A network resource balancing method, device, equipment, terminal and storage medium

Abstract

The application provides a network resource balancing method, device, equipment, terminal and storage medium, and relates to the technical field of wireless communication. The method comprises the following steps: acquiring network performance monitoring data of each network slice service every preset time; acquiring a to-be-optimized data set and a data set for optimization according to the network performance monitoring data and a service level agreement index label subscription value corresponding to each network slice service; matching services corresponding to the same indexes in the to-be-optimized data set and the data set for optimization, determining a target service matching pair of each index in the to-be-optimized data set; determining first information of the target service matching pair, and determining a resource balancing scheme according to the first information, wherein the first information comprises a matching degree of the target service matching pair, or the first information comprises the matching degree and a resource overlap degree of the target service matching pair. The scheme of the application can reduce network resource waste and automatically improve the SLA guarantee efficiency of network slice services.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, and in particular to a method, apparatus, device, terminal, and storage medium for network resource balancing. Background Technology

[0002] Network slicing can provide end-to-end differentiated network services through Service Level Agreements (SLAs) with operators, but it also brings problems such as the complexity of the causes of network performance degradation and the difficulty in quickly locating them. Currently, the SLA assurance method involves the Communication Service Management Function (CSMF) obtaining performance monitoring data based on the Single Network Slice Selection Assistance Information (S-NSSAI) dimension, which is determined by the slice service identifier, from the Performance Management System (PMS). When the monitoring data is lower than the service requirements in the customer's signed SLA, the SLA assurance operation is manually initiated.

[0003] like Figure 1 As shown, the initiation of existing SLA guarantees is determined and initiated manually. Adding the time for subsequent management system operations and interface interactions, the actual network performance experienced by businesses may have changed significantly before the guarantee is completed. Furthermore, declines in SLA metrics such as network latency and user experience speed are usually caused by abnormal traffic or a sharp increase in traffic. In such cases, both network resource expansion and isolation methods will lead to increased overall network resource investment and costs, easily resulting in network resource redundancy even when traffic is normal most of the time. Therefore, SLA guarantees generally suffer from reliance on manual intervention, high latency, and wasted network resources, failing to guarantee the efficiency of SLA guarantees for network slicing services. Summary of the Invention

[0004] The purpose of this invention is to provide a network resource balancing method, apparatus, device, terminal, and storage medium to solve the problems in the prior art where SLA assurance relies on manual labor, network resources are wasted, and the efficiency of SLA assurance for network slicing services cannot be guaranteed.

[0005] To achieve the above objectives, embodiments of the present invention provide a network resource balancing method, comprising:

[0006] Obtain network performance monitoring data for each network slice service at preset intervals;

[0007] Based on the network performance monitoring data and the service level agreement (SLA) metric signed for each network slice service, obtain the dataset to be optimized and the dataset used for optimization.

[0008] Match the dataset to be optimized with the services corresponding to the same indicators in the dataset used for optimization, and determine the target service matching pair for each indicator in the dataset to be optimized.

[0009] First information of the target service matching pair is determined, and a resource balancing scheme is determined based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair.

[0010] Further, the step of obtaining the dataset to be optimized and the dataset for optimization based on the network performance monitoring data and the service level agreement (SLA) metric signed for each network slice service includes:

[0011] Based on the network performance monitoring data and the service level agreement indicator (SLA) signing value corresponding to each network slice service, a first dataset and a second dataset corresponding to the current period are determined. The first dataset includes the dataset corresponding to services whose SLA indicator values ​​are worse than those of the previous period but better than those of the previous period in the network performance monitoring data. The second dataset includes the dataset corresponding to services whose SLA indicator values ​​are better than those of the previous period in the network performance monitoring data.

[0012] Determine the first target dataset for the next period corresponding to the first dataset, and determine the second target dataset for the next period corresponding to the second dataset;

[0013] The dataset to be optimized is determined based on the first target dataset, and the dataset used for optimization is determined based on the second target dataset.

[0014] Further, determining the dataset to be optimized based on the first target dataset includes:

[0015] The dataset corresponding to the business whose indicator value in the first target dataset is worse than the service level agreement indicator signing value is identified as the dataset to be optimized.

[0016] The step of determining the dataset for optimization based on the second target dataset includes:

[0017] The dataset corresponding to the services in the second target dataset that are better than the service level agreement indicator signing value is identified as the dataset used for optimization.

[0018] Further, the step of matching the dataset to be optimized with the services corresponding to the same indicators in the dataset used for optimization, and determining the target service matching pair for each indicator in the dataset to be optimized, includes:

[0019] Match the dataset to be optimized with the business corresponding to the same indicator in the dataset used for optimization to generate a business matching pair for each indicator in the dataset to be optimized.

[0020] Filter out the target business matching pairs from the business matching pairs;

[0021] The target service matching pair includes: service matching pairs in which the deviation between the dataset used for optimization and the service level agreement indicator signing value is greater than the deviation between the dataset to be optimized and the service level agreement indicator signing value.

[0022] Further, determining the first information of the target service matching pair and determining the resource balancing scheme based on the first information includes:

[0023] Calculate the resource overlap and matching degree of the target service matching pair, and use the matching degree of the target service matching pair or the resource overlap and matching degree of the target service matching pair as the first information;

[0024] A business matching scheme is obtained based on the first information;

[0025] The amount of resources that need to be adjusted is determined based on the aforementioned business matching scheme.

[0026] Further, calculating the resource overlap of the target service matching pair includes:

[0027] Based on the first network function identifier and the second network function identifier in the target service matching pair, calculate the resource overlap of the target service matching pair;

[0028] Wherein, the first network function identifier is the network function identifier corresponding to the dataset to be optimized in the matching pair, and the second network function identifier is the network function identifier corresponding to the dataset used for optimization in the matching pair.

