Network slice configuration optimization method and system

Abstract

The invention provides a network slice configuration optimization method and system, and relates to the technical field of communication networks. The method comprises the following steps: firstly, acquiring first service demand data and second service demand data corresponding to a first network slice and a second network slice, and acquiring resource occupation state data of a shared resource between the two slices; secondly, determining a target conflict event according to the second service demand data and the resource occupation state data; calculating a resource configuration parameter based on the conflict event and an association relationship between the second service demand data and the resource occupation state data; generating a configuration instruction according to the resource configuration parameters, and establishing an isolation resource channel in shared resources between the two network slices; and finally, the service flow of the second network slice is routed to the isolation resource channel for transmission. According to the technical scheme provided by the invention, seamless and accurate redirection from the service flow to the newly established isolation channel is realized, and the key service performance is also ensured.

Description

Technical Field

[0001] This application relates to the field of communication network technology, and in particular to an optimization method and system for network slicing configuration. Background Technology

[0002] In 5G mobile communication networks, network slicing technology virtualizes multiple logically independent networks on a shared physical network infrastructure to simultaneously meet the performance requirements of differentiated services such as enhanced mobile broadband (eMBB), ultra-reliable low-latency communication (uRLLC), and massive machine-type communication (mMTC). A typical application scenario is that high-bandwidth services carried by eMBB slices and mission-critical services carried by uRLLC slices need to share radio time and frequency resources under the same base station. In this scenario, the sudden large-volume transmission of eMBB services will instantly occupy a large amount of shared resources, causing uRLLC slice service requests to queue or be dropped due to insufficient resources, resulting in severe end-to-end latency jitter or even timeout, which cannot meet the strict deterministic latency and high reliability requirements of uRLLC services.

[0003] Currently, the solution adopted to address the performance conflict caused by the aforementioned resource contention is a dynamic resource adjustment scheme based on real-time monitoring and threshold triggering. This scheme continuously monitors the real-time performance indicators and resource utilization of each network slice on shared resources, presets a performance threshold for each slice, and determines that a resource conflict has occurred when the monitoring system detects that the performance indicators of a certain slice continue to deteriorate and exceed its preset threshold. Then, according to a predefined strategy, a portion of the resources are immediately reclaimed from the slices identified as consuming too many resources, and statically redistributed to the slices with poor performance in an attempt to mitigate their performance degradation. However, this existing solution has significant drawbacks. First, it adopts a passive, reactive approach, intervening only after performance indicators have actually deteriorated and the impact of conflicts has occurred. This lag may lead to irreversible latency violations in uRLLC services before resource adjustments take effect. Second, its resource adjustment strategies are often static or semi-static, lacking a fine-grained quantification of the root causes of conflicts and the actual dynamic needs of the business. The adjustment process may be too coarse, resulting in low resource utilization efficiency, or excessively damaging the performance of another slice while solving the performance problem of one slice, causing new unfairness or performance fluctuations. Third, this solution usually lacks a complete closed-loop control logic based on optimization goals. There is no continuous, adaptive calibration mechanism between resource adjustment actions and the ultimate business quality assurance goals to be achieved, resulting in a discontinuous optimization process. Summary of the Invention

[0004] This application provides a method and system for optimizing network slice configuration, in order to solve the problems of lagging resource configuration adjustment, coarse adjustment strategies and lack of continuous optimization loop in the prior art.

[0005] Firstly, this application provides a method for optimizing network slicing configuration, including: Obtain the first service requirement data of the first network slice and the second service requirement data of the second network slice; Obtain resource occupancy status data of shared resources between the first network slice and the second network slice; Based on the second business requirement data and the resource occupancy status data, the target conflict event is determined; Based on the conflict events and the correlation between the second business requirement data and the resource occupancy status data, resource configuration parameters are calculated; Based on the resource configuration parameters, generate configuration instructions; Based on the configuration instructions, an isolated resource channel is established in the shared resources between the first network slice and the second network slice to route the service traffic of the second network slice to the isolated resource channel for transmission.

[0006] Optionally, based on the second business demand data and the resource occupancy status data, a target conflict event is determined, including: Extract the service constraints of the second network slice from the second service requirement data; Extract the historical resource usage records of the first network slice on shared resources from the resource occupancy status data; Based on the historical resource usage records, predict the resource occupancy trend of the first network slice in the future time window; By combining the business constraints with the resource occupancy trend, the processing of business requests for the second network slice on the shared resources is simulated within a future time window. Based on the simulated processing procedure, determine whether the business constraints will be violated; When the determination result indicates that the business constraint will be violated, a target conflict event is determined to have occurred.

[0007] Optionally, based on the conflict event and the correlation between the second business requirement data and the resource occupancy status data, resource configuration parameters are calculated, including: Obtain the resource requirement information of the second network slice from the second service requirement data; Obtain the occupancy rate information of the first network slice on the shared resource from the resource occupancy status data; Identify the conflict time period corresponding to the conflict event and the degree of performance degradation caused by the conflict event; Based on the resource demand information, the occupancy rate information, the conflict time period, and the performance degradation level, calculate the resource compensation amount; Based on the resource compensation amount and the total amount of shared resources, calculate the resource configuration parameters.

[0008] Optionally, based on the resource compensation amount and the total amount of the shared resources, resource configuration parameters are calculated, including: The first proportional factor is calculated based on the proportion of the resource compensation amount to the total amount of shared resources; From the resource occupancy status data, obtain the occupancy ratio of the first network slice on the shared resource, and use the occupancy ratio as the second ratio factor; Determine the reservation ratio factor based on the preset resource reservation strategy; The first proportional factor, the second proportional factor, and the reserved proportional factor are combined to generate a resource allocation coefficient. Based on the resource allocation coefficient and the total amount of shared resources, the number of resources used to establish isolated resource channels is calculated, and the number of resources is used as a resource configuration parameter.

[0009] Optionally, configuration instructions are generated based on the resource configuration parameters, including: Extract the quantity of resources to be allocated and the resource location identifiers from the resource configuration parameters; Based on the resource location identifier, determine the set of target resource blocks corresponding to the shared resource; Based on the number of resources to be allocated, a preset number of target resource blocks are selected from the set of target resource blocks; Create an independent resource channel identifier for the second network slice, and establish a mapping relationship between the independent resource channel identifier and the target resource block; Based on the mapping relationship, a configuration instruction is generated, which includes the independent resource channel identifier, the information of the target resource block, and the identifier of the second network slice.

[0010] Optionally, based on the mapping relationship, configuration instructions are generated, including: Obtain the association information between the independent resource channel identifier and the target resource block from the mapping relationship; Based on the association information, a first instruction field and a second instruction field are generated, wherein the first instruction field contains the configuration attributes of the target resource block, and the second instruction field contains the configuration attributes of the independent resource channel identifier; The first instruction field, the second instruction field, and the identifier of the second network slice are combined to form configuration instruction data; Based on the structure of the configuration instruction data, a configuration instruction containing an instruction header and an instruction body is generated, wherein the instruction header contains an instruction type identifier and the instruction body contains the configuration instruction data.

