Slice management methods, devices, electronic equipment, storage media and computer program products

Abstract

The application discloses a slice management method and device, electronic equipment, a storage medium and a computer program product. The method comprises: determining a slice management operation to be executed for a first slice instance set, the first slice instance set containing N candidate slice instances running in a current system, N being an integer greater than 1; determining a first weight set of the first slice instance set by using M performance indexes based on an analytic hierarchy process, M being an integer greater than 1, one performance index representing at least one of service quality (QoS) of one candidate slice instance, one system resource occupied, and demand level, the first weight set containing N first weights, one first weight representing the influence degree of one candidate slice instance on the running state of the system; and determining whether to execute the slice management operation to be executed based on the first weight set.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of network slicing, and particularly relates to a slice management method and device, an electronic device, a storage medium and a computer program product. BACKGROUND

[0002] As a new type of network architecture, network slicing (which can also be referred to simply as slicing) is a key enabling technology for network intelligence, and can provide multiple logically independent networks on a shared underlying network infrastructure. Therefore, slicing can be used to provide specific and mutually isolated network capabilities for users, and has the feature of customizable functions, and has been widely used in many vertical industries.

[0003] However, there is no effective solution in the related art for how to realize automatic management of slicing according to the objective status of the network without increasing the operating burden of the network. SUMMARY

[0004] To solve the problems in the related art, the present application provides a slice management method and device, an electronic device, a storage medium and a computer program product.

[0005] The technical scheme of the present application embodiment is implemented as follows:

[0006] The present application embodiment provides a slice management method, comprising:

[0007] For a first slice instance set, determining a slice management operation to be executed, the first slice instance set containing N candidate slice instances running in a current system, N being an integer greater than 1;

[0008] Based on the analytic hierarchy process, a first weight set of the first slice instance set is determined using M performance indicators, M being an integer greater than 1, one performance indicator representing at least one of a quality of service (QoS) of one candidate slice instance, a system resource occupied, and a demand level, the first weight set containing N first weights, one first weight representing the degree of influence of one candidate slice instance on the running state of the system;

[0009] Based on the first weight set, it is determined whether to execute the slice management operation to be executed.

[0010] In the above scheme, the first weight set of the first slice instance set is determined using M performance indicators based on the analytic hierarchy process, comprising:

[0011] Determine a second weight set and N third weight sets for the first slice instance set. The second weight set contains M second weights, and each second weight represents the degree of influence of a performance indicator on a target slice instance. The target slice instance includes the candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set. A third weight set is associated with a candidate slice instance, and a third weight set contains M third weights. Each third weight represents the degree of influence of a candidate slice instance on a performance indicator.

[0012] The first weight set is determined based on the second weight set and N third weight sets.

[0013] In the above scheme, determining the first weight set based on the second weight set and N third weight sets includes:

[0014] Determine the first judgment matrix corresponding to the second weight set, and based on the N third weight sets, determine M second judgment matrices, with each second judgment matrix associated with a performance index;

[0015] The first weight set is determined based on the first judgment matrix and M second judgment matrices.

[0016] In the above scheme, determining whether to execute the slice management operation to be executed based on the first weight set includes:

[0017] If the maximum value among the N first weights contained in the first weight set is not equal to 0, the candidate slice instance corresponding to the maximum value is determined as the target slice instance. The target slice instance includes the candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set.

[0018] For the target slice instance, perform the slice management operation to be performed.

[0019] In the above scheme, the step of performing the slice management operation to be performed on the target slice instance includes:

[0020] In the case that multiple target slice instances are identified, first information and second information are obtained. The first information is used to indicate a second slice instance set, which contains multiple slice instances and can reflect user preferences associated with the system. The second information is used to indicate slice instances that the user has selected from the second slice instance set.

[0021] If the plurality of target slice instances are a subset of the second slice instance set, and the plurality of target slice instances include the slice instance indicated by the second information, the slice management operation to be performed is executed for the slice instance indicated by the second information.

[0022] In the above scheme, the step of performing the slice management operation to be performed on the target slice instance includes:

[0023] In the case that multiple target slice instances are identified, first information and second information are obtained. The first information is used to indicate a second slice instance set, which contains multiple slice instances and can reflect user preferences associated with the system. The second information is used to indicate slice instances that the user has selected from the second slice instance set.

[0024] If the plurality of target slice instances are a subset of the second slice instance set and the plurality of target slice instances do not include the slice instance indicated by the second information, or if the plurality of target slice instances are not a subset of the second slice instance set, third information is obtained, the third information being used to indicate the slice instance selected from the plurality of target slice instances.

[0025] For the slice instance indicated by the third information, perform the slice management operation to be performed.

[0026] In the above scheme, determining whether to execute the slice management operation to be executed based on the first weight set includes:

[0027] If the maximum value among the N first weights contained in the first weight set is equal to 0, the slice management operation to be executed will not be performed.

[0028] In the above scheme, determining the slice management operation to be performed for the first slice instance set includes:

[0029] Based on the operating status of the system, the slice management operation to be executed is determined. The operating status of the system includes at least the system load status. The slice management operation to be executed includes a service degradation operation or a service upgrade operation.

[0030] This application also provides a slice management device, including:

[0031] The first processing unit is used to determine the slice management operation to be executed for the first slice instance set, wherein the first slice instance set contains N candidate slice instances running in the current system, where N is an integer greater than 1.

[0032] The second processing unit is used to determine the first weight set of the first slice instance set based on the analytic hierarchy process and using M performance indicators, where M is an integer greater than 1. A performance indicator represents at least one of the following: a QoS of a candidate slice instance, a system resource occupied, and a demand level. The first weight set contains N first weights, and a first weight represents the degree of influence of a candidate slice instance on the operating state of the system.

[0033] The third processing unit is used to determine, based on the first weight set, whether to execute the slice management operation to be executed.

[0034] This application also provides an electronic device, including: a communication interface and a processor; wherein,

[0035] The processor is used for:

[0036] For the first slice instance set, determine the slice management operation to be executed. The first slice instance set contains N candidate slice instances running in the current system, where N is an integer greater than 1.

[0037] Based on the analytic hierarchy process, a first weight set of the first slice instance set is determined using M performance indicators, where M is an integer greater than 1. Each performance indicator represents at least one of the following: a QoS of a candidate slice instance, a system resource it occupies, and a demand level. The first weight set contains N first weights, and each first weight represents the degree of influence of a candidate slice instance on the operating state of the system.

[0038] Based on the first weight set, determine whether to execute the slice management operation to be executed.

[0039] This application also provides an electronic device, including: a processor and a memory for storing a computer program capable of running on the processor.

[0040] When the processor runs the computer program, it executes the steps of any of the above methods.

[0041] This application also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of any of the above methods.

[0042] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the above methods.

