD's business carrying capacity, especially for time-sensitive and key-intensive services, such as services that require high-frequency key replacement, one-time large data transmission services, and duplex video, audio and other services, which may lead to business interruption or limit service time.

[0112] This disclosure is based on QKD equipment, key managers, etc., and controls the parameter evaluation interval of the QKD protocol through software to control the impact of short-term fluctuations in link status on the overall key rate. Figure 2As shown, the fixed evaluation period is 30 minutes, meaning the parameter evaluation interval is 30 minutes. By determining the current link attenuation and the coding rate history, the expected time for the next parameter evaluation after the current parameter evaluation is determined. This dynamically controls the parameter evaluation interval, quickly correcting the impact of rare short-term link status fluctuations on the coding rate, and shortening inefficient coding time to ensure efficient link resource utilization.

[0113] After the key generation process begins, the parameter evaluation module evaluates the current link to determine a secure upper bound on the bitrate. Because this result is subject to potential eavesdropping and link perturbations, it must be periodically adjusted, with the next adjustment time calculated.

[0114] It should be noted that the parameter evaluation module can be a module on the QKD device or a module on other devices. The expected coding rate in the present disclosure can also be replaced by the coding rate upper limit determined by the parameter evaluation module.

[0115] The present disclosure is further illustrated below through two embodiments.

[0116] In one embodiment, if Figure 3 As shown, the parameter determination method provided by the present disclosure may include S301 to S306.

[0117] S301, parameter evaluation. It should be noted that the device performs normal coding after parameter evaluation.

[0118] S302: Determine a historical coding rate. Exemplarily, historical coding rate information and a first preset duration are obtained, and the historical coding rate is determined based on the historical coding rate information and the first preset duration.

[0119] S303, determine whether to use the current real coding rate as the current coding rate. If so, execute S304; if not, execute S305. Exemplarily, obtain the recovery time of the quantum key distribution device, which is the time taken by the quantum key distribution device from the start of the coding process to the recovery of the device coding rate to a preset parameter multiple; when the recovery time is less than the second preset time, calculate the current average coding rate, and use the current average coding rate (current real coding rate) as the current coding rate. Exemplarily, when the recovery time is greater than or equal to the second preset time, obtain the expected coding rate, and use the expected coding rate as the current coding rate.

[0120] S304: Use the current actual bit rate as the current bit rate.

[0121] S305: Taking the expected coding rate as the current coding rate.

[0122] S306: Calculate a second time interval. Exemplarily, the bitrate fluctuation information and the first time interval are obtained, and the second time interval is determined based on the historical bitrate, the current bitrate, the bitrate fluctuation information, and the first time interval. The time for the next parameter evaluation can be calculated based on the second time interval, so that the parameter evaluation is performed at the next parameter evaluation time.

[0123] For example, the second time interval is calculated using the following formula 2.

[0124]

[0125] Wherein, T2 is the second time interval; T1 is the first time interval; kr current is the current bit rate; kr history is the historical bit rate; f is the bit rate fluctuation information.

[0126] It should be noted that there is no specific limitation on how to calculate the historical bit rate. a , calculate t a A statistic of the hourly average coding rate (such as the average, maximum, or minimum value) is used as the historical coding rate. Coding rate fluctuation information indicates acceptable coding rate fluctuations caused by normal link fluctuations. The user sets the initial parameter evaluation interval as the parameter evaluation interval under normal circumstances (such as the first time interval). The parameter evaluation result is that the key rate does not exceed the current coding rate.

[0127] While ensuring the security of its key distribution service, the disclosed embodiments minimize the impact of link fluctuations on parameter evaluation results, thereby improving the key rate. It is important to note that the entire parameter evaluation process is identical to that in the protocol. Dynamically shortening the parameter evaluation interval based solely on the evaluation results and the historical bitrate does not create additional security vulnerabilities.

[0128] In another embodiment, in scenarios with high bitrate requirements, the impact of periodic low bitrates on services is reduced. The application requirement is to ensure long-term stable key output under limited bitrates and key pool size to ensure that services are not affected by fluctuations in the QKD device's bitrate.