[0029] Further, calculating the matching degree of the target service matching pair includes:

[0030] The matching degree of the target service matching pair is calculated based on the service level agreement indicator signing value, the first matching degree calculation weight, the second matching degree calculation weight, the network resource overlap of the target service matching pair, and the indicator signing values ​​corresponding to the dataset to be optimized and the dataset used for optimization in the target service matching pair.

[0031] Wherein, the service level agreement indicator signing value, the first matching degree calculation weight, and the second matching degree calculation weight are preset values. The first matching degree calculation weight is used to indicate the degree of influence of the indicator difference between the first service and the second service on the matching of resource balancing from the first service to the second service. The second matching degree calculation weight is used to indicate the degree of influence of the resource similarity of the indicators of the first service and the second service on the matching of resource balancing from the first service to the second service. The first service is the service corresponding to the dataset to be optimized, and the second service is the service corresponding to the dataset used for optimization.

[0032] Further, a business matching scheme is obtained based on the first information, including:

[0033] Filter out the first matching pair with the highest matching degree among the matching pairs of each business in the dataset to be optimized;

[0034] If there are no multiple second matching pairs in the first matching pair that match the third service with the fourth service, then the first matching pair is the service matching scheme;

[0035] If there are multiple second matching pairs in the first matching pair that match the third service with the fourth service, then the service matching scheme is determined based on at least one of the matching degree, resource overlap degree and deviation value of the second matching pair.

[0036] The third service is the service corresponding to the dataset used for optimization, and the fourth service is the service corresponding to the dataset to be optimized.

[0037] Further, determining the business matching scheme based on at least one of the matching degree, resource overlap, and deviation value of the second matching pair includes:

[0038] The matching scheme is defined as the matching pair with the highest matching degree in the second matching pair.

[0039] If there are multiple third matching pairs with the same matching degree in the second matching, then the matching pair with the highest resource overlap among the third matching pairs shall be used as the matching scheme;

[0040] If there are multiple fourth matching pairs with the same resource overlap in the third matching pair, then the matching pair with the largest target deviation value in the fourth matching pair shall be the matching scheme.

[0041] The target deviation value is the larger deviation value between the deviation values ​​of the first business indicator and the service level agreement indicator signed by the second business indicator. The first business is the business corresponding to the dataset to be optimized, and the second business is the business corresponding to the dataset used for optimization.

[0042] If there are multiple matching pairs with the same target deviation value in the fourth matching pair, then any one of the matching pairs in the fourth matching pair shall be used as the matching scheme.

[0043] Furthermore, determining the amount of resources to be adjusted based on the business matching scheme includes:

[0044] According to the matching scheme, a first target service is determined, and a balance ratio is determined based on the first target service, the balance coefficient, and the service level agreement indicator signing value of the first target service.

[0045] Based on the matching scheme and the resource balancing ratio, determine the amount of resources that need to be adjusted;

[0046] The balance coefficient is a preset value.

[0047] Furthermore, both the dataset to be optimized and the dataset used for optimization include at least one of the following:

[0048] Attribute service identifier, indicator name, indicator value, network slice instance identifier, network slice subnet instance identifier, and network element function identifier.

[0049] To achieve the above objectives, embodiments of the present invention provide a network resource balancing device, comprising:

[0050] The first acquisition module is used to acquire network performance monitoring data for each network slice service at preset intervals.

[0051] The second acquisition module is used to acquire the dataset to be optimized and the dataset for optimization based on the network performance monitoring data and the service level agreement indicator signing value corresponding to each network slice service.

[0052] The first determining module is used to match the data set to be optimized with the services corresponding to the same indicators in the data set used for optimization, and to determine the target service matching pair for each indicator in the data set to be optimized.

[0053] The second determining module is used to determine first information of the target service matching pair and determine a resource balancing scheme based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair.

[0054] To achieve the above objectives, embodiments of the present invention provide a network resource balancing device, including: a transceiver and a processor;

[0055] The transceiver is used to acquire network performance monitoring data for each network slice service at preset intervals.

[0056] Based on the network performance monitoring data and the service level agreement (SLA) metric signed for each network slice service, obtain the dataset to be optimized and the dataset used for optimization.

[0057] The processor is used to match the dataset to be optimized with the services corresponding to the same indicators in the dataset used for optimization, and to determine the target service matching pair for each indicator in the dataset to be optimized;

[0058] First information of the target service matching pair is determined, and a resource balancing scheme is determined based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair.

[0059] To achieve the above objectives, embodiments of the present invention provide a mobile terminal, including a transceiver, a processor, a memory, and a program or instructions stored in the memory and executable on the processor; when the processor executes the program or instructions, it implements the network resource balancing method described above.

[0060] To achieve the above objectives, embodiments of the present invention provide a readable storage medium having a program or instructions stored thereon, which, when executed by a processor, implement the steps in the network resource balancing method described above.

[0061] The beneficial effects of the above-described technical solution of the present invention are as follows:

[0062] The network resource balancing method of this invention obtains network performance monitoring data for each network slice service at preset time intervals and compares it with the service level agreement (SLA) indicator signing value corresponding to each network slice service to obtain a dataset to be optimized and a dataset for optimization. By matching the dataset to be optimized with services corresponding to the same indicator in the dataset for optimization to obtain target service matching pairs for each indicator in the dataset to be optimized, a resource balancing scheme can be determined based on the first information of the target service matching pairs. This invention's scheme can determine a resource balancing scheme based on the indicators of services in the dataset to be optimized and the indicators of services in the dataset for optimization, along with the SLA indicator signing value for each indicator, thereby reducing network resource waste and automatically improving the SLA guarantee efficiency of network slice services. Attached Figure Description

[0063] Figure 1 This is a flowchart illustrating existing network resource balancing methods.