[0011] Optionally, based on the configuration instructions, an isolated resource channel is established in the shared resources between the first network slice and the second network slice to route the service traffic of the second network slice to the isolated resource channel for transmission, including: The configuration instructions are parsed to obtain information about the target resource block, the independent resource channel identifier, and the identifier of the second network slice; A resource allocation request is sent to the control entity that manages the shared resources, so that the control entity allocates the target resource block from the shared resources and binds the target resource block with the independent resource channel identifier to establish the isolated resource channel. The resource allocation request includes information about the target resource block and the independent resource channel identifier. At the network entry node through which the service traffic of the second network slice enters the shared resource, a traffic forwarding rule corresponding to the independent resource channel identifier is created. According to the traffic forwarding rules, the service traffic of the second network slice is redirected from the network ingress node to the target resource block bound to the independent resource channel identifier for transmission.

[0012] Secondly, this application provides an optimization system for network slicing configuration, comprising: The first acquisition module is used to acquire the first service requirement data of the first network slice and the second service requirement data of the second network slice; The second acquisition module is used to acquire resource occupancy status data of shared resources between the first network slice and the second network slice; The determination module is used to determine the target conflict event based on the second business requirement data and the resource occupancy status data; The calculation module is used to calculate resource configuration parameters based on the conflict event and the correlation between the second business requirement data and the resource occupancy status data; The generation module is used to generate configuration instructions based on the resource configuration parameters; A module is established to establish an isolated resource channel in the shared resources between the first network slice and the second network slice based on the configuration instructions, so as to route the service traffic of the second network slice to the isolated resource channel for transmission.

[0013] Thirdly, this application provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement an optimization method for network slicing configuration as described in the first aspect above.

[0014] Fourthly, this application provides a computer storage medium storing a computer program, which, when executed by a computer, implements an optimization method for network slicing configuration as described in the first aspect.

[0015] This application proactively identifies target conflict events based on the service demand data and real-time resource occupancy status data of the second network slice. This allows for the pre-identification of potential resource conflict risks before the service performance of the second network slice, such as the uRLLC slice, actually deteriorates due to resource contention. This prediction-based conflict determination mechanism changes the past passive response model that only occurred after performance indicators worsened, significantly advancing optimization actions and effectively avoiding performance degradation of critical services such as low-latency services due to delayed response. Furthermore, resource configuration parameters are calculated based on the correlation between the conflict events, service demands, and resource status. This ensures that the resource compensation planned for the second network slice more accurately matches the actual needs of its service guarantee and the severity of the conflict, rather than making fixed-ratio or simple preemptive adjustments. This makes resource configuration decisions more targeted and reasonable, improving the precision of the optimization strategy from the source.

[0016] Furthermore, resource configuration parameters are transformed into configuration instructions containing explicit information such as target resource blocks and independent channel identifiers. Through interaction with the underlying control entity, isolated resource channels are actually partitioned and bound within shared resources. Subsequently, by creating corresponding traffic forwarding rules at the network entry node, the service traffic of the second network slice can be accurately redirected to this isolated channel for transmission. On this basis, not only are the aforementioned optimization decisions executed accurately on the physical network, constructing a logically isolated and dedicated resource guarantee channel, but more importantly, it completes a fully automated closed loop from conflict prediction to policy calculation to channel establishment and traffic guidance. This closed loop enables the network to dynamically and continuously execute the optimization process of perception, decision-making, and execution based on real-time service status and resource situation, thereby systematically solving the problems of lagging resource configuration, coarse policies, and lack of continuous optimization capabilities. Therefore, the technical solution of this application can achieve proactive prevention and refined, closed-loop resolution of resource conflicts between network slices.

[0017] These or other aspects of this application will become more apparent in the following description of the embodiments. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating an optimization method for network slicing configuration provided in this application is shown; Figure 2 A schematic diagram of the structure of an optimization system for network slicing configuration provided in this application is shown; Figure 3 A schematic diagram of the structure of a computing device provided in this application is shown. Detailed Implementation

[0020] To enable those skilled in the art to better understand the present application, the technical solution of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0021] In some of the processes described in the specification, claims, and accompanying drawings of this application, multiple operations appearing in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order they appear herein, or may be executed in parallel. The operation numbers, such as 101, 102, etc., are merely used to distinguish different operations and do not themselves represent any execution order. Furthermore, these processes may include more or fewer operations, and these operations may be executed sequentially or in parallel. It should be noted that the descriptions such as "first," "second," etc., in this document are used to distinguish different messages, devices, modules, etc., and do not represent a chronological order, nor do they limit "first" and "second" to different types.

[0022] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] Figure 1 A flowchart of an optimization method for network slicing configuration is provided in this application, as shown below. Figure 1 As shown, the method includes: Step 101: Obtain the first service requirement data of the first network slice and the second service requirement data of the second network slice.

[0024] In this step, the first network slice refers to the first independent logical network instance created on a shared physical network infrastructure to carry a specific type of service. It is used to transmit a type of service flow that has specific requirements for network resources and is created through the network management configuration interface.

[0025] The first service requirement data refers to the set of data describing the service quality level required for the first network slice, used to clearly define the key network performance indicators required for the operation of the slice's services.

[0026] A second network slice refers to a second, independent logical network instance created on the same shared physical network infrastructure to carry a different type of service. It is used to transmit a type of service flow that has different or more stringent requirements for network performance and is created through the network management configuration interface.

[0027] Secondary service requirement data refers to the set of data that describes the quality of service level that the second network slice must guarantee. It is used to clearly define the network performance indicators required for the operation of the slice's services, which are usually more stringent or critical.

[0028] In this step, firstly, the control module calls the northbound application programming interface provided by the network slice management component to send a query request to the network slice management component. This query request uses the Hypertext Transfer Protocol and explicitly includes the unique identifiers of the first and second network slices in the request message body. Secondly, after receiving the query request, the network slice management component's internal query processing engine uses these two slice identifiers to search the background relational database. By executing Structured Query Language commands, it finds the Service Level Agreement (SLA) configuration file stored in YAML format that is bound to these two identifiers. Then, a syntax parser within the network slice management component processes the retrieved SLA configuration file. The file is parsed. This parser reads the Service Level Agreement (SLA) configuration file layer by layer according to YAML syntax rules, identifies and extracts the predefined key fields describing service quality and their corresponding threshold values, such as latency limits and bandwidth guarantees. Finally, the parser packages and serializes all the extracted key fields and values ​​belonging to the first slice into a first business requirement data object. At the same time, it packages and serializes all the key fields and values ​​belonging to the second slice into a second business requirement data object. Finally, the network slice management component returns these two business requirement data objects to the control module through the same application programming interface response channel, thus completing the acquisition operation.