[0043] The slice management method, apparatus, electronic device, storage medium, and computer program product provided in this application, for a first slice instance set, determine the slice management operation to be executed. The first slice instance set contains N candidate slice instances running in the current system, where N is an integer greater than 1. Based on the analytic hierarchy process (AHP), using M performance indicators, determine a first weight set for the first slice instance set, where M is an integer greater than 1. Each performance indicator represents at least one of the following: a QoS of a candidate slice instance, a system resource it occupies, and a demand level. The first weight set contains N first weights, where each first weight represents the degree of influence of a candidate slice instance on the operating state of the system. Based on the first weight set, determine whether to execute the slice management operation to be executed. The solution provided in this application, for N candidate slice instances (N being an integer greater than 1) running in the current system, uses the Analytic Hierarchy Process (AHP) and M performance indicators (M being an integer greater than 1, where each performance indicator represents at least one of a candidate slice instance's QoS, system resource usage, and demand level). By quantifying the impact of each candidate slice instance on the current system's operating state, a comprehensive score is given to each candidate slice instance (i.e., determining the first weight). Then, based on the result of the comprehensive score (i.e., the first weight set), automated operation and maintenance of the slice is performed, i.e., determining whether to execute the slice management operation to be performed. Since the comprehensive score result is obtained based on the AHP, using M performance indicators, and quantifying the impact of each candidate slice instance on the current system's operating state, the comprehensive score result can objectively reflect the current network status, i.e., it can characterize the objective network status. Thus, based on the AHP, automated slice management can be achieved according to the objective network status without increasing the network's operational burden, thereby meeting the slice management needs of vertical industries and related scenarios using slices. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating the slice management method according to an embodiment of this application;

[0045] Figure 2 This is a flowchart illustrating a slice management method based on hierarchical analysis, serving as an application example of this application.

[0046] Figure 3 This is a flowchart illustrating another slice management method based on hierarchical analysis, serving as an application example of this application.

[0047] Figure 4 This application example illustrates a slice management hierarchical analysis model.

[0048] Figure 5 This is a schematic diagram of another slice management hierarchy analysis model used in this application.

[0049] Figure 6 This is a schematic diagram of the slice management device according to an embodiment of this application;

[0050] Figure 7 This is a schematic diagram of the electronic device structure according to an embodiment of this application. Detailed Implementation

[0051] The present application will now be described in further detail with reference to the accompanying drawings and embodiments.

[0052] Current slice management is relatively simple, limited to manual pause, resume, performance monitoring, and alarm functions, which cannot cope with increasingly complex network structures and user needs. However, related technologies can employ the following two types of slice management methods to achieve slice management:

[0053] Type 1, rule-based management of slices, that is, managing slices through pre-defined slice management rules, which can usually involve multiple simple dimensions, such as effective time, expiration time, action time, action area, etc.

[0054] Type 2, slice management based on machine learning algorithms. This type of method usually requires collecting a large amount of historical network data and training and analyzing the collected data to complete the slice management.

[0055] However, for the type 1 slice management method mentioned above, although rule-based slice management is time-efficient and easy to operate, it essentially operates on a specific slice instance / class / region. The operation is primarily based on subjective factors such as the operational experience of the maintenance personnel, and cannot accurately reflect the current network status. For the type 2 slice management method mentioned above, although machine learning-based slice management can better reflect the current network status and characteristics, this type of method requires high model accuracy and is highly dependent on the quality of the model itself. Furthermore, this type of method typically requires building large neural networks and collecting a large amount of historical network data for training and analysis in the early stages, which can easily create a significant burden on network operations.

[0056] Based on this, in various embodiments of this application, for N candidate slice instances (N being an integer greater than 1) running in the current system, the Analytic Hierarchy Process (AHP) is used to quantify the impact of each candidate slice instance on the current system's operating state. M performance indicators (M being an integer greater than 1, where each performance indicator represents at least one of a candidate slice instance's QoS, system resource usage, and demand level) are used to comprehensively score each candidate slice instance. Then, based on the comprehensive score result, automated operation and maintenance of the slice is performed, i.e., determining whether to execute the slice management operation to be performed. Since the comprehensive score result is obtained based on the AHP, using M performance indicators, and quantifying the impact of each candidate slice instance on the current system's operating state, the comprehensive score result can objectively reflect the current network status, i.e., it can characterize the objective network status. Thus, based on the AHP, automated slice management can be achieved according to the objective network status without increasing the network's operational burden, thereby meeting the slice management needs of vertical industries and related scenarios using slices.

[0057] Specifically, embodiments of this application provide a slice management method applied to electronic devices (such as servers), such as... Figure 1 As shown, the method includes:

[0058] Step 101: For the first slice instance set, determine the slice management operation to be executed. The first slice instance set contains N candidate slice instances running in the current system, where N is an integer greater than 1.

[0059] Step 102: Based on the analytic hierarchy process, use M performance indicators to determine the first weight set of the first slice instance set, where M is an integer greater than 1. A performance indicator represents at least one of the following: a QoS of a candidate slice instance, a system resource occupied, and a demand level. The first weight set contains N first weights, and a first weight represents the degree of influence of a candidate slice instance on the operating state of the system.

[0060] Step 103: Based on the first weight set, determine whether to execute the slice management operation to be executed.

[0061] In practical applications, the value of N can be determined based on requirements (such as slice management requirements), and this embodiment does not limit this. It is understood that the first slice instance set may include all slice instances currently running in the system, or it may include only a portion of the slice instances currently running in the system.

[0062] In practical applications, the specific method and type of the slice management operation to be executed by the electronic device can be determined according to requirements (such as slice management requirements), and this application embodiment does not limit this. For example, the electronic device can use a specific method (such as a specific model / algorithm / strategy / rule) to determine the slice management operation to be executed. For instance, the electronic device can determine whether to perform a service degradation or service upgrade operation on the slice based on the current system load status; or, the electronic device can use the slice management operation input / selection / instruction by the user or maintenance personnel as the slice management operation to be executed. For example, the electronic device can obtain fourth information through a standard interface (such as a user interface (UI), voice device, or other system interface), and the fourth information is used to indicate the slice management operation to be executed. The fourth information can be generated based on the input / selection / instruction of the user or maintenance personnel.

[0063] Based on this, in one embodiment, determining the slice management operation to be performed for the first slice instance set may include:

[0064] Based on the operating status of the system, the slice management operation to be executed is determined. The operating status of the system includes at least the system load status. The slice management operation to be executed includes a service degradation operation or a service upgrade operation.