[0064] Figure 2This is a flowchart illustrating the network resource balancing method according to an embodiment of the present invention.

[0065] Figure 3 This is a logical schematic diagram of the network resource balancing method according to an embodiment of the present invention;

[0066] Figure 4 This is a schematic diagram of the network resource balancing device according to an embodiment of the present invention;

[0067] Figure 5 This is a schematic diagram of the network resource balancing device according to an embodiment of the present invention;

[0068] Figure 6 This is a schematic diagram of the terminal structure according to an embodiment of the present invention. Detailed Implementation

[0069] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0070] It should be understood that the phrase "one embodiment" or "an embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of the invention. Therefore, "in one embodiment" or "in an embodiment" appearing throughout the specification do not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0071] In various embodiments of the present invention, it should be understood that the sequence number of each process described below does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0072] In addition, the terms "system" and "network" are often used interchangeably in this article.

[0073] In the embodiments provided in this application, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0074] like Figure 2 As shown, a network resource balancing method according to an embodiment of the present invention includes the following steps:

[0075] Step 201: Obtain network performance monitoring data for each network slice service at preset intervals.

[0076] Optionally, the network performance monitoring data for each network slice service includes:

[0077] PMS periodically collects network performance monitoring data for network slice services in the S-NSSAI dimension.

[0078] In one embodiment of the present invention, the network resource balancing method is executed by the Network Slice Management Function (NSMF).

[0079] Step 202: Based on the network performance monitoring data and the service level agreement indicator signing value corresponding to each network slice service, obtain the dataset to be optimized and the dataset for optimization.

[0080] Step 203: Match the dataset to be optimized with the services corresponding to the same indicators in the dataset used for optimization, and determine the target service matching pair for each indicator in the dataset to be optimized.

[0081] In one embodiment of the present invention, the matching pair of the target service can be in the form of: (service 2 in the dataset to be optimized, service 1 in the dataset to be optimized), or service 2 in the dataset to be optimized, service 5 in the dataset to be optimized.

[0082] Step 204: Determine the first information of the target service matching pair, and determine the resource balancing scheme based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair.

[0083] The network resource balancing method of this invention obtains network performance monitoring data for each network slice service at preset time intervals and compares it with the service level agreement (SLA) indicator signing value corresponding to each network slice service to obtain a dataset to be optimized and a dataset for optimization. By matching the dataset to be optimized with services corresponding to the same indicator in the dataset for optimization to obtain target service matching pairs for each indicator in the dataset to be optimized, a resource balancing scheme can be determined based on the first information of the target service matching pairs. This invention's scheme can determine a resource balancing scheme based on the indicators of services in the dataset to be optimized and the indicators of services in the dataset for optimization, along with the SLA indicator signing value for each indicator, thereby reducing network resource waste and automatically improving the SLA guarantee efficiency of network slice services.

[0084] Optionally, the step of obtaining the dataset to be optimized and the dataset for optimization based on the network performance monitoring data and the service level agreement (SLA) metric subscription value corresponding to each network slice service includes:

[0085] Based on the network performance monitoring data and the service level agreement indicator (SLA) signing value corresponding to each network slice service, a first dataset and a second dataset corresponding to the current period are determined. The first dataset includes the dataset corresponding to services whose SLA indicator values ​​are worse than those of the previous period but better than those of the previous period in the network performance monitoring data. The second dataset includes the dataset corresponding to services whose SLA indicator values ​​are better than those of the previous period in the network performance monitoring data.

[0086] Determine the first target dataset for the next period corresponding to the first dataset, and determine the second target dataset for the next period corresponding to the second dataset;

[0087] The dataset to be optimized is determined based on the first target dataset, and the dataset used for optimization is determined based on the second target dataset.

[0088] It should be noted that a value worse than the previous period can be understood as the performance of the service corresponding to the value of the value decreasing compared to the previous period; a value better than the previous period can be understood as the performance of the service corresponding to the value increasing compared to the previous period.

[0089] In one embodiment of the present invention, regarding latency, if the index value increases compared to the previous period, then the index value is worse than the previous period; regarding transmission rate, if the index value decreases compared to the previous period, then the index value is worse than the previous period.

[0090] Optionally, determining the first target dataset for the next period corresponding to the first dataset includes:

[0091] Based on the first dataset, the first target dataset corresponding to the first dataset in the next period is calculated using a time-series prediction method.

[0092] Optionally, determining the second target dataset for the next period corresponding to the second dataset includes:

[0093] Based on the second dataset, the second target dataset corresponding to the second dataset in the next period is calculated using a time-series prediction method.

[0094] The network resource balancing method of this invention predicts the corresponding first target dataset and second target dataset for the next period using the first dataset and second dataset of the current period. It can balance network resources in the next period based on the data of the next period, compensate for the time required for service matching and resource balancing, and ensure the timeliness and accuracy of SLA guarantee.

[0095] Optionally, determining the dataset to be optimized based on the first target dataset includes:

[0096] The dataset corresponding to the business whose indicator value in the first target dataset is worse than the service level agreement indicator signing value is identified as the dataset to be optimized.

[0097] The step of determining the dataset for optimization based on the second target dataset includes:

[0098] The dataset corresponding to the services in the second target dataset that are better than the service level agreement indicator signing value is identified as the dataset used for optimization.