[0029] For example, in a mobile communication company's network laboratory test bench, two network slices are pre-configured. Slice Alpha, intended for web browsing and video-on-demand services for ordinary mobile phone users, is designated as the first network slice. Slice Beta, planned for real-time control signaling for autonomous vehicles, is designated as the second network slice. When this optimization method is initiated, its control module sends an HTTP GET request to the network slice orchestrator deployed in the core network. The request address contains the IDs of slice Alpha and slice Beta. Upon receiving the request, the network slice orchestrator retrieves the corresponding two YAML configuration files from its MySQL database using the slice ID. One configuration file specifies that slice Alpha must guarantee a downlink rate of 50Mbps, and the other specifies that the end-to-end latency of slice Beta must be less than 10 milliseconds. Simultaneously, the orchestrator's built-in YAML parsing library reads these two configuration files, extracts fields such as guaranteed rate: 50Mbps and latency limit: 10ms, and encapsulates them into two JSON objects. Finally, these two JSON objects, as the first and second service requirement data, are returned to the control module via an HTTP response.

[0030] Step 102: Obtain resource occupancy status data of shared resources between the first network slice and the second network slice.

[0031] In this step, the resource occupancy status data refers to the data set describing the actual usage of physical or virtual resources shared by the first network slice and the second network slice at a specific moment or time period. It is used to reflect the load distribution, remaining availability, and resource contention status of the shared resource pool in real time or near real time. The raw performance indicators are collected by the monitoring agent and then aggregated, timestamped, and formatted through a dedicated telemetry data pipeline.

[0032] In this step, firstly, monitoring agents deployed on shared network devices such as base stations, routers, and switches actively collect underlying resource metrics related to the service flows of the first and second network slices according to a predetermined sampling period. These monitoring agents use Simple Network Management Protocol (SMLP) to collect raw data such as the physical resource block utilization rate of a specific slice on a certain wireless channel, the bandwidth occupancy on a certain transmission port, and the CPU utilization rate on a certain computing node. Secondly, these timestamped raw data streams collected from different network locations and devices are pushed in real time to a central data stream processing engine, such as one based on Apache. In Kafka's message bus, the data aggregation module within the central data stream processing engine categorizes metric data belonging to the first and second network slices based on the network slice identifiers in the data. Simultaneously, a time synchronization module aligns all incoming raw data streams with local timestamps from different collection points, using a unified time provided by the network time protocol as a benchmark, ensuring comparability of different metrics across time dimensions. Next, the formatting unit organizes the categorized and time-aligned metrics into structured records according to a predefined data pattern; each record includes fields such as timestamp, slice identifier, resource type, and metric value. Finally, these structured records are persistently stored in a time-series database and simultaneously encapsulated into a unified resource usage status report containing details of the shared resource usage of the first and second network slices within a specific time window.

[0033] For example, following the specific implementation of the previous step, firstly, after the service flow begins to be transmitted in the Alpha first network slice and the Beta second network slice, it is necessary to obtain the usage of the shared radio spectrum and transmission bandwidth resources between them; secondly, on the base station and core network router carrying these two slices, the pre-deployed telemetry agent collects data every 100 milliseconds. This base station agent collects the number of physical resource blocks occupied by the Alpha and Beta slices respectively, and the router agent collects the outbound bandwidth of the ports occupied by the service flow from these two slices; then, these collected raw data are sent in real time to the Kafka message queue deployed in the network management area. The stream processing engine then subscribes to the queue. Its processing logic is to distinguish physical resource block usage data from port bandwidth data based on the tags in the raw data, and to calibrate the timestamps of all raw data to a unified system clock. Subsequently, the engine averages the usage of all physical resource blocks belonging to slice Alpha over the past second to obtain an instantaneous value of its wireless resource utilization. Similarly, it calculates the wireless resource utilization of slice Beta, as well as the bandwidth utilization of both on the router port. Finally, these calculated metrics are organized into records and stored in the InfluxDB time series database. When the analysis module needs it, it can query the time series database to retrieve the most recent complete report containing the wireless and transmission resource utilization of the two slices, obtaining the required resource utilization status data.

[0034] Step 103: Determine the target conflict event based on the second business requirement data and the resource occupancy status data.

[0035] Optionally, step 103 may specifically include: Step 1031: Extract the service constraints of the second network slice from the second service requirement data.

[0036] Step 1032: Extract the historical resource usage records of the first network slice on the shared resources from the resource occupancy status data.

[0037] Step 1033: Based on the historical resource usage records, predict the resource occupancy trend of the first network slice in the future time window.

[0038] Step 1034: Combine the business constraints with the resource occupancy trend to simulate the processing of business requests of the second network slice on the shared resources within a future time window.

[0039] Step 1035: Based on the simulated processing procedure, determine whether the business constraints will be violated.

[0040] Step 1036: When the judgment result is that the business constraint will be violated, a target conflict event is determined to have occurred.

[0041] In this step, the target conflict event refers to an event in the future where, due to the first network slice's occupation of shared resources, the service requests of the second network slice cannot meet their service constraints. This event is used to identify a resource conflict problem that needs to be pre-processed and optimized.

[0042] Business constraints refer to the performance limitations extracted from the second business requirement data that must be followed to operate the second network slice service, and are used to quantitatively evaluate whether the service quality of the service meets the standards.

[0043] Historical resource usage records refer to a series of time-sorted data points extracted from resource occupancy status data regarding the use of shared resources by the first network slice over a past period, used to analyze the historical patterns and rules of resource usage in that slice.

[0044] Resource occupancy trend refers to the direction and extent of changes in the shared resource occupancy of the first network slice within a specified future time period, inferred from historical resource usage records using a prediction algorithm. It is used to estimate the amount of remaining resources available for the second network slice at a future point in time.

[0045] A service request refers to an independent data transmission task or service unit that needs to be processed during the simulation process, representing the services of the second network slice. Each task has its required resource quantity and arrival time, and is used to reproduce the service behavior of the second network slice in the simulation environment. It is generated based on the service model of the second network slice.