[0065] In practical applications, the value of M can be determined based on requirements (such as slice management requirements), and this application embodiment does not limit this. It can be understood that the M performance indicators can reflect the operating status of a candidate slice instance. Specifically, one type of QoS of the candidate slice instance can be understood with reference to the QoS definition in relevant technologies; one type of system resource occupied by the candidate slice instance can include bandwidth utilization, central processing unit (CPU) utilization, virtual machine utilization, and overall resource utilization (which can be determined based on bandwidth utilization, CPU utilization, virtual machine utilization, and other resource utilization); the demand level of the candidate slice instance can include tenant level, etc. Furthermore, the performance indicators can also be called criteria factors, etc. This application embodiment does not limit the specific names of the performance indicators, as long as their functions are implemented.

[0066] In practical applications, the electronic device can construct a hierarchical analysis model during the process of determining the first weight set based on the analytic hierarchy process (AHP). This model can include the following three layers:

[0067] The first layer can be understood as the final goal of the current analysis. That is, the first layer may include target slice instances, and the target slice instances include candidate slice instances corresponding to the slice management operation to be executed in the first slice instance set.

[0068] The second layer can be understood as the influencing factors involved in the final target selection, that is, the second layer may include the M performance indicators;

[0069] The third layer may include alternative slice instances, that is, the third layer may include the first set of slice instances.

[0070] In practical applications, the hierarchical analysis model can also be called a slice management hierarchical analysis model, etc. The first layer can also be called the target layer, etc., the second layer can also be called the criterion layer, etc., and the third layer can also be called the instance layer or scheme layer, etc. The embodiments of this application do not limit these specific names, as long as the corresponding functions are implemented. Specifically, the electronic device can first determine the influence weight of the second layer on the first layer, that is, determine the influence weight of each of the M performance indicators on the target slice instance (which can be referred to as the second weight in the following description); and determine the influence weight of the third layer on the second layer, that is, determine the influence weight of each candidate slice instance in the first slice instance set on each of the M performance indicators (which can be referred to as the third weight in the following description); and then determine the first weight set based on the determined weights.

[0071] Based on this, in one embodiment, determining the first weight set of the first slice instance set using M performance metrics based on the analytic hierarchy process may include:

[0072] Determine a second weight set and N third weight sets for the first slice instance set. The second weight set contains M second weights, and each second weight represents the degree of influence of a performance indicator on a target slice instance. The target slice instance includes the candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set. A third weight set is associated with a candidate slice instance, and a third weight set contains M third weights. Each third weight represents the degree of influence of a candidate slice instance on a performance indicator.

[0073] The first weight set is determined based on the second weight set and N third weight sets.

[0074] In practical applications, all / part of the second weights in the second weight set can be determined by the electronic device through collecting and analyzing relevant data from the current system, or by user or maintenance personnel through input / selection / instruction operations; all / part of the third weights in the N third weight sets can be determined by the electronic device through collecting and analyzing relevant data from the current system, or by user or maintenance personnel through input / selection / instruction operations; all / part of the third weights in the third weight sets can be determined by the electronic device through collecting and analyzing relevant data from the current system, or by user or maintenance personnel through input / selection / instruction operations. For example, the electronic device can obtain fifth information through a standard interface (such as a UI interface, voice device, or other system interface), which is used to indicate the second weight set. This fifth information can be generated based on user or maintenance personnel's input / selection / instruction operations; and the electronic device can determine the N third weight sets by collecting and analyzing relevant data from the current system through a data collection and analysis module (which may contain a preset data collection and analysis model). Alternatively, for the M performance metrics, the weights related to factors such as bandwidth utilization, CPU utilization, and virtual machine utilization (i.e., the performance metrics) can be determined by the electronic device through the data acquisition and analysis module by collecting and analyzing relevant data of the current system, while the weights related to factors such as QoS and the system resources that can be occupied after slice instantiation (i.e., the comprehensive resource occupancy) can be set by the user.

[0075] In practical applications, during the process of determining the first weight set based on the second weight set and N third weight sets, the electronic device can construct the judgment matrix of the second layer (which can be referred to as the first judgment matrix in the following description) and the judgment matrix of the third layer (which can be referred to as the second judgment matrix in the following description) based on these weight sets, and determine the comprehensive score of each candidate slice instance among the N candidate slice instances based on these constructed matrices, that is, determine the first weight of each candidate slice instance.

[0076] Based on this, in one embodiment, determining the first weight set based on the second weight set and N third weight sets may include:

[0077] Determine the first judgment matrix corresponding to the second weight set, and based on the N third weight sets, determine M second judgment matrices, with each second judgment matrix associated with a performance index;

[0078] The first weight set is determined based on the first judgment matrix and M second judgment matrices.

[0079] In practical applications, the electronic device can first perform vector summation on the first judgment matrix and the M second judgment matrices, standardize the resulting column vectors, and obtain the weight vectors of the second layer and the weight vectors of the third layer, and then use the weight vectors of the second layer and the weight vectors of the third layer to determine the first weight set.

[0080] In practical applications, if the maximum value of the N first weights contained in the first weight set is equal to 0, it means that none of the slice instances currently running in the system can meet the requirements (i.e., the requirements corresponding to the slice management operation to be executed), and the slice management operation to be executed can be skipped.

[0081] Based on this, in one embodiment, determining whether to execute the slice management operation to be executed based on the first weight set may include:

[0082] If the maximum value among the N first weights contained in the first weight set is equal to 0, the slice management operation to be executed will not be performed.

[0083] In practical applications, when the maximum value of the N first weights contained in the first weight set is equal to 0, the electronic device can re-evaluate the slice instances currently running in the system, that is, re-execute steps 101 to 103; or, the electronic device can report the score of each candidate slice instance in the first slice instance set, that is, report the first weight set, so that the user or maintenance personnel can specify the target slice instance or instruct subsequent operations.

[0084] In practical applications, when the maximum value among the N first weights contained in the first weight set corresponds to only one candidate slice instance, the electronic device can determine the slice instance as the target slice instance and perform the slice management operation to be performed on the target slice instance.

[0085] Based on this, in one embodiment, determining whether to execute the slice management operation to be executed based on the first weight set may include:

[0086] If the maximum value among the N first weights contained in the first weight set is not equal to 0, the candidate slice instance corresponding to the maximum value is determined as the target slice instance. The target slice instance includes the candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set.

[0087] For the target slice instance, perform the slice management operation to be performed.

[0088] In practical applications, the electronic device can maintain a user preference database for storing user preference data associated with the system. This database can at least store a user identifier that can uniquely identify a user, as well as first information and second information associated with the user. The first information can be used to indicate a second slice instance set, which can contain multiple slice instances. The second slice instance set can reflect the user preferences associated with the system, and the second information can be used to indicate the slice instances selected by the user from the second slice instance set. The second slice instance set can be understood as the user's preference dataset, and the slice instances indicated by the second information can be understood as the user's preference selections. When the maximum value among the N first weights contained in the first weight set corresponds to multiple candidate slice instances, that is, when multiple target slice instances are determined, the electronic device can introduce relevant processing of the user preference database. That is, it can obtain the first information and the second information from the user preference database, determine whether the multiple target slice instances are a subset of the second slice instance set, and determine whether the multiple target slice instances include the slice instance indicated by the second information. In other words, the electronic device needs to determine whether the user has selected one of the multiple target slice instances in a slice instance selection scenario similar to the current scenario, and use the user's preference selection as a reference to determine a target slice instance for which the slice management operation to be executed will be performed.

