Network slice access control method, system and equipment based on time sampling interval

Abstract

The invention discloses a network slice access control method, system and device based on a time sampling interval, and relates to the technical field of 5G system access control. The method comprises the following steps: firstly, determining a time sampling interval, and measuring and calculating a sampling proportion of any service in the time sampling interval by combining arrival and service time of a new service; according to the load threshold, calculating the residual load of the slices, calculating the throughput of any service, and calculating the throughput margin of the service and the throughput margin of all the slices in combination with the sampling proportion; calculating a time delay space and a time delay margin of the service, and calculating time delay margins of all slices; and judging whether the new service is time delay sensitive according to the application rate of the new service, and selecting a target slice to access based on the throughput margin and the time delay margin. According to the invention, by introducing a time dimension sampling mechanism and a resource margin refined measurement and calculation method, the technical problems of insufficient slice load dynamic sensing capability, coarse service feature mapping granularity and lack of spatio-temporal joint optimization in access decision in the prior art are effectively solved.

Description

Technical Field

[0001] This invention relates to the field of 5G system access control technology, specifically to a network slicing access control method, system, and device based on time sampling intervals. Background Technology

[0002] With the large-scale commercial deployment of 5G mobile communication technology, network slicing, as one of the core enabling technologies of 5G, can support differentiated service scenarios such as enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (uRLLC), and massive machine-type communication (mMTC) on a unified infrastructure through logical isolation and on-demand orchestration of physical network resources. Access control, as a key link in 5G radio resource management, directly determines the level of Quality of Service (QoS) and system resource utilization. Under the 5G network slicing architecture, how to select the optimal target slice for newly arriving services and implement precise access has become a core technical issue affecting network performance and user experience.

[0003] An existing patent (application number: 202211365786.8) discloses a 5G network slice access control method based on service type. It first determines the service type and then selects different principles to implement network slice access control based on whether the service is latency-sensitive. This method is simple, efficient, and easy to implement, but it doesn't give much consideration to the quality of the sliced ​​network. As more and more accesses occur, the slice load increases significantly, the possibility of service collisions rises sharply, and the probability of access failure also increases dramatically. Furthermore, this algorithm does not differentiate between services based on their size, leading to fairness distortion. Therefore, this invention proposes a network slice access control method, system, and device based on time sampling intervals. Summary of the Invention

[0004] The purpose of this invention is to provide a network slice access control method, system, and device based on time sampling intervals. Under the premise of certain 5G network slice resources, it can more intuitively realize access control of different services through differentiated strategies. Each network slice contains an appropriate amount of services, and the system predicts the arrival of new services to seek target slices that meet resource requirements. Different access criteria are set according to the differentiated services in different scenarios, and dynamic adjustment control is implemented for services. Thus, the implementation of access to different network slices can be guaranteed, and the indicator requirements of different services can be met.

[0005] According to a first aspect of the present invention, in order to achieve the above objective, the present invention provides the following technical solution: a network slicing access control method based on a time sampling interval, comprising the following steps: Based on new arrivals Service Hours Determine the start and end points of the time sampling interval; According to each business Startup time End time And the time sampling interval, and calculate the sampling ratio of each service within the time sampling interval; Load threshold based on network slicing Current load of each network slice Throughput of each service And the sampling ratio, to calculate the throughput capacity of each service. and the throughput capacity of each network slice ; Calculate the latency space for each service and delay margin Based on this, the latency margin of all network slices is calculated. ; The latency sensitivity type of newly arriving services is determined based on their application rate. For latency-sensitive new services, the slice with the largest latency margin is selected as the target slice, and its priority is updated for access. For non-latency-sensitive new services, the target slice with the largest throughput margin is selected for access.

[0006] Furthermore, based on new arrivals business Service Hours The start and end points of the time sampling interval are determined as follows: (21) For any business Calculate its business end time Calculate new arrivals End time (22): If the condition is met Then all services in all slices will be included in the sampling target; if the condition is met... Then calculate the starting point of the sampling interval. The endpoint of the sampling interval is .

