Resource configuration method, device, computing device and storage medium for network slicing

Abstract

The present invention discloses a resource configuration method, apparatus, computing device and storage medium for network slicing, the method comprising: obtaining slice configuration requirement information; constructing an integer linear programming model according to the slice configuration requirement information; the constraints of the integer linear programming model are determined according to the slice configuration requirement information, and the optimization goal of the integer linear programming model is to maximize the availability weighted capacity of the network slice; determining each candidate network resource by solving the integer linear programming model; evaluating the utility scores of each reserved network path corresponding to each candidate network resource, and determining the target network path according to the utility scores of each reserved network path; and configuring the network slice according to the target network path. In the above manner, using a heuristic algorithm, wireless resources can be quickly reallocated, and resource utilization can be maximized while meeting the user's configuration requirements.

Description

Technical Field

[0001] The present invention relates to the field of communication technology, and specifically to a resource configuration method, device, computing equipment and storage medium for network slicing. Background Art

[0002] Cloud computing is the result of the convergence of several technologies, including the Internet of Things (IoT), distributed computing, grid computing, and system management. In today's era of big data, traditional single or small physical machines struggle to process large amounts of data. This is why cloud computing has emerged. Based on a large number of distributed virtual environments, cloud computing allows users to lease resources that meet their needs and dynamically run projects. However, when connecting to cloud computing, wireless resource allocation mechanisms are a pressing issue.

[0003] In related technologies, a resource allocation solution utilizes wireless access network sharing technology to manage and schedule wireless resources on multiple base stations of different entities in a shared network. It uses programming to calculate the needs of each user and provides an interface to control their resource allocation in the network. A small portion of resources is reserved during the resource slicing process. However, this solution is a static solution that uses wireless slicing technology to slice the spectrum based on the initial needs provided by the user and environmental factors. As the number of end users grows and their needs change, wireless spectrum resources will become scarce, and wireless resource fragmentation will often occur. This means that resource allocation is unbalanced, and the resource allocation ratio cannot be dynamically adjusted based on actual network needs, resulting in a waste of resources in certain dimensions and ultimately a reduction in service quality. Furthermore, the method of reserving a small portion of resources may not be able to meet the user's service quality requirements well given limited resources.

[0004] Another resource allocation solution is based on deep reinforcement learning. This method trains a model and uses it to reallocate wireless resources in real time based on changes in customer demand, user resource utilization, and the number of customers. However, deep reinforcement learning is complex and subject to latency, requiring significant computational time to find the optimal solution. Furthermore, as the environment changes, the previously trained deep model becomes inapplicable, creating the risk of predictive model failure due to the system's open learning space. While it is possible to collect a large number of test samples in the laboratory to train the model, these samples are unlikely to represent the all-weather status data found in a real-world open environment, and the model parameters obtained in the laboratory are not suitable for predicting real-world data. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a resource configuration method, apparatus, computing device and storage medium for network slicing that overcome the above problems or at least partially solve the above problems.

[0006] According to one aspect of the present invention, a resource configuration method for a network slice is provided, comprising:

[0007] Get slice configuration requirement information;

[0008] Construct an integer linear programming model based on slice configuration requirement information;

[0009] The constraints of the integer linear programming model are determined according to the slice configuration requirement information, and the optimization goal of the integer linear programming model is to maximize the availability-weighted capacity of the network slice.

[0010] By solving the integer linear programming model, each candidate network resource is determined;

[0011] Evaluate the utility scores of each reserved network path corresponding to each candidate network resource, and determine the target network path based on the utility scores of each reserved network path;

[0012] Configure network slices based on the target network path.

[0013] Optionally, the slice configuration requirement information includes: availability requirement information, reliability requirement information, and delay requirement information;

[0014] The constraints include: the availability of network resources meets the reliability requirement information; the reliability of network resources meets the reliability requirement information; and the end-to-end delay from the source node to the destination node in the network resources meets the delay requirement information.

[0015] Optionally, evaluating the utility scores of the respective reserved network paths corresponding to the respective candidate network resources and determining the target network path according to the utility scores of the respective reserved network paths specifically includes:

[0016] Construct a heuristic algorithm and determine the target network path based on the heuristic algorithm;

[0017] The heuristic algorithm process includes:

[0018] Traversing each reserved network path corresponding to the candidate network resource and calculating the utility score of the reserved network path;

[0019] Determine whether the utility score of the retained network path meets the heuristic condition;

[0020] If so, the reserved network path is added to the target network path set, and the target network path is filtered from the target network path set.