[0089] Based on this, in one embodiment, performing the slice management operation to be performed on the target slice instance may include:

[0090] In the case that multiple target slice instances are identified, first information and second information are obtained. The first information is used to indicate a second slice instance set, which contains multiple slice instances and can reflect user preferences associated with the system. The second information is used to indicate slice instances that the user has selected from the second slice instance set.

[0091] If the plurality of target slice instances are a subset of the second slice instance set, and the plurality of target slice instances include the slice instance indicated by the second information, the slice management operation to be performed is executed for the slice instance indicated by the second information.

[0092] In practical applications, during the process of determining whether the multiple target slice instances are a subset of the second slice instance set and whether the multiple target slice instances include the slice instance indicated by the second information, if the electronic device determines that the multiple target slice instances are not a subset of the second slice instance set, or determines that the multiple target slice instances are a subset of the second slice instance set but do not include the slice instance indicated by the second information, the electronic device can further introduce a manual selection mechanism (which can also be understood as a manual intervention mechanism), report or present the multiple target slice instances on the corresponding screen, and allow the user or maintenance personnel to input / select / instruct a target slice instance to ultimately execute the slice management operation to be performed.

[0093] Based on this, in one embodiment, performing the slice management operation to be performed on the target slice instance may include:

[0094] In the case that multiple target slice instances are identified, first information and second information are obtained. The first information is used to indicate a second slice instance set, which contains multiple slice instances and can reflect user preferences associated with the system. The second information is used to indicate slice instances that the user has selected from the second slice instance set.

[0095] If the plurality of target slice instances are a subset of the second slice instance set and the plurality of target slice instances do not include the slice instance indicated by the second information, or if the plurality of target slice instances are not a subset of the second slice instance set, third information is obtained, the third information being used to indicate the slice instance selected from the plurality of target slice instances.

[0096] For the slice instance indicated by the third information, the slice management operation to be performed is executed. In practical applications, the third information may be generated based on user or maintenance personnel's input / selection / instruction, etc. Furthermore, simultaneously with, before, or after executing the slice management operation for the slice instance indicated by the third information, the electronic device can associate the user's identifier with the sixth information and the third information, and store the associated information in the user preference database. The sixth information can be used to indicate a third slice instance set, which may contain the multiple target slice instances.

[0097] The slice management method provided in this application, for a first slice instance set, determines the slice management operation to be executed. The first slice instance set contains N candidate slice instances running in the current system, where N is an integer greater than 1. Based on the analytic hierarchy process (AHP), using M performance indicators, a first weight set of the first slice instance set is determined, where M is an integer greater than 1. Each performance indicator represents at least one of the following: a QoS of a candidate slice instance, a system resource it occupies, and a demand level. The first weight set contains N first weights, where each first weight represents the degree of influence of a candidate slice instance on the operating state of the system. Based on the first weight set, it is determined whether to execute the slice management operation to be executed. The solution provided in this application, for N candidate slice instances (N being an integer greater than 1) running in the current system, uses the Analytic Hierarchy Process (AHP) and M performance indicators (M being an integer greater than 1, where each performance indicator represents at least one of a candidate slice instance's QoS, system resource usage, and demand level). By quantifying the impact of each candidate slice instance on the current system's operating state, a comprehensive score is given to each candidate slice instance (i.e., determining the first weight). Then, based on the result of the comprehensive score (i.e., the first weight set), automated operation and maintenance of the slice is performed, i.e., determining whether to execute the slice management operation to be performed. Since the comprehensive score result is obtained based on the AHP, using M performance indicators, and quantifying the impact of each candidate slice instance on the current system's operating state, the comprehensive score result can objectively reflect the current network status, i.e., it can characterize the objective network status. Thus, based on the AHP, automated slice management can be achieved according to the objective network status without increasing the network's operational burden, thereby meeting the slice management needs of vertical industries and related scenarios using slices.

[0098] The following section provides a more detailed description of this application with reference to application examples.

[0099] This application example proposes a slice management method based on hierarchical analysis. This method combines the subjective intentions of users or maintenance personnel with the objective status of the network, and integrates multiple influencing factors to comprehensively analyze slice management operations suitable for the current network. Specifically, a flowchart of this method can be shown as follows: Figure 2 As shown, the method may include the following steps:

[0100] Step 201: Obtain the operation information related to the current slice management (i.e., obtain the fourth and fifth information mentioned above);

[0101] Step 202: Generate a relevant judgment matrix based on the operation information (i.e., generate the first judgment matrix and the second judgment matrix mentioned above);

[0102] Step 203: Calculate the score (i.e. the first weight set) of the current slice instance set (i.e. the first slice instance set mentioned above), and perform the corresponding management operation on the slice instance with the highest score; if there are cases with the same score, introduce a manual intervention mechanism until the corresponding slice instance is selected to perform the management operation.

[0103] First, in step 201, relevant slice management information can be obtained. The slice management information may include, but is not limited to, the following information: slice management operation (such as service degradation, service upgrade, etc.) information (i.e., the fourth information mentioned above), the influence weight of the criterion factors (i.e., the performance indicators mentioned above) on the target layer (i.e., the first layer mentioned above) (i.e., the second weight mentioned above) information (i.e., the fifth information mentioned above), etc.

[0104] Secondly, in step 202, the criterion layer (i.e., the second layer) judgment matrix (i.e., the first judgment matrix) and the instance layer (i.e., the third layer) judgment matrix (i.e., the second judgment matrix) can be constructed based on the obtained influence weights and the influence weights of each slice instance on each criterion factor collected and analyzed by the network (i.e., the third weights mentioned above).

[0105] Finally, in step 203, after calculating the comprehensive score (i.e., the first weight mentioned above) of each slice instance running in the current system based on the judgment matrix generated in step 202, the comprehensive score can be automatically judged:

[0106] If the highest score is 0, it means that none of the current instances can meet the requirements for performing slice management operations, and slice management operations can be skipped.

[0107] If there is a slice instance with the highest score, the corresponding slice management operation can be performed on that slice instance;

[0108] If multiple slice instances achieve the highest score, a manual intervention mechanism can be introduced.