[0129] like Figure 4As shown, the device includes a key manager (KM, such as KM-A and KM-B) and a quantum key distribution device. The KM can store 1.5G keys and provide them to applications for data service encryption. The generation rate of Alice (sender) and Bob (receiver) of the quantum key distribution device is 3.5Mb / s (megabits per second), but the overall fluctuation is large. The minimum value is about 1.2Mb / s. It should be noted that Alice and Bob can be different terminal devices. APP1 and APP2 are both applications. APP can be various types of applications, such as social media, games, tools, productivity, education, shopping, health, etc.

[0130] The reasons for fluctuations are as follows:

[0131] Device fluctuations: Even if the device parameters are completely fixed, the bitrate may fluctuate due to link instability or device fluctuations.

[0132] Fluctuation in parameter evaluation results: Device operating parameters change periodically due to protocol requirements, resulting in predictable fluctuations. The typical update interval is approximately 30 minutes. An acceptable jitter limit is 10%. In other words, a downward fluctuation of more than 10% in the minimum bitrate is considered abnormal and falls within the unacceptable jitter range. Note that, assuming the bitrate for the next cycle is 1.2 Mb / s, a calculated fluctuation greater than 10% requires recalculating the evaluation time.

[0133] The process of determining the second time interval is as follows:

[0134] a. The device parameter evaluation is completed and the code is generated normally. In other words, the device generates the key.

[0135] b. Obtain historical bitrate information and calculate the historical bitrate. The calculated historical bitrate is 3.5Mb / s, that is, kr history =3.5Mb / s.

[0136] c. The coding rate fluctuation information and the first time interval are 10% and 30 minutes respectively, that is, f=10%, T1=30 minutes.

[0137] d. Calculate the current bit rate. The method of calculation has been described in the above embodiment and will not be repeated here. Assume that the calculated current bit rate is 1.2 Mb / s, that is, kr current =1.2Mb / s.

[0138] e. According to the above formula 2, since kr current <(1-f)kr history , so the second time interval is:

[0139]

[0140] Estimated key pool consumption = 13.2 × 60 × (2.5 - 1.2) = 1029.6 Mb < 1.5 Gb. This means that the number of keys that can be stored in the KM before the next parameter evaluation meets the consumption requirement. By shortening the evaluation interval through this disclosure, the service can operate normally. It should be noted that 2.5 Mb / s is the rate at which the service consumes keys, and 1.2 Mb / s is the rate at which keys are added (the current bitrate).

[0141] Assuming that a fixed time (first time interval) is used for parameter evaluation, the estimated key pool consumption = 30 × 60 × (2.5-1.2) = 2340 Mb > 1.5 Gb (service interruption). In other words, the key consumption requirement cannot be met and the service is interrupted.

[0142] It should be noted that 13.2 minutes in the formula for calculating the estimated key pool consumption is the second time interval, 60 can be converted into seconds, 2.5 Mb / s is the service key consumption rate, and 1.2 Mb / s is the current coding rate, that is, the key increase rate.

[0143] This formula calculates how many pre-stored keys will be consumed before the next parameter evaluation, given the current key consumption and generation rate. The calculation shows that 1029.6 Mb of keys will be consumed, which is less than the 1.5 Gb of pre-stored keys in the key pool. Therefore, the consumption is less than the pre-stored amount, and service will not be interrupted due to key pool depletion.

[0144] The disclosed embodiment dynamically adjusts the parameter evaluation time based on the current encoding rate, historical encoding rates, encoding rate fluctuation information, and the first time interval, shortening low encoding time and improving the long-term average encoding rate. By dynamically adjusting the parameter evaluation time, the disclosed embodiment stabilizes the device key generation rate and provides stronger support for peak traffic periods.

[0145] It should be noted that, while considering the worst possible performance of QKD, this disclosure can also meet more business needs by improving the lower limit of the QKD link. By comparing the code rate corresponding to the current parameter evaluation results with the historical code rate, jitter in the current link status can be detected in a timely manner.

[0146] Based on the same inventive concept, the present disclosure also provides a parameter determination device, as described in the following embodiments. Since the principle of solving the problem in the device embodiment is similar to that in the above method embodiment, the implementation of the device embodiment can refer to the implementation of the above method embodiment, and the repeated parts will not be repeated.