[0007] Furthermore, according to each business Startup time End time And the time sampling interval, calculate the sampling ratio of each service within the time sampling interval, as follows: (31) For any business If the conditions are met or Then the sampling interval ratio of this service ; Calculate the remaining business Sampling start point Calculate the remaining business sampling termination point in, Describes the minimum value function. Represents the maximum value function; (32) Computing services sampling interval ratio .

[0008] Furthermore, load threshold based on network slices Current load of each network slice Throughput of each service And the sampling ratio, to calculate the throughput capacity of each service. and the throughput capacity of each network slice The details are as follows: (41) Set network slice load threshold For any network slice Calculate its remaining load ; Calculate any business throughput (42) Computing services throughput margin ; Calculate slices throughput margin .

[0009] Furthermore, calculate the latency space for each service. and delay margin Based on this, the latency margin of all network slices is calculated. The details are as follows: (51) Calculate any business Time delay space Based on this, calculate its time delay margin. ; (52) Calculate network slices delay margin .

[0010] Furthermore, the latency sensitivity type of newly arriving services is determined based on their application rate. For latency-sensitive new services, the slice with the largest latency margin is selected as the target slice, and its priority is updated for access. For non-latency-sensitive new services, the target slice with the largest throughput margin is selected for access, as detailed below: (61) Set a rate threshold for newly arriving services For new business If the conditions are met This service is determined to be a non-latency-sensitive service; the service with the largest throughput capacity is selected. The network slice is used as the target slice for access, and the new service is placed at the end of the queue of the target slice; (62) If the condition is met Then select the one with the largest delay margin. The network slice is used as the target slice for access, and the latency margin value of all services within this slice is calculated. And the latency tolerance of new services Arranged in ascending order, they are sent to the target slice scheduling in sequence.

[0011] According to a second aspect of the present invention, the present invention provides a network slice access control system based on a time sampling interval, for implementing the network slice access control method based on a time sampling interval described in the first aspect, comprising: The time sampling interval determination module is used to determine the time sampling interval based on newly arriving services. Service Hours Determine the start and end points of the time sampling interval; The sampling interval ratio calculation module is used to calculate the ratio based on various services. Startup time End time And the time sampling interval, and calculate the sampling ratio of each service within the time sampling interval; The throughput margin calculation module is used for load thresholding based on network slices. Current load of each network slice Throughput of each service And the sampling ratio, to calculate the throughput capacity of each service. and the throughput capacity of each network slice ; The latency margin calculation module is used to calculate the latency space for each service. and delay margin Based on this, the latency margin of all network slices is calculated. ; The new service access control module is used to determine the latency sensitivity type of newly arriving services based on their application rate. For latency-sensitive new services, the slice with the largest latency margin is selected as the target slice, and its priority is updated for access. For non-latency-sensitive new services, the target slice with the largest throughput margin is selected for access.

[0012] According to a third aspect of the present invention, a terminal device is provided, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores the computer program capable of running on the processor, and when the processor loads and executes the computer program, it employs the network slicing access control method based on time sampling intervals described in the first aspect.

[0013] According to a fourth aspect of the present invention, the present invention provides a storage medium containing computer-executable instructions, wherein the computer-executable instructions, when executed by a computer processor, are used to perform a network slice access control method based on a time sampling interval as described in the first aspect.

[0014] According to a fifth aspect of the present invention, the present invention provides a computer program product, characterized in that the computer program product includes a computer program, which, when executed by a processor, is used to load and execute the network slice access control method based on time sampling intervals as described in the first aspect.

[0015] This invention has at least the following beneficial effects: 1. This invention, through the time sampling interval determination step, can dynamically define the time analysis window based on the service time of newly arrived services, accurately identify the set of existing services that may compete for resources with the target service within the time window, and quantify the resource overlap of each service on the time axis by combining the service sampling ratio calculation. This enables the prediction of the resource competition situation in future time periods and avoids the problem of frequent conflicts after access caused by traditional methods that make decisions based solely on instantaneous load status.