[0099] The network resource balancing method of this invention filters out degraded indicator values ​​in the first target dataset and optimizes indicator values ​​in the second target dataset, thereby updating the dataset corresponding to the indicator values ​​in the next cycle. By updating the indicator values, the network is resource-balanced in the next cycle, ensuring the accuracy of SLA guarantee.

[0100] Optionally, the step of matching the dataset to be optimized with the services corresponding to the same indicators in the dataset used for optimization, and determining the target service matching pair for each indicator in the dataset to be optimized, includes:

[0101] Match the dataset to be optimized with the business corresponding to the same indicator in the dataset used for optimization to generate a business matching pair for each indicator in the dataset to be optimized.

[0102] Filter out the target business matching pairs from the business matching pairs;

[0103] The target service matching pair includes: service matching pairs in which the deviation between the dataset used for optimization and the service level agreement indicator signing value is greater than the deviation between the dataset to be optimized and the service level agreement indicator signing value.

[0104] In one embodiment of the present invention, the business matching pair satisfies the condition: |Indicator value of the dataset used for optimization - SLA contract value of the corresponding indicator|>|Indicator value of the dataset to be optimized - SLA contract value of the corresponding indicator|.

[0105] The network resource balancing method of this invention obtains the target service matching pair by filtering the service matching pairs, which enables the dataset used for optimization in the target service matching pair to have sufficient resources to balance the dataset to be optimized in the target service matching pair, thereby improving the success probability of resource balancing.

[0106] Optionally, determining the first information of the target service matching pair and determining the resource balancing scheme based on the first information includes:

[0107] Calculate the resource overlap and matching degree of the target service matching pair, and use the matching degree of the target service matching pair or the resource overlap and matching degree of the target service matching pair as the first information;

[0108] A business matching scheme is obtained based on the first information;

[0109] The amount of resources that need to be adjusted is determined based on the aforementioned business matching scheme.

[0110] Optionally, calculating the resource overlap of the target service matching pair includes:

[0111] Based on the first network function identifier and the second network function identifier in the target service matching pair, calculate the resource overlap of the target service matching pair;

[0112] Wherein, the first network function identifier is the network function identifier corresponding to the dataset to be optimized in the matching pair, and the second network function identifier is the network function identifier corresponding to the dataset used for optimization in the matching pair.

[0113] In one embodiment of the present invention, the resource overlap of the target service matching pair is equal to the number of network function identifiers that are the same in the first network function identifier and the second network function identifier, divided by the number of the first network function identifiers.

[0114] The network resource balancing method of this invention calculates the resource overlap of the target service matching pairs and selects matching pairs with higher resource overlap for network resource balancing.

[0115] Optionally, calculating the matching degree of the target service matching pair includes:

[0116] The matching degree of the target service matching pair is calculated based on the service level agreement indicator signing value, the first matching degree calculation weight, the second matching degree calculation weight, the network resource overlap of the target service matching pair, and the indicator signing values ​​corresponding to the dataset to be optimized and the dataset used for optimization in the target service matching pair.

[0117] Wherein, the service level agreement indicator signing value, the first matching degree calculation weight, and the second matching degree calculation weight are preset values. The first matching degree calculation weight is used to indicate the degree of influence of the indicator difference between the first service and the second service on the matching of resource balancing from the first service to the second service. The second matching degree calculation weight is used to indicate the degree of influence of the resource similarity of the indicators of the first service and the second service on the matching of resource balancing from the first service to the second service. The first service is the service corresponding to the dataset to be optimized, and the second service is the service corresponding to the dataset used for optimization.

[0118] In one embodiment of the present invention, the matching degree = first matching degree calculation weight * deviation between the deviation of the indicator and the contract value in the dataset to be optimized and the deviation between the indicator and the contract value in the dataset used for optimization + second matching degree calculation weight * (network resource overlap between the service corresponding to the dataset to be optimized and the service corresponding to the dataset used for optimization in the target service matching pair).

[0119] = First matching degree calculation weight * ||Indicator-SLA contract value in the dataset used for optimization| - ||Indicator-SLA contract value in the dataset to be optimized|| / |Indicator-SLA contract value in the dataset to be optimized| + Second matching degree calculation weight * Number of Network Function IDs (NFIDs) that are the same as the services in the dataset to be optimized and the services in the dataset used for optimization / Total number of NFIDs of the services in the dataset to be optimized.

[0120] Optionally, a business matching scheme is obtained based on the first information, including:

[0121] Filter out the first matching pair with the highest matching degree among the matching pairs of each business in the dataset to be optimized;

[0122] If there are no multiple second matching pairs in the first matching pair that match the third service with the fourth service, then the first matching pair is the service matching scheme;

[0123] If there are multiple second matching pairs in the first matching pair that match the third service with the fourth service, then the service matching scheme is determined based on at least one of the matching degree, resource overlap degree and deviation value of the second matching pair.

[0124] The third service is the service corresponding to the dataset used for optimization, and the fourth service is the service corresponding to the dataset to be optimized.

[0125] In one embodiment of the present invention, for the same indicator corresponding to the business in the dataset to be optimized, the matching pair with the highest matching degree is selected as the business matching scheme.

[0126] In one embodiment of the present invention, for service 1 of the dataset to be optimized, there are no multiple second matching pairs in the first matching pairs that match the third service and the fourth service. There are no two matching pairs (service 1 of the dataset to be optimized, service 3 of the dataset used for optimization) and (service 1 of the dataset to be optimized, service 5 of the dataset used for optimization). If the former has a higher matching degree than the latter, then the former is the matching scheme.

[0127] Optionally, determining the business matching scheme based on at least one of the matching degree, resource overlap, and deviation value of the second matching pair includes:

[0128] The matching scheme is defined as the matching pair with the highest matching degree in the second matching pair.