[0046] In this step, firstly, a data parsing component processes the second business requirement data. This component, following a predefined data structure template, identifies and reads fields describing key service quality indicators and their corresponding values, such as the thresholds for maximum allowable latency and minimum required bandwidth, thereby extracting the business constraints of the second network slice. Secondly, a data filtering engine processes the resource occupancy status data. Based on the network slice identity tag carried in each resource occupancy status data record, it filters out all records tagged as the first network slice and sorts these records in ascending order according to their timestamps, thus forming a coherent historical resource usage record for the first network slice. Next, a time series prediction model processes this historical resource usage record, employing algorithms such as autoregressive integral moving average to analyze the data fluctuation patterns and periodicity in the historical resource usage record. Based on the learned patterns, it calculates a predicted sequence of shared resource occupancy rates for the first network slice within a specific future time period; this sequence represents the resource occupancy trend. Then, a discrete event simulator is used to simulate the business constraints and resource consumption trends. First, based on the known business characteristics of the second network slice, such as using a stochastic process like the Poisson process, a series of simulated business requests with random arrival timestamps and determined resource requirements are generated. Then, the discrete event simulator sets a virtual clock and loads the obtained resource consumption trends as background. In each step of the virtual clock, the discrete event simulator calculates the remaining available resources in the shared resource pool based on the resource consumption trend value corresponding to the current time. That is, whenever a new business request arrives, the discrete event simulator checks whether the current remaining resources are sufficient to process the business request immediately. If they are sufficient, resources are allocated and the processing time is calculated. If they are insufficient, the business request is placed in a waiting queue. At the same time, the discrete event simulator schedules the business requests in the queue according to the first-come, first-served rule and records the entire timeline of each business request from arrival, waiting to final processing. This process is the simulated processing process. Subsequently, a performance check module analyzes the result logs generated by the simulated processing, traversing all simulated business requests, extracting the end-to-end latency of each business request, and comparing the latency of each business request with the maximum allowable latency threshold specified in the extracted business constraints. If a certain number of simulated requests, such as more than 5%, are found to have end-to-end latency exceeding the specified threshold, the performance check module determines that the business constraints will be violated. Finally, the decision logic takes action based on the judgment result. If the performance check module determines that the business constraints will be violated, the decision logic immediately generates a signal confirming the occurrence of a target conflict event and outputs detailed information about the target conflict event.

[0047] For example, following the specific implementation of the previous step, after obtaining the service requirements and resource occupancy status of slices Alpha and Beta, the conflict prediction begins. Service constraints are extracted from the second service requirement data of slice Beta, specifically, the end-to-end latency must not exceed 20 milliseconds. Secondly, the historical data of physical resource block occupancy rate on the wireless channel for slice Alpha in the past 10 minutes is extracted from the resource occupancy status data. Then, a trained long short-term memory recurrent neural network model is used, inputting this historical resource usage record, to predict that the physical resource block occupancy rate of slice Alpha will rapidly climb from 60% to 85% in the next 30 seconds. This prediction sequence is the resource occupancy trend. Then, the discrete event simulator generates a simulated service request sequence of 30 seconds in length based on the service model of slice Beta. It is assumed that this service request arrives randomly at a rate of 50 per second, each service request needs to continuously occupy 5 physical resource blocks for 2 milliseconds, and the discrete event simulator is set to share a total of 100 physical resource blocks, and the predicted occupancy trend is used as background load. Subsequently, during the simulation, as virtual time progressed, when the predicted occupancy rate of slice Alpha reached 80%, the remaining resource blocks available for slice Beta decreased to 20. At this point, if multiple consecutive service requests from slice Beta arrived, they would be queued due to insufficient resources, causing the end-to-end latency of some requests calculated by the discrete event simulator to reach 25 milliseconds. Finally, the performance check module found that the proportion of these service requests exceeding the 20-millisecond threshold exceeded the preset tolerance line of 5%, thus determining that the service constraints would be violated and that a target conflict event would occur within the next 30 seconds.

[0048] This step utilizes prediction and simulation technologies to proactively identify resource conflict events, shifting the timing of optimization from post-event remediation to pre-event prevention, providing valuable lead time for taking optimization measures. Simultaneously, through detailed simulation of the entire business process, the basis for conflict determination is upgraded from a single threshold comparison to a reliable assessment of end-to-end performance, thereby improving the accuracy and reliability of decision-making.

[0049] Step 104: Calculate resource configuration parameters based on the conflict event and the correlation between the second business requirement data and the resource occupancy status data.

[0050] Optionally, step 104 may specifically include: Step 1041: Obtain the resource requirement information of the second network slice from the second service requirement data.

[0051] Step 1042: Obtain the occupancy rate information of the first network slice on the shared resource from the resource occupancy status data.

[0052] Step 1043: Identify the conflict time period corresponding to the conflict event and the degree of performance degradation caused by the conflict event.

[0053] Step 1044: Calculate the resource compensation amount based on the resource demand information, the occupancy rate information, the conflict time period, and the performance degradation degree.

[0054] Step 1045: Calculate resource configuration parameters based on the resource compensation amount and the total amount of shared resources.

[0055] Optionally, step 1045 may include the following steps: calculating a first proportional factor based on the proportion of the resource compensation amount to the total amount of shared resources; obtaining the occupancy ratio of the first network slice on the shared resources from the resource occupancy status data, and using the occupancy ratio as a second proportional factor; determining a reservation proportional factor according to a preset resource reservation strategy; combining the first proportional factor, the second proportional factor, and the reservation proportional factor to generate a resource allocation coefficient; and calculating the number of resources used to establish an isolated resource channel based on the resource allocation coefficient and the total amount of shared resources, and using the number of resources as a resource configuration parameter.

[0056] In this step, the resource configuration parameter refers to the final calculated amount of resources that need to be allocated from the shared resources to establish an isolated resource channel for the second network slice, which is used to precisely guide the subsequent channel establishment operation.

[0057] Resource requirement information refers to data obtained from the second service requirement data that describes the amount of basic resources required for the normal operation of the second network slice service. It is used to quantify the basic resource requirements of the slice under non-conflict conditions and is obtained by parsing the fields of basic guarantee indicators such as bandwidth, computing power or number of connections in the second service requirement data.

[0058] Occupancy rate information refers to data obtained from resource occupancy status data that describes the average or instantaneous utilization rate of shared resources by the first network slice within a certain period before and after the conflict occurs. It is used to reflect the level of resource competition pressure caused by the first network slice. It is obtained by extracting the resource utilization rate data of the first network slice within a specific time window from the resource occupancy status data and calculating the average value.

[0059] The conflict time period refers to the start and end times of the future time range from the identified target conflict events where business constraints are expected to be violated. It is used to define the effective period during which resource compensation needs to be implemented and is obtained by parsing the predicted conflict start and end times recorded in the target conflict event information.

[0060] The degree of performance degradation refers to the quantitative assessment of the extent to which the performance of the second network slice service deviates from its constraints due to the target conflict event. It is used to measure the severity of the conflict and determine the intensity of resource compensation required. It is calculated by comparing the estimated performance value of the service request during the simulation process with the threshold specified in the service constraints.

[0061] Resource compensation refers to the amount of additional resources required to offset the impact of conflicts and ensure that the second network slice service meets performance standards during the conflict period. It is used to quantify specific resource gaps.

[0062] The total amount of shared resources refers to the overall size or capacity limit of the physical or virtual resource pool used by the first network slice and the second network slice. It is used as a benchmark for the allocation ratio of computing resources and is obtained by querying the management interface of the network infrastructure.