[0016] 2. This invention targets latency-sensitive services. Based on latency margin calculation results, it prioritizes the slice with the largest latency margin for access and ensures that urgent services receive the highest priority through an ascending-order scheduling mechanism based on latency tolerance values, thereby reducing the average access latency of latency-sensitive services. For non-latency-sensitive services, it selects target slices based on the principle of maximizing throughput margin, effectively avoiding resource mismatch problems caused by homogeneous service processing in traditional methods.

[0017] 3. By introducing a slice load threshold and a remaining load calculation mechanism, this invention always maintains a safety margin during resource allocation, prevents slice load overload, dynamically senses and avoids congestion risks during peak business periods, reduces the access failure rate of the system under heavy load conditions, and ensures the long-term stable operation of the slice network.

[0018] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the method described in this invention; Figure 2 This is a comparison chart of the average service access latency between the present invention and traditional algorithms; Figure 3 This is a comparison chart of the slice access throughput of the present invention and traditional algorithms. Detailed Implementation

[0020] The technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0021] Example 1: Please see Figures 1-3 This invention provides a technical solution: a network slice access control method based on time sampling intervals, including defining a statistical start time. ; Network slices Network slicing Current load ;slice It already contains Business For any business Relative to the start time of statistics Business launch time Service hours and the resulting business throughput Business latency and latency tolerance Current moment New arrivals business Service hours Application processing speed Delay tolerance ; The specific steps are as follows: S1. Based on new arrivals Service Hours The start and end points of the time sampling interval are determined as follows: Step 1-1: For any business Calculate its business end time Calculate new arrivals End time ; Step 1-2: If the conditions are met Then all services in all slices will be included in the sampling target; if the condition is met... Then calculate the starting point of the sampling interval. The endpoint of the sampling interval is ; S2. Based on each business Startup time End time And the time sampling interval, calculate the sampling ratio of each service within the time sampling interval, as follows: Step 2-1: For any business If the conditions are met or Then the sampling interval ratio of this service ; Calculate the remaining business Sampling start point Calculate the remaining business sampling termination point ;in, Describes the minimum value function. Represents the maximum value function; Step 2-2: Calculate the business sampling interval ratio ; S3. Load threshold based on network slice Current load of each network slice Throughput of each service And the sampling ratio, to calculate the throughput capacity of each service. and the throughput capacity of each network slice The details are as follows: Step 3-1: Set the slice load threshold For any slice Calculate its remaining load ; Calculate any business throughput ; Step 3-2: Calculate the business throughput margin ; Calculate slices throughput margin ; S4. Calculate the latency space for each service. and delay margin Based on this, the latency margin of all network slices is calculated. The details are as follows: Step 4-1: Calculate arbitrary business Time delay space Based on this, calculate its time delay margin. ; Step 4-2: Calculate slices delay margin ; S5. Determine the latency sensitivity type of newly arriving services based on their application rate. For latency-sensitive new services, select the slice with the largest latency margin as the target slice and update its priority for access. For non-latency-sensitive new services, select the target slice with the largest throughput margin for access, as detailed below: Step 5-1: Set the rate threshold For new businesses If the conditions are met This service can be approximated as a non-latency-sensitive service; therefore, the service with the maximum throughput capacity should be selected. The slice is used as the target slice for access, and the new service is placed at the end of the queue of the target slice; Step 5-2: If the conditions are met Then select the one with the largest delay margin. The slice is used as the target slice for access, and the latency margin value of all services within that slice is determined. And latency tolerance for new services Arranged in ascending order, they are sent to the target slice scheduling in sequence.