[0129] If there are multiple third matching pairs with the same matching degree in the second matching, then the matching pair with the highest resource overlap among the third matching pairs shall be used as the matching scheme;

[0130] If there are multiple fourth matching pairs with the same resource overlap in the third matching pair, then the matching pair with the largest target deviation value in the fourth matching pair shall be the matching scheme.

[0131] The target deviation value is the larger deviation value between the deviation values ​​of the first business indicator and the service level agreement indicator signed by the second business indicator. The first business is the business corresponding to the dataset to be optimized, and the second business is the business corresponding to the dataset used for optimization.

[0132] If there are multiple matching pairs with the same target deviation value in the fourth matching pair, then any one of the matching pairs in the fourth matching pair shall be used as the matching scheme.

[0133] If, for service 1 of the dataset to be optimized, there are multiple second matching pairs in the first matching pair that match service 1, such as (service 1 of the dataset to be optimized, service 3 of the dataset used for optimization) and (service 2 of the dataset to be optimized, service 3 of the dataset used for optimization), then the matching pair with the higher matching degree is the matching scheme. If the matching degree of the two matching pairs is the same, then the network resource overlap of the two matching pairs is calculated, and the matching pair with the higher network resource overlap is the matching scheme. If both the matching degree and the network resource overlap of the two matching pairs are the same, then the matching pair with the larger target deviation value is the matching service.

[0134] Optionally, determining the amount of resources to be adjusted based on the service matching scheme includes:

[0135] According to the matching scheme, a first target service is determined, and a balance ratio is determined based on the first target service, the balance coefficient, and the service level agreement indicator signing value of the first target service.

[0136] Based on the matching scheme and the resource balancing ratio, determine the amount of resources that need to be adjusted;

[0137] The balance coefficient is a preset value.

[0138] Optionally, the balance ratio = balance coefficient * |data set indicator value used for optimization - SLA indicator contract value| / SLA indicator contract value.

[0139] In one embodiment of the present invention, the indicator is latency. When the balancing ratio is ≤0.2, the service in the data set used for optimization balances 1 UPF to the centralized service of the data set to be optimized, while simultaneously loading the traffic of the indicator optimization service and the indicator degradation service; when 0.2≤balancing ratio≤0.5, 2 UPFs are balanced; when the balancing ratio is ≥0.5, 3 UPFs are balanced.

[0140] Optionally, both the dataset to be optimized and the dataset used for optimization include at least one of the following:

[0141] Attribute service identifier, indicator name, indicator value, network slice instance identifier, network slice subnet instance identifier, and network element function identifier.

[0142] like Figure 3 As shown, the network resource balancing method of Embodiment 1 of the present invention is as follows:

[0143] The following data is pre-configured on the NSMF side: the resources and configuration strategies associated with each SLA indicator. For example, for the latency indicator, the corresponding resources to be adjusted are the number of horizontal core network user plane UPF network elements, the balance coefficient of each SLA indicator, the weight for calculating the first matching degree, and the weight for calculating the second matching degree.

[0144] NSMF obtains periodic network performance monitoring data for network slice services in the S-NSSAI dimension from PMS;

[0145] At each preset time interval, the difference between the acquired network performance monitoring data and the SLA contract data is calculated. The data sets of deterioration indicators that have declined compared to the previous time interval but are still better than the contract value are selected as the first dataset (dataset 1 corresponding to time 1, as shown in column A of Table 1) and the data sets of optimization indicators that have increased compared to the previous time interval are selected as the second dataset (dataset 2 corresponding to time 1, as shown in column B of Table 1). The dataset format includes the S-NSSAI identifier, indicator name, indicator value, Network Slice Instance (NSI) identifier, Network Slice Subnet Instance (NSSI) identifier, and Network Element Function (Network) identifier. An array of objects identified by function (NF); in one embodiment of the present invention, the format of the dataset can be: [{S-NSSAI:ns-1,indicator:[{name:lantency,value:10}],nsiId:nsi-1,nssiId:[nssi1,nssi2,nssi3],nfId:[nf1,nf2,nf3,nf4,nf5...]},...];

[0146] Table 1

[0147]

[0148] For the services in the first dataset and the second dataset, the time series prediction method is used to predict the first target dataset corresponding to the first dataset and the second target dataset corresponding to the second dataset at the next time (time 2); and the dataset corresponding to the service level agreement indicator in the first target dataset with an indicator value lower than the service level agreement indicator signing value is determined as the third dataset (dataset 3 corresponding to time 2, as shown in column C of Table 1), and the dataset corresponding to the service level agreement indicator in the second target dataset with an indicator value higher than the service level agreement indicator signing value is determined as the fourth dataset (dataset 4 corresponding to time 2, as shown in column D of Table 1).

[0149] For the same indicators in the third dataset and the fourth dataset, perform a full match on the corresponding services in the order of (third dataset service, fourth dataset service) to generate service matching pairs for each indicator, and filter out the target matching pairs that meet the condition |fourth dataset service indicator value - SLA contract value| > |third dataset service indicator value - SLA contract value|. It should be noted that if the indicator value is not a numerical value but an enumerated value, it is pre-converted into numerical values ​​1, 2, 3... according to the meaning of the indicator value represented by the enumerated value.

[0150] If there are no multiple second matching pairs in the first matching pair that match the third service with the fourth service, then the first matching pair is the service matching scheme; for example, for service 1, the calculated matching degree from high to low is (1,3) and (1,5), and for service 2, the calculated matching degree from high to low is (2,3) and (2,5), then (1,3) is selected first as the matching scheme for service 1.