[0109] In the manual intervention mechanism, the system first checks if user preference data exists under the username in the user preference database. If it does, it checks if the highest-scoring slice instance set (i.e., the aforementioned multiple target slice instances, also known as the aforementioned third slice instance set) is a subset of the existing dataset (i.e., the aforementioned second slice instance set). If it is a subset, it checks if the final user preference selection in that set (i.e., the slice instance indicated by the aforementioned second information) is in the current highest-scoring slice instance set. If it exists, it performs the corresponding slice management operation on that slice instance (i.e., the slice instance indicated by the aforementioned second information). Otherwise, the score of the highest-scoring slice instance set can be reported, and the system manually selects the slice instance for which slice management operation needs to be performed. The slice instance set (i.e., the highest-scoring slice instance set, also known as the aforementioned third slice instance set) and the result of the manual selection (i.e., the aforementioned third information) are associated with the user and recorded in the user preference database within the system.

[0110] Another flowchart illustrating the slice management method based on hierarchical analysis presented in this application example can be shown as follows: Figure 3 As shown, the method may include the following steps:

[0111] Step 301: Obtain slice management information (i.e., obtain the fourth and fifth information mentioned above), and then proceed to step 302;

[0112] Step 302: The slice management hierarchy analysis module outputs a slice instance (i.e., the target slice instance mentioned above), and then proceeds to step 303;

[0113] Step 303: Perform slice management operations, that is, based on the output of the slice management hierarchy analysis module (specifically, the output of the slice management hierarchy analysis model in the slice management hierarchy analysis module), perform the slice management operations specified by the slice management information on the corresponding slice instances.

[0114] In step 301, slice management information can be obtained through standard interfaces in related technologies (such as UI interfaces, voice devices or other system interfaces). The slice management information may include, but is not limited to: slice management operation (such as service degradation, service upgrade, etc.) information (i.e., the fourth information mentioned above), and the influence weight of the criterion factors (i.e., the performance indicators mentioned above) on the target layer (i.e., the first layer mentioned above) (i.e., the second weight mentioned above) information (i.e., the fifth information mentioned above).

[0115] In step 302, the slice management hierarchical analysis module may include two functional parts: a slice management hierarchical analysis model (i.e., the hierarchical analysis model mentioned above) and a user preference database.

[0116] Among them, such as Figure 4As shown, the slice management hierarchical analysis model established in the slice management hierarchical analysis module can include three layers: the target layer (i.e., the first layer mentioned above), the criteria layer (i.e., the second layer mentioned above), and the instance layer (i.e., the third layer mentioned above). The target layer can be understood as the final goal of the current analysis, i.e., the final slice instance (i.e., the target slice instance mentioned above); the criteria layer can include the influencing factors involved in the selection of the final goal (i.e., m performance indicators, where m is an integer greater than 1); the instance layer can include candidate instances (i.e., n candidate slice instances, where n is an integer greater than 1).

[0117] Specifically, the processing steps of the slice management hierarchical analysis model may include:

[0118] Step 1: Create an alternative slice instance set (i.e., the first slice instance set mentioned above), which contains all slice instances currently running in the system.

[0119] Step 2: Construct a slice management hierarchical analysis model, which may include three layers: the target layer (i.e., the first layer mentioned above), the criteria layer (i.e., the second layer mentioned above), and the instance layer (i.e., the third layer mentioned above). The target layer can be understood as the final goal of the current analysis, i.e., the final slice instance (i.e., the target slice instance mentioned above); the criteria layer may include the influencing factors involved in the selection of the final goal (i.e., m performance indicators, where m is an integer greater than 1); the instance layer may include candidate instances (i.e., n candidate slice instances, where n is an integer greater than 1), i.e., a set of candidate slice instances (i.e., the first slice instance set mentioned above).

[0120] Step 3: The slice management information may include the influence weights of the criterion factors on the target layer (i.e., the second weights mentioned above), which are a1, a2, ..., a m Among them, the criteria factors may include, but are not limited to: bandwidth utilization, CPU utilization, virtual machine utilization, resource consumption (here referring to the comprehensive resource consumption factor that combines multiple resource consumption situations), QoS and other system resources that can be occupied after slice instantiation or QoS factors provided, and may also include demand level factors such as tenant level.

[0121] The influence weights of the instance layer on the criterion factors (i.e., the third weights mentioned above) can be collected and processed by the data analysis and processing module in the system (i.e., the data acquisition and analysis module mentioned above, which may include a preset data acquisition and analysis model) to obtain the influence weights b of candidate instance 1 on each criterion factor of the criterion layer. 11 ,b 12 ,...,b 1m The influence weight b of candidate instance 2 on each criterion factor in the criterion layer. 21 ,b 22 ,...,b 2mSimilarly, the influence weights b of candidate instance n on each criterion factor in the criterion layer are obtained. n1 ,b n2 ,...,b nm .

[0122] Here, the weight design methods involved in this application example can include two categories: one is user-defined, and the other is weight analysis completed through the system's data acquisition and analysis module. For example, factors such as bandwidth utilization, CPU utilization, and virtual machine utilization in the above criteria can be analyzed for weight through the system's data acquisition and analysis module, while factors such as QoS and other slice instantiation can be set by the user.

[0123] Step 4: Based on the above data (i.e., weights), generate the criterion layer judgment matrix of the slice management hierarchical analysis model (i.e., the first judgment matrix mentioned above):

[0124]

[0125] And generate the scheme layer judgment matrix (i.e., the second judgment matrix mentioned above) O1, O2, ..., O m :

[0126]

[0127]

[0128]

[0129] Step 5: Perform vector summation on the criterion layer judgment matrix and the instance layer judgment matrix respectively, and standardize the resulting column vectors to obtain the criterion layer weight vector ω. C and instance layer weight vector Based on this, the column vector composed of the scores of each slice instance in the instance layer (i.e., the first weight mentioned above) can be calculated by the following formula:

[0130]

[0131] Find the maximum value S of the column vector formed by the scores of the slice instances. max If the highest score is 0, it means that none of the current slice instances can meet the requirements for performing slice management operations. Slice management operations can be skipped, and the scores of each slice instance (i.e., the first weight set mentioned above) need to be re-reported. If S max If there is only one corresponding slice instance, then the slice management operation can be performed on the slice instance with the highest score. If S max For multiple slice instances, a manual intervention mechanism needs to be introduced, namely, the relevant processing of the user preference database.