[0022] The technical solution of the present invention will be further described below with reference to specific embodiments: Below, m The present invention will be specifically described using an example. The network slicing of 5G is shown in Table 1: Table 1. Services Existing in Each 5G Network Slice The details of new business are shown in Table 2: Table 2 New Arrival Business Status The basic data is shown in Table 3: Table 3 Basic Data This example describes a 5G network slicing access control method based on time sampling intervals, including the following steps: defining the time sampling interval, measuring the service sampling interval ratio, calculating throughput margin, calculating latency margin, and controlling new service access. Step 1: Define the time sampling interval; Step 1-1: For any business Calculate its business end time Calculate new arrivals End time ; Step 1-2: Conditions are met Then calculate the starting point of the sampling interval. The endpoint of the sampling interval is ; Step 2: Measure the proportion of the business sampling interval; Step 2-1: Srv(1,1) satisfies the condition Then the sampling interval ratio of this service ; Calculate the remaining business Sampling start point Calculate the remaining business sampling termination point ; Step 2-2: Calculate the business sampling interval ratio ; Step 3: Calculate throughput margin; Step 3-1: For any slice Calculate its remaining load ; Calculate any business throughput ; Step 3-2: Calculate the business throughput margin ; Calculate slices throughput margin ; Step 4: Calculate the delay margin; Step 4-1: Calculate arbitrary business Time delay space Based on this, calculate its time delay margin. ; Step 4-2: Calculate slices delay margin ; Step 5: New service access control; Step 5-1: New Business The conditions are not met. ; Step 5-2: New Business Meet the conditions Then select the one with the largest delay margin. The slice is used as the target slice for access, and the latency margin value of all services within that slice is determined. And latency tolerance for new services Sort in ascending order, we get: Each corresponds to a business And sequentially send them to the target slice scheduling; Simulation experiment: The prior art (application number: 202211365786.8) discloses a 5G network slicing access control method based on service type (hereinafter referred to as the conventional method). This invention uses the TSI-NSAC 5G network slicing access control method based on time sampling intervals. The aforementioned prior art is simulated on a MATLAB platform. Network and service configurations are performed according to the above table. The resulting average access latency and access throughput are shown in the appendix. Figures 2 to 3 As shown.

[0023] like Figure 2 As shown, both algorithms operate by selectively accessing different target slices based on the attributes of the new service. For latency-sensitive services, meeting the latency requirements of that service is the primary objective. Therefore, during the initial access phase of the simulation, the slice load is low, the possibility of service collisions is small, and each slice strives to minimize the total latency of the accessed service, especially the traditional method. TSI-MBT, on the other hand, determines the latency margin of the target slice based on the sampling interval. This can lead to slight distortion when the sampling quantity is small or the sampling time is short. Therefore, in the initial stage, the performance of the TSI-NSAC algorithm is slightly lower. As the number of accessed services increases, the slice links become increasingly congested, and the access latency of both algorithms increases. However, the benefit for TSI-NSAC is that with the increase in the number of samples, the calculated latency margin becomes more accurate, allowing it to detect target slices more suitable for latency-sensitive services for access. Meanwhile, larger-granularity service access provides a more substantial time sampling interval (a larger proportion of service sampling intervals), which is also more conducive to the TSI-NSAC algorithm coordinating collisions between new and existing services, thereby shortening access latency. In contrast, traditional methods tend to experience a decline in service quality as the number of access services increases. Therefore, in overall comparison, the protection role of TSI-NSAC is more significant, and the most direct effect is that the overall service latency does not increase too rapidly. Reflected in the latency curve, the method in this embodiment generally outperforms the traditional method. like Figure 3As shown, access throughput reflects slice bandwidth performance. Traditional methods, during the startup phase, simply control throughput-sensitive services based on the amount of physical resources consumed per unit of service within the transmission queue, thus wasting system resources and resulting in slightly higher throughput performance. However, as the number of access services increases, system congestion intensifies, naturally reducing resource utilization. For traditional methods without corresponding countermeasures, throughput jitter increases, and the growth trend of throughput performance slows down. TSI-NSAC, on the other hand, comprehensively considers throughput calculated from load measurements and throughput margins to select the slice that best meets the rate requirements of new services as the target slice for access. Furthermore, with an increased number of access services, sampling accuracy is higher, making it easier to control congestion behavior among access services. Reflected in the curve, TSI-NSAC's throughput performance is significantly better than traditional methods, improving customer experience and ensuring the robustness of the sliced ​​network.