[0151] If there are multiple second matching pairs in the first matching pair that match the third service and the fourth service, the matching pair with the highest matching degree in the second matching pair shall be the matching scheme; for example, for the indicator latency, (1,3) and (2,3) are both the highest matching values ​​in the matching pair ranking of services 1 and 2, then the matching values ​​of (1,3) and (2,3) are compared to determine whether service 3 should balance resources and configuration for service 1 or service 2 in terms of latency indicator;

[0152] If there are multiple third matching pairs with the same matching degree in the second matching, then the matching pair with the highest resource overlap among the third matching pairs shall be the matching scheme; for example, if the matching values ​​of (1,3) and (2,3) are exactly the same, the network resource overlap between service 1 and service 3 and the network resource overlap between service 2 and service 3 shall be compared.

[0153] If there are multiple fourth matching pairs with the same resource overlap in the third matching pair, then the matching pair with the largest target deviation value in the fourth matching pair shall be the matching scheme; for example, if the network resource overlap of (1,3) and the network resource overlap of (2,3) are exactly the same, compare the deviation between the deviation of the service 1 indicator value and the SLA contract value and the deviation between the service 3 indicator value and the SLA contract value, and compare the deviation between the deviation of the service 2 indicator value and the SLA contract value and the deviation between the service 3 indicator value and the SLA contract value.

[0154] According to the matching scheme, calculate the proportion (balancing ratio) of network resources and configurations for the optimized data-centralized service to the data-centralized service to be optimized in each service matching scheme. Combine the preset SLA index with the strategy of resource and configuration adjustment to determine the resources and configurations to be changed for the optimized data-centralized service and the data-centralized service to be optimized respectively.

[0155] like Figure 4 As shown, this embodiment of the invention also provides a network resource balancing device, comprising:

[0156] The first acquisition module 401 is used to acquire network performance monitoring data of each network slice service at preset intervals;

[0157] The second acquisition module 402 is used to acquire the dataset to be optimized and the dataset for optimization based on the network performance monitoring data and the service level agreement indicator signing value corresponding to each network slice service.

[0158] The first determining module 403 is used to match the data set to be optimized with the services corresponding to the same indicators in the data set used for optimization, and to determine the target service matching pair for each indicator in the data set to be optimized.

[0159] The second determining module 404 is used to determine the first information of the target service matching pair and determine the resource balancing scheme based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair.

[0160] The network resource balancing device of this invention acquires network performance monitoring data for each network slice service at preset intervals and compares it with the service level agreement (SLA) indicator subscription value corresponding to each network slice service to obtain a dataset to be optimized and a dataset for optimization. By matching the dataset to be optimized with services corresponding to the same indicator in the dataset for optimization to obtain target service matching pairs for each indicator in the dataset to be optimized, a resource balancing scheme can be determined based on the first information of the target service matching pairs. The solution of this invention can determine a resource balancing scheme based on the indicators of services in the dataset to be optimized and the indicators of services in the dataset for optimization, along with the SLA indicator subscription value of each indicator, thereby reducing network resource waste and automatically improving the SLA guarantee efficiency of network slice services.

[0161] like Figure 5 As shown, a network resource balancing device 500 according to an embodiment of the present invention includes a processor 510 and a transceiver 520, wherein,

[0162] The transceiver is used to acquire network performance monitoring data for each network slice service at preset intervals.

[0163] Based on the network performance monitoring data and the service level agreement (SLA) metric signed for each network slice service, obtain the dataset to be optimized and the dataset used for optimization.

[0164] The processor is used to match the data set to be optimized with the services corresponding to the same indicators in the data set used for optimization, and to determine the target service matching pair for each indicator in the data set to be optimized;

[0165] First information of the target service matching pair is determined, and a resource balancing scheme is determined based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair.

[0166] The network resource balancing device of this invention obtains network performance monitoring data for each network slice service at preset intervals and compares it with the service level agreement (SLA) indicator subscription value corresponding to each network slice service to obtain a dataset to be optimized and a dataset for optimization. By matching the dataset to be optimized with services corresponding to the same indicator in the dataset for optimization to obtain target service matching pairs for each indicator in the dataset to be optimized, a resource balancing scheme can be determined based on the first information of the target service matching pairs. The solution of this invention can determine a resource balancing scheme based on the indicators of services in the dataset to be optimized and the indicators of services in the dataset for optimization, along with the SLA indicator subscription value of each indicator, thereby reducing network resource waste and automatically improving the SLA guarantee efficiency of network slice services.

[0167] Another embodiment of the present invention includes a terminal, such as Figure 6 As shown, it includes a transceiver 610, a processor 600, a memory 620, and a program or instructions stored in the memory 620 and executable on the processor 600; when the processor 600 executes the program or instructions, it implements the above-mentioned method for network resource balancing.

[0168] The transceiver 610 is used to receive and send data under the control of the processor 600.

[0169] Among them, Figure 6 In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 600 and memory represented by memory 620 together. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. Transceiver 610 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. For different user equipment, user interface 630 can also be an interface capable of connecting external or internal devices, including but not limited to keypads, displays, speakers, microphones, joysticks, etc.

[0170] The processor 600 is responsible for managing the bus architecture and general processing, while the memory 620 can store the data used by the processor 600 when performing operations.

[0171] An embodiment of the present invention provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the steps in the network resource balancing method described above and achieve the same technical effect. To avoid repetition, further details are omitted here.

[0172] The processor mentioned above is the processor in the terminal described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0173] It should be further noted that the terminals described in this specification include, but are not limited to, smartphones, tablets, etc., and many of the functional components described are referred to as modules in order to emphasize the independence of their implementation.