[0063] The first proportional factor refers to the proportion of resource compensation to the total amount of shared resources. It is used to initially measure the share of resources that need to be allocated from the perspective of overall resources. It is obtained by dividing the resource compensation by the total amount of shared resources.

[0064] The occupancy ratio refers to the proportion of the first network slice's current or recent usage of shared resources relative to the total amount, obtained from resource occupancy status data. It is used to reflect the real-time load level of the first slice and is obtained by calculating the average resource usage of the first network slice in the recent period and dividing it by the total amount of shared resources.

[0065] The second proportional factor refers to using the occupancy ratio directly as an input factor in calculating resource allocation parameters. It is used to consider the existing load of the first network slice in resource allocation decisions to maintain fairness or system stability.

[0066] The preset resource reservation policy refers to a set of predefined rules that specify the minimum proportion of shared resources to be reserved for high-priority or critical business type slices under any circumstances. This is to ensure that the system still has basic guarantee capabilities in the worst case, and is read from the policy configuration file.

[0067] The reservation ratio factor refers to the fixed proportion of resources that need to be reserved for the second network slice or its service type, determined according to the preset resource reservation strategy, and is obtained by querying the attributes of the second network slice in accordance with the resource reservation strategy.

[0068] The resource allocation coefficient is a final weighted value that combines the first proportional factor, the second proportional factor, and the reserved proportional factor. It is used to dynamically calculate the final amount of resources to be allocated and is obtained by processing the three proportional factors through a weighted combination function.

[0069] The resource quantity of an isolated resource channel refers to the absolute amount of resources that will ultimately be allocated to the second network slice to establish the isolated channel, calculated based on the resource allocation coefficient and the total amount of shared resources. It is a specific manifestation of the resource configuration parameters and is obtained by multiplying the resource allocation coefficient by the total amount of shared resources.

[0070] In this step, firstly, the second business requirement data is parsed by the information extraction module to locate and read the fields describing basic resource guarantees, such as guaranteed bandwidth of 100 megabits per second or guaranteed computing units of 4, thereby obtaining the resource requirement information of the second network slice. Secondly, a statistical analysis component processes the resource occupancy status data, filters out all resource utilization records belonging to the first network slice within a time window close to the current moment, such as the last minute, and then calculates the average of these resource utilization records to obtain the occupancy information of the first network slice on shared resources. Next, the event parser analyzes the target conflict event, reads the event description, extracts the predicted conflict start time and end time, thereby identifying the conflict time period. At the same time, it reads the performance violation amount shown in the simulation results from the event details, such as the number of milliseconds that the average latency exceeds the threshold, or the percentage of requests exceeding the threshold, and quantifies this as the degree of performance degradation. Then, the compensation calculation model is activated and receives resource demand information, occupancy information, conflict time periods, and performance degradation as input. One calculation unit within the model calculates a basic compensation amount based on the resource demand information and performance degradation level. For example, for every unit increase in performance degradation, the basic compensation amount increases proportionally to the demand information. Another calculation unit then adjusts this basic compensation amount based on the length of the conflict time period and occupancy information. Higher occupancy indicates more intense resource competition, and the adjustment coefficient may be larger, thus calculating the final resource compensation amount. Finally, a scaling factor calculation unit divides the resource compensation amount by the total amount of shared resources obtained from network management queries. The first proportional factor is obtained, and the obtained occupancy information can be directly used as the second proportional factor. A preset resource reservation policy is queried from a policy configuration library based on the service type of the second network slice, such as mission-critical, and the corresponding reservation proportional factor is read. Finally, a coefficient synthesizer uses a weighted summation algorithm to assign appropriate weights to the first proportional factor, the second proportional factor, and the reservation proportional factor, and then adds them together to generate a resource allocation coefficient between 0 and 1. Finally, a multiplier multiplies the resource allocation coefficient by the total amount of shared resources, and the calculated product is the amount of resources used to establish isolated resource channels. This amount of resources is formally determined as the resource configuration parameter required for optimization.

[0071] For example, following the specific implementation of the previous step, firstly, after determining that a target conflict event will occur between slice Beta and slice Alpha within the next 30 seconds, the calculation begins to determine how many resources need to be allocated to slice Beta. Resource requirement information is obtained from slice Beta's service requirement data, indicating that the slice service needs to continuously guarantee a basic resource quantity of 20 physical resource blocks. Secondly, the current occupancy rate information of slice Alpha is obtained from the resource occupancy status data, showing that it occupies 70% of the resources in the shared wireless channel. Next, the conflict time period is identified as the next 10 to 25 seconds, and the performance degradation is assessed based on simulation results, indicating that the latency of some requests exceeds the standard by 5 milliseconds. Then, the compensation calculation model processes this input information and comprehensively... The resource compensation required to offset the impact of the conflict was calculated, and it was ultimately determined that an additional 12 physical resource blocks were needed. Then, the total number of shared wireless channel resource blocks was found to be 100, and a first proportional factor was calculated based on the resource compensation. Next, the current occupancy rate of slice Alpha was directly used as the second proportional factor, and a reserved proportional factor for critical services like slice Beta was determined according to a preset strategy. Then, by weighting and combining these three proportional factors, a final resource allocation coefficient was generated. Based on this resource allocation coefficient and the total shared resources, the number of resources required to establish an isolated resource channel for slice Beta was calculated, resulting in the allocation of 24 physical resource blocks. Finally, this resource quantity of 24 is the resource configuration parameter calculated in this study.

[0072] This step uses a dynamic calculation model to integrate the predicted conflict severity, real-time load, and system policies, transforming them into a precise resource allocation parameter. This enables the resource allocation scheme to not only compensate for performance losses in a targeted manner but also to take into account the overall network efficiency and fairness, providing a direct and reasonable quantitative basis for the subsequent establishment of isolation channels.

[0073] Step 105: Generate configuration instructions based on the resource configuration parameters.

[0074] Optionally, step 105 may specifically include: Step 1051: Extract the quantity of resources to be allocated and the resource location identifier from the resource configuration parameters.

[0075] Step 1052: Based on the resource location identifier, determine the set of target resource blocks corresponding to the shared resource.

[0076] Step 1053: Select a preset number of target resource blocks from the target resource block set according to the number of resources to be allocated.

[0077] Step 1054: Create an independent resource channel identifier for the second network slice, and establish a mapping relationship between the independent resource channel identifier and the target resource block.

[0078] Step 1055: Based on the mapping relationship, generate a configuration instruction, which includes the independent resource channel identifier, the target resource block information, and the identifier of the second network slice.