[0021] Optionally, filtering the target network path from the target network path set further includes:

[0022] The retained network path with the highest utility score is selected from the target network path set as the target network path.

[0023] Optionally, calculating the utility score of the network path specifically includes:

[0024] Calculate the availability effect value, reliability effect value, and delay effect value of the reserved network path respectively;

[0025] Calculating the product of the availability effect value and its first utility coefficient, the reliability effect value and its second utility coefficient, and the delay effect value and its third utility coefficient to obtain a utility score of the retained network path;

[0026] Among them, when the availability corresponding to the reserved network path does not meet the availability requirement information, the availability effect value is 0, otherwise, the availability effect value is not 0; when the reliability corresponding to the reserved network path does not meet the reliability requirement information, the reliability effect value is 0, otherwise, the reliability effect value is not 0; when the delay corresponding to the reserved network path does not meet the delay requirement information, the delay effect value is 0, otherwise, the delay effect value is not 0;

[0027] If the utility score of the retained network path is not equal to 0, it is determined that the utility score of the retained network path meets the heuristic condition.

[0028] Optionally, the method further comprises:

[0029] Calculate the network slice available capacity of the network slice.

[0030] According to another aspect of the present invention, a resource configuration device for a network slice is provided, comprising:

[0031] A demand acquisition module, suitable for obtaining slice configuration demand information;

[0032] A model building module, suitable for building an integer linear programming model based on slice configuration requirement information;

[0033] The constraints of the integer linear programming model are determined according to the slice configuration requirement information, and the optimization goal of the integer linear programming model is to maximize the availability-weighted capacity of the network slice.

[0034] A model solving module, adapted to determine various candidate network resources by solving an integer linear programming model;

[0035] A path solving module, adapted to evaluate the utility scores of each reserved network path corresponding to each candidate network resource, and determine a target network path according to the utility scores of each reserved network path;

[0036] The configuration module is adapted to determine a target network path according to the utility scores of each reserved network path; and configure network slices according to the target network path.

[0037] Optionally, the slice configuration requirement information includes: availability requirement information, reliability requirement information, and delay requirement information;

[0038] The constraints include: the availability of network resources meets the reliability requirement information; the reliability of network resources meets the reliability requirement information; and the end-to-end delay from the source node to the destination node in the network resources meets the delay requirement information.

[0039] Optionally, the path solving module is further adapted to: construct a heuristic algorithm and determine the target network path according to the heuristic algorithm; wherein the process of the heuristic algorithm includes:

[0040] Traversing each reserved network path corresponding to the candidate network resource, and calculating the utility score of the reserved network path;

[0041] Determine whether the utility score of the retained network path meets the heuristic condition;

[0042] If so, the reserved network path is added to the target network path set, and the target network path is filtered from the target network path set.

[0043] Optionally, the path solving module is further adapted to: select a reserved network path with the highest utility score from the target network path set as the target network path.

[0044] Optionally, the path solving module is further adapted to:

[0045] Calculate the availability effect value, reliability effect value, and delay effect value of the reserved network path respectively;

[0046] Calculating the product of the availability effect value and its first utility coefficient, the reliability effect value and its second utility coefficient, and the delay effect value and its third utility coefficient to obtain a utility score of the retained network path;

[0047] Among them, when the availability corresponding to the reserved network path does not meet the availability requirement information, the availability effect value is 0, otherwise, the availability effect value is not 0; when the reliability corresponding to the reserved network path does not meet the reliability requirement information, the reliability effect value is 0, otherwise, the reliability effect value is not 0; when the delay corresponding to the reserved network path does not meet the delay requirement information, the delay effect value is 0, otherwise, the delay effect value is not 0;

[0048] If the utility score of the reserved network path is not equal to 0, it is determined that the utility score of the reserved network path meets the heuristic condition.

[0049] Optionally, the device also includes: a capacity calculation module, suitable for calculating the network slice available capacity of the network slice.

[0050] According to another aspect of the present invention, there is provided a computing device, comprising: a processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus;

[0051] The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the resource configuration method of the above-mentioned network slicing.