[0174] In this embodiment of the invention, the module can be implemented in software so that it can be executed by various types of processors. For example, an identified executable code module may include one or more physical or logical blocks of computer instructions, which may be constructed as objects, procedures, or functions. Nevertheless, the executable code of the identified module does not need to be physically located together, but may include different instructions stored in different bits, which, when logically combined, constitute the module and achieve the module's intended purpose.

[0175] In practice, an executable code module can be a single instruction or many instructions, and can even be distributed across multiple different code segments, different programs, and across multiple memory devices. Similarly, operational data can be identified within the module and can be implemented in any suitable form and organized within any suitable type of data structure. This operational data can be collected as a single dataset or distributed across different locations (including different storage devices), and can exist, at least in part, solely as electronic signals within the system or network.

[0176] When a module can be implemented using software, considering the current level of hardware technology, modules that can be implemented in software can be implemented using hardware circuits by those skilled in the art to achieve the corresponding functions, without considering cost. These hardware circuits include conventional very-large-scale integrated circuits (VLSI) or gate arrays, as well as existing semiconductors such as logic chips and transistors, or other discrete components. Modules can also be implemented using programmable hardware devices, such as field-programmable gate arrays, programmable array logic, and programmable logic devices.

[0177] The exemplary embodiments described above are with reference to the accompanying drawings. Many different forms and embodiments are feasible without departing from the spirit and teachings of the invention. Therefore, the invention should not be construed as limiting the exemplary embodiments set forth herein. Rather, these exemplary embodiments are provided to make the invention complete and convey the scope of the invention to those skilled in the art. In these drawings, component dimensions and relative dimensions may be exaggerated for clarity. The terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. As used herein, unless clearly indicated otherwise, the singular forms “a,” “an,” and “the” are intended to include all such forms. It will be further understood that the terms “comprising” and / or “including”, when used in this specification, indicate the presence of the stated features, integers, steps, operations, components, and / or elements, but do not exclude the presence or addition of one or more other features, integers, steps, operations, components, and / or groups thereof. Unless otherwise indicated, when stated, a range of values ​​includes the upper and lower limits of the range and any subranges in between.

[0178] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for balancing network resources, characterized in that, include: Obtain network performance monitoring data for each network slice service at preset intervals; Based on the network performance monitoring data and the service level agreement (SLA) metric signed for each network slice service, obtain the dataset to be optimized and the dataset used for optimization. Match the dataset to be optimized with the services corresponding to the same indicators in the dataset used for optimization, and determine the target service matching pair for each indicator in the dataset to be optimized. First information of the target service matching pair is determined, and a resource balancing scheme is determined based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair. The step of obtaining the dataset to be optimized and the dataset for optimization based on the network performance monitoring data and the service level agreement (SLA) metric signed for each network slice service includes: Based on the network performance monitoring data and the service level agreement indicator (SLA) signing value corresponding to each network slice service, a first dataset and a second dataset corresponding to the current period are determined. The first dataset includes the dataset corresponding to services whose SLA indicator values ​​are worse than those of the previous period but better than those of the previous period in the network performance monitoring data. The second dataset includes the dataset corresponding to services whose SLA indicator values ​​are better than those of the previous period in the network performance monitoring data. Determine the first target dataset for the next period corresponding to the first dataset, and determine the second target dataset for the next period corresponding to the second dataset; The dataset to be optimized is determined based on the first target dataset, and the dataset used for optimization is determined based on the second target dataset.

2. The network resource balancing method according to claim 1, characterized in that, The step of determining the dataset to be optimized based on the first target dataset includes: The dataset corresponding to the business whose indicator value in the first target dataset is worse than the service level agreement indicator signing value is identified as the dataset to be optimized. The step of determining the dataset for optimization based on the second target dataset includes: The dataset corresponding to the services in the second target dataset that are better than the service level agreement indicator signing value is identified as the dataset used for optimization.

3. The network resource balancing method according to claim 1, characterized in that, The step of matching the dataset to be optimized with the services corresponding to the same indicators in the dataset used for optimization, and determining the target service matching pair for each indicator in the dataset to be optimized, includes: Match the dataset to be optimized with the business corresponding to the same indicator in the dataset used for optimization to generate a business matching pair for each indicator in the dataset to be optimized. Filter out the target business matching pairs from the business matching pairs; The target service matching pair includes: service matching pairs in which the deviation between the dataset used for optimization and the service level agreement indicator signing value is greater than the deviation between the dataset to be optimized and the service level agreement indicator signing value.

4. The network resource balancing method according to claim 1, characterized in that, The step of determining the first information of the target service matching pair and determining the resource balancing scheme based on the first information includes: Calculate the resource overlap and matching degree of the target service matching pair, and use the matching degree of the target service matching pair or the resource overlap and matching degree of the target service matching pair as the first information; A business matching scheme is obtained based on the first information; The amount of resources that need to be adjusted is determined based on the aforementioned business matching scheme.

5. The network resource balancing method according to claim 4, characterized in that, The calculation of the resource overlap of the target service matching pair includes: Based on the first network function identifier and the second network function identifier in the target service matching pair, calculate the resource overlap of the target service matching pair; Wherein, the first network function identifier is the network function identifier corresponding to the dataset to be optimized in the matching pair, and the second network function identifier is the network function identifier corresponding to the dataset used for optimization in the matching pair.

6. The network resource balancing method according to claim 4, characterized in that, The calculation of the matching degree of the target service matching pair includes: The matching degree of the target service matching pair is calculated based on the service level agreement indicator signing value, the first matching degree calculation weight, the second matching degree calculation weight, the network resource overlap of the target service matching pair, and the indicator signing values ​​corresponding to the dataset to be optimized and the dataset used for optimization in the target service matching pair. Wherein, the service level agreement indicator signing value, the first matching degree calculation weight, and the second matching degree calculation weight are preset values. The first matching degree calculation weight is used to indicate the degree of influence of the indicator difference between the first service and the second service on the matching of resource balancing from the first service to the second service. The second matching degree calculation weight is used to indicate the degree of influence of the resource similarity of the indicators of the first service and the second service on the matching of resource balancing from the first service to the second service. The first service is the service corresponding to the dataset to be optimized, and the second service is the service corresponding to the dataset used for optimization.