[0147] Figure 5A schematic diagram of a parameter determination device in an embodiment of the present disclosure is shown. Figure 5 As shown, the parameter determination device includes an acquisition module 51 and a determination module 52. The acquisition module 51 can be used to acquire historical bit rate information and a first preset duration; the determination module 52 can be used to determine the historical bit rate based on the historical bit rate information and the first preset duration; the acquisition module 51 can also be used to acquire the current bit rate, bit rate fluctuation information, and a first time interval, where the first time interval is a preset parameter evaluation time interval; the determination module 52 can also be used to determine a second time interval based on the historical bit rate, the current bit rate, the bit rate fluctuation information, and the first time interval, where the second time interval is the difference between the time of the next parameter evaluation and the time of the current parameter evaluation.

[0148] In one embodiment, before obtaining the current coding rate, coding rate fluctuation information and a first time interval, where the first time interval is a preset parameter evaluation time interval, the acquisition module 51 can also be used to obtain the recovery time of the quantum key distribution device, where the recovery time is the time taken by the quantum key distribution device from the start of the coding process to the recovery of the device coding rate to a preset parameter times; when the recovery time is less than the second preset time, the current average coding rate is calculated, and the current average coding rate is used as the current coding rate.

[0149] In one embodiment, the acquisition module 51 may be further configured to acquire an expected coding rate when the recovery time is greater than or equal to a second preset time, and use the expected coding rate as the current coding rate.

[0150] In one embodiment, before obtaining the current bit rate, bit rate fluctuation information, and a first time interval, where the first time interval is a preset parameter evaluation time interval, the acquisition module 51 may also be configured to, when the business demand is greater than or equal to a business demand threshold, obtain an expected bit rate, and use the expected bit rate as the current bit rate; or, when the bit rate fluctuation value is greater than or equal to a first fluctuation threshold, obtain the expected bit rate, and use the expected bit rate as the current bit rate; or, when the number of times the bit rate fluctuation value is equal to a second fluctuation threshold within a third preset time period is greater than a number threshold, obtain the expected bit rate, and use the expected bit rate as the current bit rate.

[0151] In one embodiment, the acquisition module 51 can also be used to calculate the current average coding rate and use the current average coding rate as the current coding rate when the business demand is less than the business demand threshold and the coding rate fluctuation value of the quantum key distribution device after the fourth preset time period is less than the third fluctuation threshold.

[0152] In one embodiment, the determination module 52 can also be used to calculate the maximum value of the sliding average coding rate of the first preset duration based on the historical coding rate information, and determine the maximum value of the sliding average coding rate of the first preset duration as the historical coding rate; or, based on the historical coding rate information, calculate the average value of the sliding average coding rate of the first preset duration, and determine the average value of the sliding average coding rate of the first preset duration as the historical coding rate; or, based on the historical coding rate information, calculate the minimum value of the sliding average coding rate of the first preset duration, and determine the minimum value of the sliding average coding rate of the first preset duration as the historical coding rate.

[0153] In one embodiment, the coding rate fluctuation information is the fluctuation value of the coding rate caused by acceptable normal link fluctuations; the determination module 52 can also be used to determine a first weight value based on the coding rate fluctuation information; calculate the product of the first weight value and the historical coding rate to obtain the historical reference coding rate; when the current coding rate is greater than or equal to the historical reference coding rate, determine the first time interval as the second time interval; when the current coding rate is less than the historical reference coding rate, shorten the first time interval, and determine the shortened first time interval as the second time interval.

[0154] In one embodiment, the determination module 52 may also be configured to determine a second weight value based on the historical coding rate, the current coding rate, and coding rate fluctuation information, where the second weight value is less than 1; and determine the product of the first time interval and the second weight value as the second time interval.

[0155] In one embodiment, the determination module 52 may be further configured to shorten the first time interval to 0 seconds when the current coding rate is less than the coding rate threshold, and determine the shortened first time interval as the second time interval.