[0079] Optionally, step 1055 may include the following steps: obtaining the association information between the independent resource channel identifier and the target resource block from the mapping relationship; generating a first instruction field and a second instruction field based on the association information, wherein the first instruction field contains the configuration attributes of the target resource block, and the second instruction field contains the configuration attributes of the independent resource channel identifier; combining the first instruction field, the second instruction field, and the identifier of the second network slice to form configuration instruction data; generating a configuration instruction containing an instruction header and an instruction body according to the structure of the configuration instruction data, wherein the instruction header contains an instruction type identifier, and the instruction body contains the configuration instruction data.

[0080] In this step, the configuration instruction refers to a structured command or message used to dynamically establish an isolated resource channel for the second network slice in the shared resources, that is, to transform the calculated isolated resource channel scheme into a command that can be recognized and executed by the network device.

[0081] The number of resources to be allocated refers to the total amount of resources extracted from the resource configuration parameters that need to be allocated to the second network slice. It is used to determine the scale of resources to be allocated and is obtained by reading the resource quantity field contained in the resource configuration parameters.

[0082] Resource location identifiers refer to logical or physical address information extracted from resource configuration parameters, used to describe or index specific resources in a shared resource pool, and used to locate the range of resources available for allocation.

[0083] The target resource block set refers to the set of all available resource units located in the shared resource pool that match the location description based on the resource location identifier. It serves as a candidate pool for selecting specific resource blocks and is obtained by querying the resource management database or resource topology mapping table to match the resource location identifier.

[0084] The preset number of target resource blocks refers to one or more specific resource units actually selected from the target resource block set based on the number of resources to be allocated. These units will be actually allocated to the second network slice and obtained from the target resource block set through a resource selection algorithm such as continuous allocation.

[0085] An independent resource channel identifier is a unique identification symbol generated specifically for an isolated resource channel to be established, which is unique within the management domain. It is used to uniquely mark and address this newly established logical channel in the network and is generated by calling an identifier generator such as a UUID generation algorithm.

[0086] Mapping relationships refer to the corresponding association records between independent resource channel identifiers and their corresponding target resource blocks established in management. They are used to record which channel uses which specific resources. This is obtained by creating a record in a mapping table and associating the resource channel identifier with the identifier of the selected target resource block.

[0087] Association information refers to specific data obtained from the mapping relationship that describes the correspondence between independent resource channel identifiers and target resource blocks, and is used as source information for generating configuration instructions.

[0088] The first instruction field refers to a segment of structured data generated based on the associated information, which describes the specific configuration of the target resource block. It is used to carry the specific details of resource allocation in the configuration instruction and is obtained by encapsulating the identifier, status, parameters and other information of the target resource block in the associated information into a data block.

[0089] The second instruction field refers to a segment of structured data generated based on associated information, describing the identifier and attributes of an independent resource channel, and is used to carry the identifier and attributes of a newly created logical channel in the configuration instruction.

[0090] Configuration attributes describe the parameters and statuses that need to be set during the configuration of the target resource block or resource channel identifier, such as the resource's activation status, priority, scheduling policy, etc., which are obtained from preset configuration templates or policies.

[0091] The configuration instruction data refers to the core data payload containing complete configuration information, which is formed by combining the first instruction field, the second instruction field, and the identifier of the second network slice. It is obtained by splicing multiple fields in a predetermined format through a data assembly module.

[0092] The instruction header and instruction body are the two parts that make up the final configuration instruction. The instruction header is the control part of the instruction, which contains metadata such as the instruction type identifier and is used to indicate how to process the instruction body. The instruction body is the data part of the instruction, which contains the specific configuration instruction data. It is obtained by encapsulating the configuration instruction data in the instruction body and adding an instruction header in front of it.

[0093] The instruction type identifier is a specific code or string written in the instruction header, used to uniquely identify the operation type of this configuration instruction, such as creating an isolated channel, so that the receiver can correctly parse and execute it. It is obtained by looking up the corresponding operation code in the instruction type encoding table.

[0094] In this step, the resource configuration parameters are first processed by the parameter parsing module. According to a predefined data structure, the number of resources to be allocated (e.g., 24 resource blocks) and resource location identifiers (e.g., frequency band A, time slot groups 1-10) are extracted from the resource configuration parameters. Next, the resource locator receives the resource location identifiers and queries a topology database, searching for all resource units that match the resource location identifier description. This identifies all available physical resource blocks within the 10 time slots (1 to 10) under frequency band A, forming a target resource block set. Then, the resource selector receives the number of resources to be allocated and the target resource block set as input and runs a resource allocation algorithm, such as the first-fit algorithm. This first-fit algorithm scans from the beginning of the target resource block set, searching for the first... Once a contiguous range of available resource blocks, no less than the number of resources to be allocated, is found, the first-fit algorithm precisely selects contiguous resource blocks equal to the number of resources to be allocated and marks these resource blocks as the preset number of target resource blocks. Then, the identifier management and mapping module is started, calling a universal unique identifier generator to generate an independent resource channel identifier, such as Channel_XYZ123. Subsequently, the mapping module is started, creating a new record in an internal mapping table it maintains. In this new record, the generated independent resource channel identifier Channel_XYZ123 is associated with the selected preset number of target resource blocks, with each resource block having its own unique ID, thus establishing a one-to-one correspondence and completing the mapping relationship. Finally, from the newly established mapping relationship, the association information is obtained, and a command field generator extracts the target resource block's ID list and its default configuration attributes, such as activation status (enabled), based on the association information. This information is then packaged to generate the first command field. Simultaneously, the resource channel identifier Channel_XYZ123 and its attributes, such as channel type (isolated), are extracted and packaged to generate the second command field. Next, a data assembler combines the first command field, the second command field, and the identifier of the second network slice, such as Slice_Beta, according to a predefined format, such as JSON, to form a complete configuration command data. Then, a command wrapper adds a command header to this configuration command data. The command header contains a command type identifier obtained by looking up a table, such as OP_CREATE_ISO_CHANNEL. The wrapper concatenates the command header and command body, ultimately generating a complete, deployable configuration command.

[0095] For example, following the specific implementation of the previous step, firstly, after calculating that 24 physical resource blocks need to be allocated to slice Beta as resource configuration parameters, the number of resources to be allocated is extracted as 24, and the resource location identifier is the center frequency band of 2.6 GHz, time slots 0 to 9; secondly, the resource locator queries the resource management library based on this resource location identifier to determine that all 100 available physical resource blocks within this frequency band and time slot range constitute the target resource block set; then, the resource selector uses the first-fit algorithm to scan this target resource block set and finds that resource blocks from number 11 to 34 are consecutive and idle, so the first 24, i.e., resource blocks from number 11 to 34, are selected as the preset number of target resource blocks; then, an independent resource channel identifier is generated. The system identifies Iso-Ch-Beta-001 and creates a record in the internal mapping table, associating this resource channel identifier with resource block IDs 11 to 34. Based on this mapping, it creates a first instruction field containing a list of resource block IDs [11, 12, ..., 34] and the configuration attribute status = "Active". Simultaneously, it creates a second instruction field containing the channel identifier Iso-Ch-Beta-001 and the attribute type = "Hard Isolation". These two instruction fields are then combined with the slice identifier Beta to form a JSON-formatted configuration instruction data. Finally, an instruction header is added to this configuration instruction data, containing the instruction type identifier CreateIsolatedChannel. This complete configuration instruction is now ready to be sent to network devices for execution.