[0052] According to another aspect of the present invention, a computer storage medium is provided, wherein the storage medium stores at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the resource configuration method of the network slicing as described above.

[0053] According to the resource configuration method, apparatus, computing device and storage medium of the network slice of the present invention, the method includes: obtaining slice configuration requirement information; constructing an integer linear programming model according to the slice configuration requirement information; the constraints of the integer linear programming model are determined according to the slice configuration requirement information, and the optimization goal of the integer linear programming model is to maximize the availability weighted capacity of the network slice; by solving the integer linear programming model, each candidate network resource is determined; the utility score of each reserved network path corresponding to each candidate network resource is evaluated, and the target network path is determined according to the utility score of each reserved network path; and the network slice is configured according to the target network path. In the above manner, using a heuristic algorithm, wireless resources can be quickly reallocated, and resource utilization can be maximized while meeting the user's configuration requirements.

[0054] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0056] Figure 1 A flowchart of a resource configuration method for a network slice provided by an embodiment of the present invention is shown;

[0057] Figure 2 A schematic diagram of network slicing is shown;

[0058] Figure 3 A schematic diagram showing the structure of a resource configuration device for a network slice provided by an embodiment of the present invention is shown;

[0059] Figure 4 A schematic structural diagram of a computing device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0060] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present invention and to fully convey the scope of the present invention to those skilled in the art.

[0061] Figure 2 The diagram shows a network slice diagram, which includes three network slices. VN represents a virtual node, VL represents a virtual link, PN represents a physical node, FL represents a fiber link, and ML represents a microwave link. As can be seen, a network slice consists of a set of virtual nodes and virtual links. Virtual nodes are connected by virtual links. Each virtual node provides a certain amount of computing and storage resources to support mobile edge computing, and each virtual link provides a certain amount of network bandwidth resources to support network communications. The number of virtual nodes and virtual links in a network slice is determined by user needs. Each network slice independently carries services, and different network slices do not interfere with each other. A failure in one network slice does not affect the normal operation of other network slices, making network slices easy to maintain.

[0062] Network slice mapping is divided into two parts: virtual node mapping and virtual link mapping. When performing virtual node mapping, the embodiment of the present invention assumes that each virtual node can only be mapped to a specific physical node (i.e., one-to-one mapping). At the same time, a certain number of virtual machines are allocated to each virtual node to provide computing and storage resources for mobile edge computing. When performing virtual link mapping, each virtual link in the embodiment of the present invention can be mapped to one of the k alternative paths allocated to it according to the corresponding metric method. At the same time, a certain amount of network bandwidth is allocated to each virtual link.

[0063] Figure 1 A flowchart of a resource configuration method for a network slice according to an embodiment of the present invention is shown. Figure 1 As shown, the method includes the following steps:

[0064] Step S110: Obtain slice configuration requirement information.

[0065] Among them, the slice configuration requirement information of the network slice refers to the user's demand for the network slice, including the demand for availability, reliability and delay characteristics.

[0066] Step S120: construct an integer linear programming model according to the slice configuration requirement information.

[0067] Among them, the constraints of the integer linear programming model are determined according to the slice configuration requirement information, and the optimization goal of the integer linear programming model is to maximize the availability weighted capacity of the network slice.

[0068] When a network slice needs to be created, the target network resources must first be searched so that resources can be allocated to the slice according to its service level agreement, where the service level agreement of the slice is described based on the configuration requirement parameters.

[0069] In the method of this embodiment, an integer linear programming model (ILP model) is used to obtain candidate network resources. The constraints of the ILP model are constructed specifically according to the slice configuration requirement information provided by the user. At the same time, the optimization goal of the ILP model is set. In this embodiment, the optimization goal of the ILP model is to maximize the availability-weighted capacity of the network slice.

[0070] Step S130 : determining each candidate network resource by solving an integer linear programming model.

[0071] Among them, the network slice includes a collection of v virtual machines, n nodes and l links. The network slice is represented as: S i =<{VM i},{N i},{Link i}>, where S i Represents slice, VM i Indicates a virtual machine, Link i Indicates a link.

[0072] Solve the constructed ILP model to obtain various candidate network resources, where each candidate network resource includes a candidate virtual machine, a candidate node, and a candidate link.

[0073] Step S140: evaluate the utility scores of each reserved network path corresponding to each candidate network resource, determine the target network path according to the utility scores of each reserved network path, and configure the network slice according to the target network path.