[0024] Example 2: This embodiment provides a network slicing access control system based on time sampling intervals, used to implement the network slicing access control method based on time sampling intervals described in Embodiment 1, including: The time sampling interval determination module is used to determine the time sampling interval based on newly arriving services. Service Hours Determine the start and end points of the time sampling interval; The sampling interval ratio calculation module is used to calculate the ratio based on various services. Startup time End time And the time sampling interval, and calculate the sampling ratio of each service within the time sampling interval; The throughput margin calculation module is used for load thresholding based on network slices. Current load of each network slice Throughput of each service And the sampling ratio, to calculate the throughput capacity of each service. and the throughput capacity of each network slice ; The latency margin calculation module is used to calculate the latency space for each service. and delay margin Based on this, the latency margin of all network slices is calculated. ; The new service access control module is used to determine the latency sensitivity type of newly arriving services based on their application rate. For latency-sensitive new services, the slice with the largest latency margin is selected as the target slice, and its priority is updated for access. For non-latency-sensitive new services, the target slice with the largest throughput margin is selected for access.

[0025] Example 3: The present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and capable of running on the processor. The memory stores the computer program capable of running on the processor. When the processor loads and executes the computer program, it adopts the network slicing access control method based on time sampling interval described in Embodiment 1.

[0026] It should be noted that the terminal device can be a computer device such as a desktop computer, a laptop computer, or a cloud server, and the terminal device includes, but is not limited to, a processor and a memory. For example, the terminal device may also include input / output devices, network access devices, and buses.

[0027] Furthermore, the processor can be a central processing unit (CPU). Of course, depending on the actual use, other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), off-the-shelf programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. can also be used. The general-purpose processor can be a microprocessor or any conventional processor, etc., and this application does not limit it in this regard.

[0028] Example 4: The present invention provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the network slice access control method based on time sampling intervals described in Embodiment 1.

[0029] The computer program can be stored in a computer-readable medium. The computer program includes computer program code, which can be in the form of source code, object code, executable file, or certain middleware. The computer-readable medium includes any entity or device capable of carrying computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the computer-readable medium includes, but is not limited to, the above-mentioned components.

[0030] Example 5: The present invention provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it is used to load and execute the network slice access control method based on time sampling interval described in Embodiment 1.

[0031] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0032] For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances. When an element is referred to as being "assembled on," "mounted on," "fixed to," or "set on" another element, it may be directly on the other element or there may be an intermediate element present. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be an intermediate element present. The terms "vertical," "horizontal," "upper," "lower," "left," "right," and similar expressions used herein are for illustrative purposes only and do not represent the only possible embodiments.

[0033] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

[0034] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

Claims

1. A network slicing access control method based on time sampling intervals, characterized in that, Includes the following steps: Based on new arrivals Service Hours Determine the start and end points of the time sampling interval; According to each business Startup time End time And the time sampling interval, and calculate the sampling ratio of each service within the time sampling interval; Load threshold based on network slicing Current load of each network slice Throughput of each service And the sampling ratio, to calculate the throughput capacity of each service. and the throughput capacity of each network slice ; Calculate the latency space for each service and delay margin Based on this, the latency margin of all network slices is calculated. ; The latency sensitivity type of newly arriving services is determined based on their application rate. For latency-sensitive new services, the slice with the largest latency margin is selected as the target slice, and its priority is updated for access. For non-latency-sensitive new services, the target slice with the largest throughput margin is selected for access.