[0156] The parameter determination device disclosed in the embodiment of the present disclosure determines the second time interval through the historical coding rate, the current coding rate, the coding rate fluctuation information and the first time interval, thereby dynamically adjusting the next parameter evaluation time, shortening the low coding time, and improving the long-term average coding rate, thereby improving the utilization rate of the QKD equipment and link.

[0157] Those skilled in the art will appreciate that various aspects of the present disclosure may be implemented as systems, methods, or program products. Therefore, various aspects of the present disclosure may be implemented in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "circuits," "modules," or "systems."

[0158] Refer to the following Figure 6 hereinafter, an electronic device 600 according to this embodiment of the present disclosure is described. Figure 6The electronic device 600 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0159] like Figure 6 As shown, electronic device 600 is implemented as a general-purpose computing device. Components of electronic device 600 may include, but are not limited to, the aforementioned at least one processing unit 610, the aforementioned at least one storage unit 620, and a bus 630 connecting different system components (including storage unit 620 and processing unit 610).

[0160] The storage unit stores program code, which can be executed by the processing unit 610, so that the processing unit 610 performs the steps described in the "Exemplary Method" section of this specification according to various exemplary embodiments of the present disclosure. For example, the processing unit 610 can perform the following steps of the above-mentioned method embodiment: obtaining historical coding rate information and a first preset duration; determining the historical coding rate based on the historical coding rate information and the first preset duration; obtaining the current coding rate, coding rate fluctuation information, and a first time interval, the first time interval being a preset parameter evaluation time interval; determining a second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval, the second time interval being the difference between the time of the next parameter evaluation and the time of the current parameter evaluation.

[0161] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0162] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0163] Bus 630 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0164] The electronic device 600 can also communicate with one or more external devices 640 (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 600, and / or any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication can occur via an input / output (I / O) interface 650. Furthermore, the electronic device 600 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 660. As shown, the network adapter 660 communicates with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 600, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0165] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0166] In the disclosed exemplary embodiments, a computer-readable storage medium is also provided. The computer-readable storage medium may be a readable signal medium or a readable storage medium. Figure 7 A schematic diagram of a computer-readable storage medium according to an embodiment of the present disclosure is shown. Figure 7 As shown, the computer-readable storage medium 700 stores a program product capable of implementing the above-mentioned method of the present disclosure.

[0167] In some possible implementations, various aspects of the present disclosure may also be implemented in the form of a program product, which includes program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of various exemplary implementations of the present disclosure described in the above "Specific Implementation Methods" section of this specification.

[0168] More specific examples of computer-readable storage media in the present disclosure may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), optical fibers, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0169] In the present disclosure, a computer-readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0170] Alternatively, the program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0171] In a specific implementation, the program code for performing the operations of the present disclosure may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a standalone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0172] The present disclosure provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the parameter determination method provided in any of the optional embodiments of the present disclosure.

[0173] It should be noted that although several modules or units of the device for action execution are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0174] Furthermore, although the steps of the method of the present disclosure are described in a particular order in the accompanying drawings, this does not require or imply that the steps must be performed in this particular order, or that all steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0175] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0176] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope of the present disclosure being indicated by the appended claims.

Claims

1. A parameter determination method, characterized in that: include: Obtain historical bitrate information and the first preset duration; Determining a historical coding rate based on the historical coding rate information and the first preset time duration; Acquire a current bitrate, bitrate fluctuation information, and a first time interval, where the first time interval is a preset parameter evaluation time interval; A second time interval is determined according to the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval, where the second time interval is the difference between the time of the next parameter evaluation and the time of the current parameter evaluation.

2. The method according to claim 1, characterized in that Before obtaining the current coding rate, coding rate fluctuation information, and the first time interval, where the first time interval is a preset parameter evaluation time interval, the method further includes: Obtaining a recovery time of a quantum key distribution device, where the recovery time is the time taken by the quantum key distribution device from the start of a coding process to recovering to a device coding rate that is multiple of the preset parameter; When the recovery time is less than the second preset time, a current average coding rate is calculated and used as the current coding rate.

3. The method according to claim 2, characterized in that The method further comprises: When the recovery time is greater than or equal to the second preset time, an expected coding rate is obtained, and the expected coding rate is used as the current coding rate.