[0074] The performance of an end-to-end network slice depends on the performance of all its constituent network resources and applications. Therefore, the end-to-end reliability and availability of a deployed slice depends on the reliability and availability of each component functional block. The combination of several components in a slice deployment creates a serial dependency. The simultaneous availability and reliability of all constituent functions must be guaranteed for the entire slice to be available and reliable. For example, deploying a VNF on an NFV infrastructure is a serial dependency, with its reliability and availability relying on the physical hardware, the hypervisor, and the VNF's own software.

[0075] For each candidate network resource, it represents a slice, and there are multiple network connection paths between its source node and destination node, that is, the slice has different implementation scenarios. The method of this embodiment is to solve the optimal network slice implementation scenario between the source node and the destination node. In the method of this embodiment, by evaluating the utility scores of each reserved network path, the optimal network path is screened out according to the utility score, and finally, the network slice is configured according to the optimal network path. Among them, the reserved network path represents the connection relationship between the various component functional blocks contained in the candidate network resource. The utility score is positively correlated with the availability and reliability corresponding to the reserved network path, and negatively correlated with the delay.

[0076] In this embodiment, the availability weighted capacity of the network slice is expressed as follows:

[0077]

[0078] Among them, S represents the set of network slices, represents the set of K alternative paths mapped by the virtual link v in the network slice, V s represents the set of virtual links in the network slice s, represents a binary variable, and a value of 1 indicates that the virtual link v in the network slice s is mapped to the Kth path. represents the availability of the Kth path mapped by the virtual link v in the network slice s, represents the required capacity of the virtual link v in the network slice s. Then the optimization goal of the ILP model is to maximize the availability-weighted capacity.

[0079] The calculation formula for path availability is as follows:

[0080] A path =A s ·A d ·A n ·A l ·A m

[0081] A path Indicates the availability of the route, A sIndicates the availability of the source node of the path, A d Indicates the availability of the destination node of the path, A n Indicates the availability of the intermediate nodes of the path, A l Indicates the availability of the optical fiber link that the path passes through, A m Indicates the availability of the microwave link that the path passes through.

[0082] In an optional manner, after determining to configure the network slice according to the target network path, the available capacity of the network slice is calculated.

[0083] In an optional manner, the slice configuration requirement information includes: availability requirement information, reliability requirement information, and delay requirement information; the constraint conditions include: the availability of the network resource meets the reliability requirement information; the reliability of the network resource meets the reliability requirement information; and the end-to-end delay from the source node to the destination node in the network resource meets the delay requirement information. For example, the availability requirement information is that the availability of the selected network resource exceeds the availability threshold (i.e., the availability required by the user), the reliability requirement is that the reliability of the selected network resource exceeds the reliability threshold (i.e., the reliability required by the user), and the delay requirement information is that the end-to-end delay from the source node to the destination node in the selected network resource does not exceed the delay threshold (i.e., the delay required by the user).

[0084] Accordingly, the constraints of the ILP model are expressed as follows:

[0085]

[0086]

[0087]

[0088] Among them, constraint (1) means that the availability of the selected network resources is equal to or higher than the user's availability configuration requirement value, A i That is, it represents the user's availability configuration requirement value; constraint (2) indicates that the reliability of the selected network resource is equal to or higher than the user's reliability configuration requirement value, R i That is, it represents the user's reliability configuration requirement value; constraint (3) indicates that the end-to-end delay from the source node to the destination node in the selected network resource is less than or equal to the user's delay configuration requirement value, D i This indicates the user's delay configuration requirement value, that is, the maximum allowed delay requested.

[0089] In the above approach, attention is paid to the availability, reliability, and delay characteristics of network resources. The constraints of the ILP model are set based on the reliability, availability, and delay requirements provided by users. This enables resource allocation to maximize resource utilization while meeting the service quality required by users.

[0090] Solving the optimal network path is an NP-Hard problem. Heuristic algorithms can be used to find the most suitable network path in the shortest possible time. Heuristic solutions do not rely on the mathematical properties of the problem, such as continuous differentiability and non-convexity. They are not strict or sensitive to initial values ​​and can efficiently handle complex, high-dimensional, multimodal optimization problems, finding the global optimum or a value close to it in a reasonable time.