2. The network slice access control method based on time sampling interval according to claim 1, characterized in that: Based on new arrivals Service Hours The start and end points of the time sampling interval are determined as follows: (21) For any business Calculate its business end time Calculate new arrivals End time ; (22): If the condition is met Then all services in all slices will be included in the sampling target; if the condition is met... Then calculate the starting point of the sampling interval. The endpoint of the sampling interval is .

3. The network slice access control method based on time sampling interval according to claim 2, characterized in that: According to each business Startup time End time And the time sampling interval, calculate the sampling ratio of each service within the time sampling interval, as follows: (31) For any business If the conditions are met or Then the sampling interval ratio of this service ; Calculate the remaining business Sampling start point Calculate the remaining business sampling termination point ;in, Describes the minimum value function. Represents the maximum value function; (32) Computing services sampling interval ratio .

4. The network slice access control method based on time sampling interval according to claim 3, characterized in that: Load threshold based on network slicing Current load of each network slice Throughput of each service And the sampling ratio, to calculate the throughput capacity of each service. and the throughput capacity of each network slice The details are as follows: (41) Set network slice load threshold For any network slice Calculate its remaining load ; Calculate any business throughput ; (42) Computing services throughput margin ; Calculate slices throughput margin .

5. The network slice access control method based on time sampling interval according to claim 4, characterized in that: Calculate the latency space for each service and delay margin Based on this, the latency margin of all network slices is calculated. The details are as follows: (51) Calculate any business Time delay space Based on this, calculate its time delay margin. ; (52) Calculate network slices delay margin .

6. The network slice access control method based on time sampling interval according to claim 5, characterized in that: The latency sensitivity type of newly arriving services is determined based on their application rate. For latency-sensitive new services, the slice with the largest latency margin is selected as the target slice, and its priority is updated for access. For non-latency-sensitive new services, the target slice with the largest throughput margin is selected for access, as detailed below: (61) Set a rate threshold for newly arriving services For new businesses If the conditions are met This service is determined to be a non-latency-sensitive service; the service with the largest throughput capacity is selected. The network slice is used as the target slice for access, and the new service is placed at the end of the queue of the target slice; (62) If the condition is met Then select the one with the largest delay margin. The network slice is used as the target slice for access, and the latency margin value of all services within this slice is calculated. And the latency tolerance of new services Arranged in ascending order, they are sent to the target slice scheduling in sequence.

7. A network slice access control system based on a time sampling interval, used to implement the network slice access control method based on a time sampling interval as described in any one of claims 1 to 6, characterized in that, include: The time sampling interval determination module is used to determine the time sampling interval based on newly arriving services. Service Hours Determine the start and end points of the time sampling interval; The sampling interval ratio calculation module is used to calculate the ratio based on various services. Startup time End time And the time sampling interval, and calculate the sampling ratio of each service within the time sampling interval; The throughput margin calculation module is used for load thresholding based on network slices. Current load of each network slice Throughput of each service And the sampling ratio, to calculate the throughput capacity of each service. and the throughput capacity of each network slice ; The latency margin calculation module is used to calculate the latency space for each service. and delay margin Based on this, the latency margin of all network slices is calculated. ; The new service access control module is used to determine the latency sensitivity type of newly arriving services based on their application rate. For latency-sensitive new services, the slice with the largest latency margin is selected as the target slice, and its priority is updated for access. For non-latency-sensitive new services, the target slice with the largest throughput margin is selected for access.

8. A terminal device, comprising a memory, a processor, and a computer program stored in the memory and capable of running on the processor, characterized in that, The memory stores a computer program that can run on the processor. When the processor loads and executes the computer program, it employs the network slicing access control method based on time sampling intervals as described in any one of claims 1 to 6.

9. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the network slice access control method based on time sampling intervals as described in any one of claims 1 to 6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, is used to load and execute the network slice access control method based on time sampling intervals as described in any one of claims 1 to 6.

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