[0132] Specifically, if multiple slice instances achieve the highest score (i.e., the maximum value in the first weight set mentioned above), a manual intervention mechanism is required. First, the user preference database can be queried to determine if user preference data for that username exists. If it does, the database continues to query whether the highest-scoring slice instance set (i.e., the multiple target slice instances mentioned above, also known as the third slice instance set) is a subset of an existing dataset (i.e., the second slice instance set mentioned above). If it is a subset, the database determines whether the final user preference selection in that set (i.e., the slice instance indicated by the second information mentioned above) is within the current highest-scoring slice instance set. If it exists, the corresponding slice management operation is performed on that slice instance (i.e., the slice instance indicated by the second information mentioned above). Otherwise, the scores of the highest-scoring slice instance set can be reported, and a manual selection process is used to choose the slice instance requiring slice management. This slice instance set (i.e., the highest-scoring slice instance set, also known as the third slice instance set mentioned above) and the result of the manual selection (i.e., the third information mentioned above) are then associated with the user and recorded in the system's user preference database. The user preference database may contain at least: a user identifier that can uniquely identify the user, a preference dataset associated with the user (i.e., the second slice instance set mentioned above), and specific preference choices (i.e., the second information mentioned above).

[0133] In this application example, suppose the operations and maintenance personnel detect that the current system load is too high and need to degrade the service of one of the multiple currently running slice instances. The slice management information obtained by the system can include the slice management operation (service degradation) and the impact weights a1 and a2 of the criteria factors (bandwidth utilization, tenant level) on the target layer. Then, as... Figure 5 As shown, a slice management hierarchical analysis model can be constructed, which may include a target layer, a criterion layer, and an instance layer. The target layer can be understood as the final slice instance selection, i.e., the final slice instance (i.e., the aforementioned target slice instance). The criterion layer may include preset criterion factors: bandwidth utilization and tenant level. The criterion layer may include each slice instance currently running in the system. The data analysis and processing module in the system can collect and process the current system status (which may include relevant data such as system operating status) to obtain the influence weight of the instance layer on the criterion factors, which are the influence weights b of candidate instance 1 on each criterion factor of the criterion layer. 11 ,b 12 The influence weight b of candidate instance 2 on each criterion factor in the criterion layer. 21 ,b 22 And the influence weight b of candidate instance 3 on each criterion factor in the criterion layer. 31 ,b 32Based on the above data (i.e., weights), the criterion-level judgment matrix of the slice management hierarchical analysis model can be generated:

[0134]

[0135] And generate the scheme layer (i.e., instance layer) judgment matrix:

[0136]

[0137] The criterion layer judgment matrix and the instance layer judgment matrix are summed by vector summation, and the resulting column vectors are standardized to obtain the criterion layer weight vector ω. C and instance layer weight vector ω O1 ,ω O2 Based on this, the column vector composed of the scores of each slice instance in the instance layer can be derived from... get.

[0138] Find the maximum value S of the column vector S composed of the scores of the slice instances. max If the highest score is 0, it means that none of the current slice instances meet the requirements for performing slice management operations. In this case, slice management operations can be skipped, and the scores of each slice instance need to be re-reported. If S max If there is only one corresponding slice instance, then the slice management operation can be performed on the slice instance with the highest score. If S max For multiple slice instances, a manual intervention mechanism needs to be introduced, namely, the relevant processing of the user preference database.

[0139] Specifically, the system first checks if user preference data for the given username exists in the user preference database. If it does, it checks if the highest-scoring slice instance set (i.e., the aforementioned multiple target slice instances, also known as the aforementioned third slice instance set) is a subset of an existing dataset (i.e., the aforementioned second slice instance set). If it is a subset, it checks if the final user preference selection in that set (i.e., the slice instance indicated by the aforementioned second information) is in the current highest-scoring slice instance set. If it exists, it performs the corresponding slice management operation on that slice instance (i.e., the slice instance indicated by the aforementioned second information). Otherwise, the score of the highest-scoring slice instance set can be reported, and a manual selection can be made of the slice instance that requires slice management operation. This slice instance set (i.e., the highest-scoring slice instance set, also known as the aforementioned third slice instance set) and the result of the manual selection (i.e., the aforementioned third information) are associated with the user and recorded in the user preference database within the system.

[0140] Finally, service degradation operations can be performed on the slice instances output by the slice management hierarchy analysis model.

[0141] The solution provided in this application example has the following advantages:

[0142] 1) By using the slice management method based on hierarchical analysis, the impact of each slice instance on the current system can be specifically quantified and a specific score can be given (i.e. the first weight mentioned above). The automated operation and maintenance of the slice can be completed based on the score.

[0143] 2) A manual intervention mechanism is proposed, which can effectively solve the problem that when there are multiple highest-scoring slice instances, the system cannot decide which slice instance to manage.

[0144] 3) A user preference database maintenance method is proposed. Based on this method, user preference data can be effectively recorded. When a similar situation occurs in the system (i.e., when it is necessary to select a target slice instance), a judgment can be made immediately (i.e., the target slice instance is determined according to user preferences), thereby reducing system running time.

[0145] To implement the method of the embodiments of this application, the embodiments of this application also provide a slice management device, such as... Figure 6 As shown, the device includes:

[0146] The first processing unit 601 is used to determine the slice management operation to be executed for the first slice instance set, wherein the first slice instance set contains N candidate slice instances running in the current system, where N is an integer greater than 1.

[0147] The second processing unit 602 is used to determine a first weight set of the first slice instance set based on the analytic hierarchy process and using M performance indicators, where M is an integer greater than 1. A performance indicator represents at least one of a QoS, a system resource occupied, and a demand level of a candidate slice instance. The first weight set contains N first weights, and a first weight represents the degree of influence of a candidate slice instance on the operating state of the system.

[0148] The third processing unit 603 is used to determine whether to execute the slice management operation to be executed based on the first weight set.

[0149] In one embodiment, the second processing unit 602 is specifically used for:

[0150] Determine a second weight set and N third weight sets for the first slice instance set. The second weight set contains M second weights, and each second weight represents the degree of influence of a performance indicator on a target slice instance. The target slice instance includes the candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set. A third weight set is associated with a candidate slice instance, and a third weight set contains M third weights. Each third weight represents the degree of influence of a candidate slice instance on a performance indicator.

[0151] The first weight set is determined based on the second weight set and N third weight sets.

[0152] In one embodiment, the second processing unit 602 is further configured to:

[0153] Determine the first judgment matrix corresponding to the second weight set, and based on the N third weight sets, determine M second judgment matrices, with each second judgment matrix associated with a performance index;

[0154] The first weight set is determined based on the first judgment matrix and M second judgment matrices.

[0155] In one embodiment, the third processing unit 603 is specifically used for:

[0156] If the maximum value among the N first weights contained in the first weight set is not equal to 0, the candidate slice instance corresponding to the maximum value is determined as the target slice instance. The target slice instance includes the candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set.

[0157] For the target slice instance, perform the slice management operation to be performed.

[0158] In one embodiment, the third processing unit 603 is further configured to:

[0159] In the case that multiple target slice instances are identified, first information and second information are obtained. The first information is used to indicate a second slice instance set, which contains multiple slice instances and can reflect user preferences associated with the system. The second information is used to indicate slice instances that the user has selected from the second slice instance set.