4. The method according to claim 1, wherein Before obtaining the current coding rate, coding rate fluctuation information, and the first time interval, where the first time interval is a preset parameter evaluation time interval, the method further includes: When the service demand is greater than or equal to the service demand threshold, obtaining an expected coding rate and using the expected coding rate as the current coding rate; or When the coding rate fluctuation value is greater than or equal to the first fluctuation threshold, obtaining an expected coding rate, and using the expected coding rate as the current coding rate; or If the number of times that the coding rate fluctuation value is equal to the second fluctuation threshold within the third preset time period is greater than the number threshold, an expected coding rate is obtained, and the expected coding rate is used as the current coding rate.

5. The method according to claim 4, characterized in that The method further comprises: When the business demand is less than the business demand threshold and the coding rate fluctuation value of the quantum key distribution device after the fourth preset time period is less than the third fluctuation threshold, the current average coding rate is calculated and the current average coding rate is used as the current coding rate.

6. The method according to claim 1, characterized in that The determining the historical coding rate according to the historical coding rate information and the first preset duration includes: Based on the historical coding rate information, the sliding average coding rate of the first preset duration is calculated, and the sliding average coding rate of the first preset duration is determined as the historical coding rate.

7. The method according to claim 1 or 6, characterized in that The determining the historical coding rate according to the historical coding rate information and the first preset duration includes: Calculating a maximum value of the sliding average coding rate of the first preset duration based on historical coding rate information, and determining the maximum value of the sliding average coding rate of the first preset duration as the historical coding rate; Alternatively, based on historical coding rate information, an average value of the sliding average coding rates of the first preset duration is calculated, and the average value of the sliding average coding rates of the first preset duration is determined as the historical coding rate; Alternatively, based on historical coding rate information, a minimum value of the first preset duration sliding average coding rate is calculated, and the minimum value of the first preset duration sliding average coding rate is determined as the historical coding rate.

8. The method according to claim 1, characterized in that The coding rate fluctuation information is a fluctuation value of the coding rate caused by acceptable normal link fluctuation; The determining the second time interval according to the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval includes: determining a first weight value according to the coding rate fluctuation information; Calculating a product of the first weight value and the historical coding rate to obtain a historical reference coding rate; When the current coding rate is greater than or equal to the historical reference coding rate, determining the first time interval as the second time interval; When the current coding rate is less than the historical reference coding rate, the first time interval is shortened, and the shortened first time interval is determined as the second time interval.

9. The method according to claim 8, characterized in that The step of shortening the first time interval when the current coding rate is less than the historical reference coding rate, and determining the shortened first time interval as the second time interval, includes: determining a second weight value according to the historical coding rate, the current coding rate, and the coding rate fluctuation information, wherein the second weight value is less than 1; The product of the first time interval and the second weight value is determined as the second time interval.

10. The method according to claim 8, characterized in that The step of shortening the first time interval when the current coding rate is less than the historical reference coding rate, and determining the shortened first time interval as the second time interval, includes: When the current coding rate is less than the coding rate threshold, the first time interval is shortened to 0 seconds, and the shortened first time interval is determined as the second time interval.

11. A parameter determination device, characterized in that: include: An acquisition module, configured to acquire historical bitrate information and a first preset duration; a determination module, configured to determine a historical coding rate based on the historical coding rate information and the first preset duration; The acquisition module is further configured to acquire a current bitrate, bitrate fluctuation information, and a first time interval, where the first time interval is a preset parameter evaluation time interval; The determination module is further configured to determine a second time interval based on the historical coding rate, the current coding rate, the coding rate fluctuation information, and the first time interval, where the second time interval is the difference between the time of the next parameter evaluation and the time of the current parameter evaluation.

12. An electronic device, characterized in that: include: processor; as well as a memory for storing executable instructions of the processor; The processor is configured to execute the parameter determination method according to any one of claims 1 to 10 by executing the executable instructions.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the parameter determination method according to any one of claims 1 to 10 is implemented.

14. A computer program product comprising computer instructions, characterized in that The computer instructions are stored in a computer-readable storage medium, and when the computer instructions are executed by a processor, they are operating instructions for implementing the parameter determination method according to any one of claims 1 to 10.

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