[0096] This step accurately converts the calculated resource configuration parameters into configuration commands that network devices can recognize and execute. Through standardized resource selection, identifier binding, and command encapsulation processes, it ensures that the resource configuration intent is completely and accurately conveyed, providing direct, operable, and traceable explicit operation commands for the subsequent establishment of isolated resource channels.

[0097] Step 106: Based on the configuration instructions, establish an isolated resource channel in the shared resources between the first network slice and the second network slice, so as to route the service traffic of the second network slice to the isolated resource channel for transmission.

[0098] Optionally, step 106 may specifically include: Step 1061: Parse the configuration command to obtain information about the target resource block, the independent resource channel identifier, and the identifier of the second network slice.

[0099] Step 1062: Send a resource allocation request to the control entity that manages the shared resources, so that the control entity allocates the target resource block from the shared resources and binds the target resource block with the independent resource channel identifier to establish the isolated resource channel. The resource allocation request includes information about the target resource block and the independent resource channel identifier.

[0100] Step 1063: At the network entry node through which the service traffic of the second network slice enters the shared resource, create a traffic forwarding rule corresponding to the independent resource channel identifier.

[0101] Step 1064: According to the traffic forwarding rules, the service traffic of the second network slice is redirected from the network ingress node to the target resource block bound to the independent resource channel identifier for transmission.

[0102] In this step, service traffic refers to the actual user data packets carried by the second network slice that need to be transmitted in the network. It is used to actually transmit through the isolation resource channel after it is established, and is obtained by monitoring the data packets belonging to the second network slice on the network entry node.

[0103] A control entity refers to a software module in a network that is responsible for managing and allocating the underlying physical resources. It is used to receive and execute resource allocation requests, such as the resource management function of the base station controller in a wireless access network, which is obtained through pre-deployment and configuration by network management.

[0104] A resource allocation request is a structured message sent to a control entity, requesting it to perform a specific resource allocation operation. It is used to trigger the control entity to actually allocate and bind the target resource block in the shared resources. It is obtained by re-encapsulating the key information in the configuration instructions into a protocol message that the control entity can recognize.

[0105] The network entry node refers to the first processing node that the service traffic of the second network slice must pass through when entering the network area where the shared resources are located. It is used as the execution point for applying traffic redirection policies and is determined through network topology discovery and traffic path tracing technology.

[0106] Traffic forwarding rules refer to one or more policy entries configured on the network ingress node, which instruct the node how to identify and process service traffic with specific characteristics. They are used to direct the identified second network slice service traffic to a specified logical channel and are obtained by configuring flow tables on the control plane of the network ingress node.

[0107] In this step, the received configuration command is first processed by a command parsing module. Following a predefined command format specification, the command header is decoded to confirm the operation type. Then, the command body is read, extracting the target resource block information list, the independent resource channel identifier string, and the second network slice identifier string. Next, the parsed target resource block information and the independent resource channel identifier are obtained through a protocol adapter, and this information is filled into a standard network resource management protocol message template, such as encapsulated as a NETCONF protocol. <edit-config>An operation request is generated, thus creating a resource allocation request. The protocol adapter then sends this message to the control entity managing the shared resources, such as a base station responsible for wireless resource scheduling, via the management network. Next, the policy configurator obtains the identifier of the second network slice and the independent resource channel identifier. Based on the network topology information, it determines the network entry node, such as a specific router or gateway, that the second network slice's service traffic must pass through to enter the shared resource domain. Then, the policy configurator issues a new traffic forwarding rule to the network entry node through its management interface, such as its command-line interface. This rule typically includes matching conditions and actions: the matching condition is set to identify the identifier in the data packet belonging to the second network slice; the action is to tag the matching data packet with the corresponding resource channel identifier, or directly output it to the underlying logical port associated with the resource channel identifier. Subsequently, when the network ingress node receives the actual data packet, its forwarding plane processes it according to the issued traffic forwarding rules. When the network ingress node identifies that the characteristics of a data packet match the identifier of the second network slice in the rules, it executes the action defined in the traffic forwarding rules, namely, marking or port redirecting the data packet. This action guides the data packet to an internal logical path associated with an independent resource channel identifier. Finally, after receiving the resource allocation request, the control entity has already bound the target resource block with the same resource channel identifier on the queue of the underlying layer, such as wireless time and frequency resources or switches. Therefore, through the association of this resource channel identifier, the data packet guided from the network ingress node is finally scheduled to be transmitted on the allocated target resource block, thus completing the routing of service traffic to the isolated resource channel.

[0108] For example, following the specific implementation of the previous step, after generating a configuration instruction containing the creation of channel Iso-Ch-Beta-001 and the allocation of resource blocks 11-34 to slice Beta, the instruction parsing module parses the configuration instruction to obtain the target resource block information 11 to 34, the independent resource channel identifier Iso-Ch-Beta-001, and the second network slice identifier Beta; then, the protocol adapter combines these three pieces of information to form a RESTful API. An API request is sent to the base station managing radio resources. Upon receiving the request, the base station marks physical resource blocks 11 through 34 in its resource pool as allocated and logically binds them to the channel identifier Iso-Ch-Beta-001, thus establishing an isolated resource channel. Next, the policy configurator determines the core network user plane gateway before traffic enters the base station as the network ingress node and creates a traffic forwarding rule on it through the network gateway's interface: matching data packets with slice ID Beta and adding the internal channel label Iso-Ch-Beta-001 to them. Then, when a real service data packet belonging to slice Beta arrives at the user plane gateway, the slice ID is identified and matched against the rule, the real service data packet is tagged with Iso-Ch-Beta-001, and forwarded to the base station. Finally, the base station receives the real service data packet with this label and schedules it to be sent on the bound physical resource blocks 11 through 34, thus achieving traffic redirection and isolated transmission.

[0109] This step transforms all decisions and instructions from the preceding steps into resource isolation states and defined traffic paths on the physical network. It completes the actual allocation and binding of resources through standard protocols, configures precise forwarding policies at the network ingress, and achieves seamless and accurate redirection of business traffic to the newly established isolated channel. This prevents predicted conflicts at the physical level, fully implements the calculated resource configuration scheme, and ultimately achieves the core objective of ensuring the performance of the second network slice services.