[0091] Specifically, in an optional manner, after obtaining the candidate network resources by solving the integer current planning model, a constructed heuristic algorithm is used to determine the optimal network path between the source node and the destination node in the candidate network resources, that is, the target network path. The process of the heuristic algorithm specifically includes: traversing each reserved network path corresponding to the candidate network resource, calculating the utility score of the reserved network path; judging whether the utility score of the reserved network path meets the heuristic condition; if so, adding the reserved network path to the target network path set, and screening the target network path from the target network path set. That is, for any possible network path between the source node and the destination node in the candidate network resource, by calculating the utility score of the possible network path, if the utility score meets the heuristic condition, then adding the possible network path to the target network path set, and finally screening the target network path from each network path in the target network path set.

[0092] In an optional manner, the utility score of the retained network path is calculated as follows:

[0093] The availability effect value, reliability effect value, and delay effect value of the retained network path are calculated respectively; the product of the availability effect value and its first utility coefficient, the reliability effect value and its second utility coefficient, and the delay effect value and its third utility coefficient is calculated to obtain a utility score of the retained network path; wherein the first utility coefficient, the second utility coefficient, and the third utility coefficient are all non-zero.

[0094] Among them, when the availability corresponding to the retained network path does not meet the availability requirement information, the availability effect value is 0, otherwise, the availability effect value is not 0; when the reliability corresponding to the retained network path does not meet the reliability requirement information, the reliability effect value is 0, otherwise, the reliability effect value is not 0; when the delay corresponding to the retained network path does not meet the delay requirement information, the delay effect value is 0, otherwise, the delay effect value is not 0.

[0095] If the utility score of the reserved network path is not equal to 0, it is determined that the utility score of the reserved network path meets the heuristic condition.

[0096] From the above content, it can be seen that if the availability, reliability and delay of the retained network path all meet the user requirements, the availability effect value, reliability effect value and delay effect value are all non-zero, and accordingly, the utility score will not be zero, then the retained network path is considered to meet the heuristic conditions; on the contrary, if any one of the availability, reliability and delay of the retained network path does not meet the user requirements, and the corresponding utility score is 0, then the retained network path does not meet the heuristic conditions and is not added to the target network path set, that is, the candidate network path is not considered as a candidate option.

[0097] In an optional manner, the utility coefficient is calculated by a utility function, which is expressed as follows:

[0098] U(x)=1-e -αx

[0099] Where x represents the decision vector, α represents the weight, and α ≥ 0. The utility function used is an increasing function, and the change in the utility coefficient is proportional to the change in the variable value.

[0100] The method for evaluating the utility score of the reserved network path is: utility score = first utility coefficient × availability effect value × second utility coefficient × reliability effect value × third utility coefficient × delay effect value.

[0101] The first utility coefficient is positively correlated with the availability corresponding to the reserved network path, the second utility coefficient is positively correlated with the reliability corresponding to the reserved network path, and the third utility coefficient is negatively correlated with the delay corresponding to the reserved network path.

[0102] The specific calculation formula is as follows:

[0103]

[0104] Among them, SC(NR j ) represents the utility score of the network resource NR (essentially, the utility score of the preserved network path), represents the first utility coefficient, α A represents the weight of the availability vector, A j represents the availability vector, Indicates the usability effect value;

[0105] represents the second utility coefficient, α R Represents the weight of the reliability vector, R j represents the reliability vector, represents the reliability effect value;

[0106] represents the third utility coefficient, α L represents the weight of the delay vector, L j represents the delay vector, Indicates the delay effect value.

[0107] The ranges of availability effect value, reliability effect value, and delay effect value are as follows:

[0108]

[0109]

[0110]

[0111] In an optional manner, for the decision criteria, the weights of the vectors of the three dimensions are set equal, that is, the three different performance criteria are given the same weight.

[0112] When configuring slice resources, reliability and availability must be maximized to meet user satisfaction, while latency must be minimized. The above formula for calculating the utility score shows that greater reliability and availability result in a higher utility score, while lower latency also results in a higher utility score. Based on this, the reserved network paths corresponding to each candidate network resource are screened for the one with the highest utility score as the final result.

[0113] The utility score calculation formula above shows that the utility score of a reserved network path will not be zero unless the reliability, availability, and latency of the reserved network path all meet user requirements. Based on this, the first heuristic algorithm can be set as follows:

[0114] 1: Initialize S = [], where S represents the set of reserved network paths assigned to the slice set. (The slice set consists of slices composed of candidate network resources obtained by solving the ILP model, and the functional blocks contained in the slices are also the functional blocks contained in the candidate network resources.)