[0160] If the plurality of target slice instances are a subset of the second slice instance set, and the plurality of target slice instances include the slice instance indicated by the second information, the slice management operation to be performed is executed for the slice instance indicated by the second information.

[0161] In one embodiment, the third processing unit 603 is further configured to:

[0162] In the case that multiple target slice instances are identified, first information and second information are obtained. The first information is used to indicate a second slice instance set, which contains multiple slice instances and can reflect user preferences associated with the system. The second information is used to indicate slice instances that the user has selected from the second slice instance set.

[0163] If the plurality of target slice instances are a subset of the second slice instance set and the plurality of target slice instances do not include the slice instance indicated by the second information, or if the plurality of target slice instances are not a subset of the second slice instance set, third information is obtained, the third information being used to indicate the slice instance selected from the plurality of target slice instances.

[0164] For the slice instance indicated by the third information, perform the slice management operation to be performed.

[0165] In one embodiment, the third processing unit 603 is specifically configured to not perform the slice management operation to be performed when the maximum value among the N first weights contained in the first weight set is equal to 0.

[0166] In one embodiment, the first processing unit 601 is specifically used to determine the slice management operation to be executed based on the operating state of the system. The operating state of the system includes at least the load state of the system, and the slice management operation to be executed includes a service degradation operation or a service upgrade operation.

[0167] The functions of the second processing unit 602 and the third processing unit 603 are equivalent to those of the slice management hierarchical analysis module in the above application example.

[0168] In practical applications, the first processing unit 601, the second processing unit 602, and the third processing unit 603 can be implemented by the processor in the slice management device.

[0169] It should be noted that the slice management device provided in the above embodiments is only illustrated by the division of the above program modules when performing slice management. In actual applications, the above processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the processing described above. In addition, the slice management device and the slice management method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0170] Based on the hardware implementation of the above program modules, and in order to implement the method of the embodiments of this application, the embodiments of this application also provide an electronic device, such as... Figure 7 As shown, the electronic device 700 includes:

[0171] The communication interface 701 enables information exchange with other electronic devices;

[0172] The processor 702 is connected to the communication interface 701 to enable information interaction with other electronic devices and to execute the methods provided by one or more of the above-mentioned technical solutions when running computer programs;

[0173] The memory 703 stores computer programs that can run on the processor 702.

[0174] Specifically, the processor 702 is used for:

[0175] For the first slice instance set, determine the slice management operation to be executed. The first slice instance set contains N candidate slice instances running in the current system, where N is an integer greater than 1.

[0176] Based on the analytic hierarchy process, a first weight set of the first slice instance set is determined using M performance indicators, where M is an integer greater than 1. Each performance indicator represents at least one of the following: a QoS of a candidate slice instance, a system resource it occupies, and a demand level. The first weight set contains N first weights, and each first weight represents the degree of influence of a candidate slice instance on the operating state of the system.

[0177] Based on the first weight set, determine whether to execute the slice management operation to be executed.

[0178] In one embodiment, the processor 702 is further configured to:

[0179] Determine a second weight set and N third weight sets for the first slice instance set. The second weight set contains M second weights, and each second weight represents the degree of influence of a performance indicator on a target slice instance. The target slice instance includes the candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set. A third weight set is associated with a candidate slice instance, and a third weight set contains M third weights. Each third weight represents the degree of influence of a candidate slice instance on a performance indicator.

[0180] The first weight set is determined based on the second weight set and N third weight sets.

[0181] In one embodiment, the processor 702 is further configured to:

[0182] Determine the first judgment matrix corresponding to the second weight set, and based on the N third weight sets, determine M second judgment matrices, with each second judgment matrix associated with a performance index;

[0183] The first weight set is determined based on the first judgment matrix and M second judgment matrices.

[0184] In one embodiment, the processor 702 is further configured to:

[0185] If the maximum value among the N first weights contained in the first weight set is not equal to 0, the candidate slice instance corresponding to the maximum value is determined as the target slice instance. The target slice instance includes the candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set.

[0186] For the target slice instance, perform the slice management operation to be performed.

[0187] In one embodiment, the processor 702 is further configured to:

[0188] In the case that multiple target slice instances are identified, first information and second information are obtained. The first information is used to indicate a second slice instance set, which contains multiple slice instances and can reflect user preferences associated with the system. The second information is used to indicate slice instances that the user has selected from the second slice instance set.

[0189] If the plurality of target slice instances are a subset of the second slice instance set, and the plurality of target slice instances include the slice instance indicated by the second information, the slice management operation to be performed is executed for the slice instance indicated by the second information.

[0190] In one embodiment, the processor 702 is further configured to:

[0191] In the case that multiple target slice instances are identified, first information and second information are obtained. The first information is used to indicate a second slice instance set, which contains multiple slice instances and can reflect user preferences associated with the system. The second information is used to indicate slice instances that the user has selected from the second slice instance set.

[0192] If the plurality of target slice instances are a subset of the second slice instance set and the plurality of target slice instances do not include the slice instance indicated by the second information, or if the plurality of target slice instances are not a subset of the second slice instance set, third information is obtained, the third information being used to indicate the slice instance selected from the plurality of target slice instances.

[0193] For the slice instance indicated by the third information, perform the slice management operation to be performed.

[0194] In one embodiment, the processor 702 is further configured to not perform the slice management operation to be performed if the maximum value among the N first weights contained in the first weight set is equal to 0.

[0195] In one embodiment, the processor 702 is further configured to determine the slice management operation to be executed based on the operating state of the system, wherein the operating state of the system includes at least the load state of the system, and the slice management operation to be executed includes a service degradation operation or a service upgrade operation.

[0196] It should be noted that the specific processing procedure of the processor 702 can be understood by referring to the above method, and will not be repeated here.

[0197] Of course, in practical applications, the various components in electronic device 700 are coupled together through bus system 704. It can be understood that bus system 704 is used to realize the connection and communication between these components. In addition to a data bus, bus system 704 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, in... Figure 7 The general designated all buses as Bus System 704.

[0198] The memory 703 in this embodiment is used to store various types of data to support the operation of the electronic device 700. Examples of such data include any computer program used to operate on the electronic device 700.

[0199] The methods disclosed in the embodiments of this application can be applied to or implemented by processor 702. Processor 702 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by integrated logic circuits in the hardware of processor 702 or by instructions in software form. Processor 702 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Processor 702 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, specifically memory 703. Processor 702 reads information from memory 703 and, in conjunction with its hardware, completes the steps of the aforementioned method.

[0200] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned method.

[0201] It is understood that the memory 703 in this embodiment can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memories described in the embodiments of this application are intended to include, but are not limited to, these and any other suitable types of memories.