7. The network resource balancing method according to claim 4, characterized in that, Based on the first information, a business matching scheme is obtained, including: Filter out the first matching pair with the highest matching degree among the matching pairs of each business in the dataset to be optimized; If there are no multiple second matching pairs in the first matching pair that match the third service with the fourth service, then the first matching pair is the service matching scheme; If there are multiple second matching pairs in the first matching pair that match the third service with the fourth service, then the service matching scheme is determined based on at least one of the matching degree, resource overlap degree and deviation value of the second matching pair. The third service is the service corresponding to the dataset used for optimization, and the fourth service is the service corresponding to the dataset to be optimized.

8. The network resource balancing method according to claim 7, characterized in that, The step of determining the business matching scheme based on at least one of the matching degree, resource overlap, and deviation value of the second matching pair includes: The matching scheme is defined as the matching pair with the highest matching degree in the second matching pair. If there are multiple third matching pairs with the same matching degree in the second matching, then the matching pair with the highest resource overlap among the third matching pairs shall be used as the matching scheme; If there are multiple fourth matching pairs with the same resource overlap in the third matching pair, then the matching pair with the largest target deviation value in the fourth matching pair shall be the matching scheme. The target deviation value is the larger deviation value between the deviation values ​​of the first business indicator and the service level agreement indicator signed by the second business indicator. The first business is the business corresponding to the dataset to be optimized, and the second business is the business corresponding to the dataset used for optimization. If there are multiple matching pairs with the same target deviation value in the fourth matching pair, then any one of the matching pairs in the fourth matching pair shall be used as the matching scheme.

9. The network resource balancing method according to claim 4, characterized in that, The step of determining the amount of resources that need to be adjusted according to the business matching scheme includes: According to the matching scheme, a first target service is determined, and a balance ratio is determined based on the first target service, the balance coefficient, and the service level agreement indicator signing value of the first target service. Based on the matching scheme and the resource balancing ratio, determine the amount of resources that need to be adjusted; The balance coefficient is a preset value.

10. The network resource balancing method according to claim 1, characterized in that, Both the dataset to be optimized and the dataset used for optimization include at least one of the following: Attribute service identifier, indicator name, indicator value, network slice instance identifier, network slice subnet instance identifier, and network element function identifier.

11. A network resource balancing device, characterized in that, include: The first acquisition module is used to acquire network performance monitoring data for each network slice service at preset intervals. The second acquisition module is used to acquire the dataset to be optimized and the dataset for optimization based on the network performance monitoring data and the service level agreement indicator signing value corresponding to each network slice service. The first determining module is used to match the data set to be optimized with the services corresponding to the same indicators in the data set used for optimization, and to determine the target service matching pair for each indicator in the data set to be optimized. The second determining module is used to determine the first information of the target service matching pair and determine the resource balancing scheme based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair. The second acquisition module is further configured to: Based on the network performance monitoring data and the service level agreement indicator (SLA) signing value corresponding to each network slice service, a first dataset and a second dataset corresponding to the current period are determined. The first dataset includes the dataset corresponding to services whose SLA indicator values ​​are worse than those of the previous period but better than those of the previous period in the network performance monitoring data. The second dataset includes the dataset corresponding to services whose SLA indicator values ​​are better than those of the previous period in the network performance monitoring data. Determine the first target dataset for the next period corresponding to the first dataset, and determine the second target dataset for the next period corresponding to the second dataset; The dataset to be optimized is determined based on the first target dataset, and the dataset used for optimization is determined based on the second target dataset.

12. A network resource balancing device, characterized in that, include: Transceiver and processor; The transceiver is used to acquire network performance monitoring data for each network slice service at preset intervals. Based on the network performance monitoring data and the service level agreement (SLA) metric signed for each network slice service, obtain the dataset to be optimized and the dataset used for optimization. The processor is used to match the data set to be optimized with the services corresponding to the same indicators in the data set used for optimization, and to determine the target service matching pair for each indicator in the data set to be optimized; First information of the target service matching pair is determined, and a resource balancing scheme is determined based on the first information. The first information includes the matching degree of the target service matching pair, or the first information includes the matching degree and resource overlap of the target service matching pair. The transceiver is also used for: Based on the network performance monitoring data and the service level agreement indicator (SLA) signing value corresponding to each network slice service, a first dataset and a second dataset corresponding to the current period are determined. The first dataset includes the dataset corresponding to services whose SLA indicator values ​​are worse than those of the previous period but better than those of the previous period in the network performance monitoring data. The second dataset includes the dataset corresponding to services whose SLA indicator values ​​are better than those of the previous period in the network performance monitoring data. Determine the first target dataset for the next period corresponding to the first dataset, and determine the second target dataset for the next period corresponding to the second dataset; The dataset to be optimized is determined based on the first target dataset, and the dataset used for optimization is determined based on the second target dataset.

13. A terminal, comprising: A transceiver, a processor, a memory, and a program or instructions stored in the memory and executable on the processor; characterized in that, when the processor executes the program or instructions, it implements the network resource balancing method as described in any one of claims 1-10.

14. A readable storage medium having a program or instructions stored thereon, characterized in that, When the program or instructions are executed by the processor, they implement the steps in the network resource balancing method as described in any one of claims 1-10.

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