[0115] 2:for:Slice do, slice represents all slices

[0116] 3:src, the source node of the slice

[0117] 4:dst, the destination node of the slice

[0118] 5: s = null, s represents the reserved network path assigned to the slice.

[0119] 6: P = F (src, dst), this function records a list of all possible paths from src to dst.

[0120] 7:while(s=null&&d <d thr )do,d thr Indicates the longest reconstruction time

[0121] 8: s, score = ScoredPath(src, dst, P, score), where score represents the input and output parameters of ScoredPath and is used to calculate the score of the retained path.

[0122] 9:done

[0123] 10:if(score is not equal to 0)then

[0124] 11: Add s to the S set

[0125] 12:else

[0126] 13: return "Calculation time exceeded, no path obtained"

[0127] 14:endif

[0128] 15:end for

[0129] 16: Calculate slice availability weighted capacity

[0130] 17:return slice availability weighted capacity

[0131] It can be seen that the logic of the algorithm is to calculate the utility score of each reserved network path corresponding to the candidate network resource in turn. If the utility score is 0, it is determined that the calculation time has exceeded and no valid network path has been obtained. The current reserved network path is released, and the next reserved network path is obtained and the above process is repeated; if the utility score is not 0, the reserved network path is added to the target network path set, and the next reserved network path is obtained and the above process is repeated.

[0132] The second heuristic algorithm is as follows:

[0133] 1: L = Null, L represents the target network path

[0134] 2: c1 = card1(P); c1 function calculates the number of possible paths from src to dst

[0135] 3: i = 0

[0136] 4:PS=0; Path i ∈P score

[0137] 5: score, the score of the retained network path.

[0138] 6: while(i <c1&&PS=0)do

[0139] 7: c2 = card2(); card2 calculates the path i The cardinality or number of candidate network resources.

[0140] 8: v = 1

[0141] 9: for j=1....c2 do

[0142] 10: Calculate the score SC of the retained network path,

[0143] 11: v = v × SC

[0144] 12: end for

[0145] 13: PS = v

[0146] 14: if PS is not 0 then

[0147] 15: L = Path i , target network path

[0148] 16: score = PS; score is the score of the target retention path

[0149] 17: End if

[0150] 18: i++

[0151] 19: done

[0152] 20:Return L,score

[0153] To sum up, this embodiment provides a dynamic slice resource configuration method, which uses a heuristic algorithm to quickly reallocate wireless resources; secondly, this method can maximize resource utilization while meeting the user's configuration requirements; and it can overcome the problems of unbalanced resource allocation and low accuracy in related technologies.

[0154] Figure 3 A schematic diagram of the structure of a resource configuration device for a network slice according to an embodiment of the present invention is shown. Figure 3 As shown, the device includes:

[0155] A requirement acquisition module 31 is adapted to acquire slice configuration requirement information;

[0156] A model building module 32 is adapted to build an integer linear programming model according to slice configuration requirement information;

[0157] The constraints of the integer linear programming model are determined according to the slice configuration requirement information, and the optimization goal of the integer linear programming model is to maximize the availability-weighted capacity of the network slice.

[0158] A model solving module 33, adapted to determine each candidate network resource by solving an integer linear programming model;

[0159] a path solving module 34 adapted to evaluate the utility scores of the respective reserved network paths corresponding to the respective candidate network resources, and determine the target network path according to the utility scores of the respective reserved network paths;

[0160] The configuration module 35 is adapted to determine a target network path based on the utility scores of each reserved network path; and configure network slices based on the target network path.

[0161] In an optional manner, the slice configuration requirement information includes: availability requirement information, reliability requirement information, and delay requirement information;

[0162] The constraints include: the availability of network resources meets the reliability requirement information; the reliability of network resources meets the reliability requirement information; and the end-to-end delay from the source node to the destination node in the network resources meets the delay requirement information.

[0163] In an optional manner, the path solving module 34 is further adapted to: construct a heuristic algorithm and determine the target network path according to the heuristic algorithm; wherein the process of the heuristic algorithm includes:

[0164] Traversing each reserved network path corresponding to the candidate network resource, and calculating a utility score of the reserved network path;

[0165] Determine whether the utility score of the retained network path meets the heuristic condition;

[0166] If so, the reserved network path is added to the target network path set, and the target network path is filtered from the target network path set.