[0202] In an exemplary embodiment, this application also provides a storage medium, namely a computer storage medium, specifically a computer-readable storage medium, such as a memory 703 storing a computer program, which can be executed by the processor 702 of the electronic device 700 to complete the steps described in any of the foregoing methods. The computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, Flash Memory, magnetic surface memory, optical disc, or CD-ROM.

[0203] In an exemplary embodiment, this application also provides a computer program product, including a computer program that can be executed by a processor 702 of an electronic device 700 to perform the steps described in any of the foregoing methods.

[0204] It should be noted that terms such as "first" and "second" are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0205] Furthermore, the technical solutions described in the embodiments of this application can be combined arbitrarily without conflict.

[0206] The above description is merely a preferred embodiment of this application and is not intended to limit the scope of protection of this application.

Claims

1. A slice management method, characterized by, The method comprises: determining a slice management operation to be executed for a first slice instance set, the first slice instance set containing N candidate slice instances running in a current system, N being an integer greater than 1; determining a first weight set of the first slice instance set based on an analytic hierarchy process and using M performance indexes, M being an integer greater than 1, one performance index representing at least one of a quality of service (QoS) of one candidate slice instance, a system resource occupied by one candidate slice instance, and a demand level of one candidate slice instance, the first weight set containing N first weights, one first weight representing a degree of influence of one candidate slice instance on a running state of the system; determining whether to execute the slice management operation to be executed based on the first weight set; wherein the determining of the first weight set of the first slice instance set based on the analytic hierarchy process and using the M performance indexes comprises: determining a second weight set of the first slice instance set and N third weight sets, the second weight set containing M second weights, one second weight representing a degree of influence of one performance index on a target slice instance, the target slice instance including a candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set, one third weight set being associated with one candidate slice instance, one third weight set containing M third weights, one third weight representing a degree of influence of one candidate slice instance on one performance index; determining the first weight set based on the second weight set and the N third weight sets.

2. The method of claim 1, wherein, the determining of the first weight set based on the second weight set and the N third weight sets comprises: determining a first judgment matrix corresponding to the second weight set, and determining M second judgment matrices based on the N third weight sets, one second judgment matrix being associated with one performance index; determining the first weight set based on the first judgment matrix and the M second judgment matrices.

3. The method of claim 1, wherein, the determining of whether to execute the slice management operation to be executed based on the first weight set comprises: in a case where a maximum value in the N first weights contained in the first weight set is not equal to 0, determining a candidate slice instance corresponding to the maximum value as a target slice instance, the target slice instance including a candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set; executing the slice management operation to be executed for the target slice instance.

4. The method of claim 3, wherein, the executing of the slice management operation to be executed for the target slice instance comprises: in a case where a plurality of target slice instances are determined, obtaining first information and second information, the first information being used to indicate a second slice instance set, the second slice instance set containing a plurality of slice instances, the second slice instance set being capable of reflecting user preferences associated with the system, the second information being used to indicate slice instances selected by a user from the second slice instance set; In a case where the plurality of target slice instances are a subset of the second slice instance set and the plurality of target slice instances include the slice instances indicated by the second information, the slice management operation to be performed is performed on the slice instances indicated by the second information.

5. The method of claim 3, wherein, The performing the slice management operation to be performed on the target slice instance comprises: In a case where a plurality of target slice instances are determined, first information and second information are acquired, the first information is used to indicate a second slice instance set, the second slice instance set includes a plurality of slice instances, the second slice instance set can reflect user preferences associated with the system, and the second information is used to indicate slice instances selected by a user from the second slice instance set; In a case where the plurality of target slice instances are a subset of the second slice instance set and the plurality of target slice instances do not include the slice instances indicated by the second information, or in a case where the plurality of target slice instances are not a subset of the second slice instance set, third information is acquired, the third information is used to indicate slice instances selected from the plurality of target slice instances; The slice management operation to be performed is performed on the slice instances indicated by the third information.

6. The method of claim 1, wherein, The determining whether to perform the slice management operation to be performed based on the first weight set comprises: In a case where a maximum value of N first weights included in the first weight set is equal to 0, the slice management operation to be performed is not performed.

7. The method of claim 1, wherein, The determining the slice management operation to be performed on the first slice instance set comprises: Based on a running state of the system, the slice management operation to be performed is determined, the running state of the system at least includes a load state of the system, and the slice management operation to be performed includes a service degradation operation or a service upgrade operation.

8. A slice management apparatus characterized by comprising: Comprise: A first processing unit is configured to determine a slice management operation to be performed on a first slice instance set, the first slice instance set includes N candidate slice instances running in a current system, N is an integer greater than 1; A second processing unit is configured to determine a first weight set of the first slice instance set by using M performance indicators based on an analytic hierarchy process, M is an integer greater than 1, one performance indicator represents at least one of a QoS of one candidate slice instance, a system resource occupied by the candidate slice instance, and a demand level, and the first weight set includes N first weights, one first weight represents an influence degree of one candidate slice instance on a running state of the system; A third processing unit is configured to determine whether to perform the slice management operation to be performed based on the first weight set; wherein, The second processing unit is specifically configured to determine a second weight set and N third weight sets of the first slice instance set, the second weight set includes M second weights, one second weight representing an influence degree of one performance index on a target slice instance, the target slice instance including a candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set; one third weight set is associated with one candidate slice instance, one third weight set includes M third weights, one third weight representing an influence degree of one candidate slice instance on one performance index; and the first weight set is determined based on the second weight set and the N third weight sets.

9. An electronic device, comprising: Comprise: a communication interface and a processor; wherein the processor is configured to: determine a slice management operation to be executed for a first slice instance set, the first slice instance set including N candidate slice instances running in a current system, N being an integer greater than 1; determine a first weight set of the first slice instance set by using M performance indexes based on an analytic hierarchy process, M being an integer greater than 1, one performance index representing at least one of a QoS of one candidate slice instance, a system resource occupied by one candidate slice instance, and a demand level, the first weight set including N first weights, one first weight representing an influence degree of one candidate slice instance on a running state of the system; determine whether to execute the slice management operation to be executed based on the first weight set; and wherein the processor is further configured to: determine a second weight set and N third weight sets of the first slice instance set, the second weight set including M second weights, one second weight representing an influence degree of one performance index on a target slice instance, the target slice instance including a candidate slice instance corresponding to the slice management operation to be executed in the first slice instance set; one third weight set is associated with one candidate slice instance, one third weight set includes M third weights, one third weight representing an influence degree of one candidate slice instance on one performance index; and the first weight set is determined based on the second weight set and the N third weight sets. Comprise:

10. An electronic device, comprising: a processor and a memory for storing a computer program capable of running on the processor, wherein the processor is configured to execute the steps of the method of any one of claims 1 to 7 when running the computer program. The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

11. A storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

12. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 7.

Images