[0110] Figure 2 This application provides a schematic diagram of the structure of an optimized network slicing configuration system, as shown below. Figure 2 As shown, the system includes: The first acquisition module 21 is used to acquire the first service requirement data of the first network slice and the second service requirement data of the second network slice; The second acquisition module 22 is used to acquire resource occupancy status data of shared resources between the first network slice and the second network slice; The determination module 23 is used to determine the target conflict event based on the second business requirement data and the resource occupancy status data; Calculation module 24 is used to calculate resource configuration parameters based on the conflict event and the correlation between the second business requirement data and the resource occupancy status data; The generation module 25 is used to generate configuration instructions based on the resource configuration parameters; The module 26 is configured to establish an isolated resource channel in the shared resources between the first network slice and the second network slice based on the configuration instructions, so as to route the service traffic of the second network slice to the isolated resource channel for transmission.

[0111] Figure 2 The aforementioned network slicing configuration optimization system can execute Figure 1 The implementation principle and technical effects of the network slicing configuration optimization method described in the illustrated embodiment will not be repeated here. The specific methods by which each module and unit performs operations in the network slicing configuration optimization system described above have been detailed in the embodiments related to this method, and will not be elaborated upon here.

[0112] In one possible design, Figure 2 An optimization system for network slicing configuration in the illustrated embodiment can be implemented as a computing device, such as... Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32; The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are invoked and executed by the processing component 32.

[0113] The processing component 32 is used for the above Figure 1 The above embodiment describes an optimization method for network slicing configuration.

[0114] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. An optimization method for network slice configuration, characterized in that, include: Obtain the first service requirement data of the first network slice and the second service requirement data of the second network slice; Obtain resource occupancy status data of shared resources between the first network slice and the second network slice; Based on the second business requirement data and the resource occupancy status data, the target conflict event is determined; Based on the conflict events and the correlation between the second business requirement data and the resource occupancy status data, resource configuration parameters are calculated; Based on the resource configuration parameters, generate configuration instructions; Based on the configuration instructions, an isolated resource channel is established in the shared resources between the first network slice and the second network slice to route the service traffic of the second network slice to the isolated resource channel for transmission.

2. The method according to claim 1, characterized in that, Based on the second business requirement data and the resource occupancy status data, target conflict events are determined, including: Extract the service constraints of the second network slice from the second service requirement data; Extract the historical resource usage records of the first network slice on shared resources from the resource occupancy status data; Based on the historical resource usage records, predict the resource occupancy trend of the first network slice in the future time window; By combining the business constraints with the resource occupancy trend, the processing of business requests for the second network slice on the shared resources is simulated within a future time window. Based on the simulated processing procedure, determine whether the business constraints will be violated; When the determination result indicates that the business constraint will be violated, a target conflict event is determined to have occurred.

3. The method according to claim 1, characterized in that, Based on the conflict events and the correlation between the second business requirement data and the resource occupancy status data, resource configuration parameters are calculated, including: Obtain the resource requirement information of the second network slice from the second service requirement data; Obtain the occupancy rate information of the first network slice on the shared resource from the resource occupancy status data; Identify the conflict time period corresponding to the conflict event and the degree of performance degradation caused by the conflict event; Based on the resource demand information, the occupancy rate information, the conflict time period, and the performance degradation level, calculate the resource compensation amount; Based on the resource compensation amount and the total amount of shared resources, calculate the resource configuration parameters.

4. The method according to claim 3, characterized in that, Based on the resource compensation amount and the total amount of shared resources, resource configuration parameters are calculated, including: The first proportional factor is calculated based on the proportion of the resource compensation amount to the total amount of shared resources; From the resource occupancy status data, obtain the occupancy ratio of the first network slice on the shared resource, and use the occupancy ratio as the second ratio factor; Determine the reservation ratio factor based on the preset resource reservation strategy; The first proportional factor, the second proportional factor, and the reserved proportional factor are combined to generate a resource allocation coefficient. Based on the resource allocation coefficient and the total amount of shared resources, the number of resources used to establish isolated resource channels is calculated, and the number of resources is used as resource configuration parameters.

5. The method according to claim 1, characterized in that, Based on the resource configuration parameters, generate configuration instructions, including: Extract the quantity of resources to be allocated and the resource location identifiers from the resource configuration parameters; Based on the resource location identifier, determine the set of target resource blocks corresponding to the shared resource; Based on the number of resources to be allocated, a preset number of target resource blocks are selected from the set of target resource blocks; Create an independent resource channel identifier for the second network slice, and establish a mapping relationship between the independent resource channel identifier and the target resource block; Based on the mapping relationship, a configuration instruction is generated, which includes the independent resource channel identifier, the information of the target resource block, and the identifier of the second network slice.

6. The method according to claim 5, characterized in that, Based on the mapping relationship, configuration instructions are generated, including: Obtain the association information between the independent resource channel identifier and the target resource block from the mapping relationship; Based on the association information, a first instruction field and a second instruction field are generated, wherein the first instruction field contains the configuration attributes of the target resource block, and the second instruction field contains the configuration attributes of the independent resource channel identifier; The first instruction field, the second instruction field, and the identifier of the second network slice are combined to form configuration instruction data; Based on the structure of the configuration instruction data, a configuration instruction containing an instruction header and an instruction body is generated, wherein the instruction header contains an instruction type identifier and the instruction body contains the configuration instruction data.

7. The method according to claim 1, characterized in that, Based on the configuration instructions, an isolated resource channel is established in the shared resources between the first network slice and the second network slice to route the service traffic of the second network slice to the isolated resource channel for transmission, including: The configuration instructions are parsed to obtain information about the target resource block, the independent resource channel identifier, and the identifier of the second network slice; A resource allocation request is sent to the control entity that manages the shared resources, so that the control entity allocates the target resource block from the shared resources and binds the target resource block with the independent resource channel identifier to establish the isolated resource channel. The resource allocation request includes information about the target resource block and the independent resource channel identifier. At the network entry node through which the service traffic of the second network slice enters the shared resource, a traffic forwarding rule corresponding to the independent resource channel identifier is created. According to the traffic forwarding rules, the service traffic of the second network slice is redirected from the network ingress node to the target resource block bound to the independent resource channel identifier for transmission.

8. An optimization system for network slicing configuration, characterized in that, include: The first acquisition module is used to acquire the first service requirement data of the first network slice and the second service requirement data of the second network slice; The second acquisition module is used to acquire resource occupancy status data of shared resources between the first network slice and the second network slice; The determination module is used to determine the target conflict event based on the second business requirement data and the resource occupancy status data; The calculation module is used to calculate resource configuration parameters based on the conflict event and the correlation between the second business requirement data and the resource occupancy status data; The generation module is used to generate configuration instructions based on the resource configuration parameters; A module is established to establish an isolated resource channel in the shared resources between the first network slice and the second network slice based on the configuration instructions, so as to route the service traffic of the second network slice to the isolated resource channel for transmission.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement an optimization method for network slice configuration as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements an optimization method for network slice configuration as described in any one of claims 1 to 7.

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