[0167] In an optional manner, the path solving module 34 is further adapted to: select a reserved network path with the highest utility score from the target network path set as the target network path.

[0168] In an optional manner, the path solving module 34 is further adapted to:

[0169] Calculate the availability effect value, reliability effect value, and delay effect value of the reserved network path respectively;

[0170] Calculating the product of the availability effect value and its first utility coefficient, the reliability effect value and its second utility coefficient, and the delay effect value and its third utility coefficient to obtain a utility score of the retained network path;

[0171] Among them, when the availability corresponding to the reserved network path does not meet the availability requirement information, the availability effect value is 0, otherwise, the availability effect value is not 0; when the reliability corresponding to the reserved network path does not meet the reliability requirement information, the reliability effect value is 0, otherwise, the reliability effect value is not 0; when the delay corresponding to the reserved network path does not meet the delay requirement information, the delay effect value is 0, otherwise, the delay effect value is not 0;

[0172] If the utility score of the reserved network path is not equal to 0, it is determined that the utility score of the reserved network path meets the heuristic condition.

[0173] In an optional manner, the device also includes: a capacity calculation module, suitable for calculating the network slice available capacity of the network slice.

[0174] This embodiment provides a dynamic slice resource configuration method, which uses a heuristic algorithm to quickly reallocate wireless resources; secondly, this method can maximize resource utilization while meeting the user's configuration requirements; and it can overcome the problems of unbalanced resource allocation and low accuracy in related technologies.

[0175] An embodiment of the present invention provides a non-volatile computer storage medium, which stores at least one executable instruction, and the computer executable instruction can execute the resource configuration method of the network slice in any of the above method embodiments.

[0176] Figure 4 The schematic diagram of the structure of the computing device embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the computing device.

[0177] like Figure 4 As shown, the computing device may include: a processor 402 , a communications interface 404 , a memory 406 , and a communication bus 408 .

[0178] Processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408. Communication interface 404 is used to communicate with other devices, such as clients or other server network elements. Processor 402 is used to execute program 410, which can specifically perform the relevant steps of the above-mentioned embodiment of the resource configuration method for a network slice of a computing device.

[0179] Specifically, the program 410 may include program codes, which include computer operation instructions.

[0180] Processor 402 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in a computing device may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0181] The memory 406 is used to store the program 410. The memory 406 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0182] The algorithm or demonstration provided herein are not inherently relevant to any particular computer, virtual system or other equipment. Various general-purpose systems may also be used together with the teachings based on this. According to the above description, it is apparent that the structure required for constructing this type of system. In addition, the embodiment of the present invention is not directed to any specific programming language yet. It should be understood that various programming languages ​​can be utilized to realize the content of the present invention described herein, and the above description of specific languages ​​is for the purpose of disclosing the best mode of the present invention.

[0183] In the description provided herein, numerous specific details are described. However, it is understood that embodiments of the present invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0184] Similarly, it should be understood that in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together into a single embodiment, figure, or description thereof. However, this disclosed method should not be interpreted as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the claims below, inventive aspects lie in less than all the features of the individual embodiments disclosed above. Accordingly, the claims that follow the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of the invention.

[0185] Those skilled in the art will appreciate that the modules in the devices in the embodiments may be adaptively changed and arranged in one or more devices different from the embodiments. The modules or units or components in the embodiments may be combined into one module or unit or component, and in addition may be divided into multiple submodules or subunits or subcomponents. All features disclosed in this specification (including the accompanying claims, abstracts and drawings) and all processes or units of any method or device disclosed herein may be combined in any combination, except that at least some of such features and / or processes or units are mutually exclusive. Unless expressly stated otherwise, each feature disclosed in this specification (including the accompanying claims, abstracts and drawings) may be replaced by an alternative feature providing the same, equivalent or similar purpose.

[0186] Furthermore, those skilled in the art will appreciate that although some embodiments herein include certain features included in other embodiments but not other features, combinations of features from different embodiments are intended to be within the scope of the present invention and to form different embodiments. For example, in the claims below, any of the claimed embodiments may be used in any combination.

[0187] The various component embodiments of the present invention can be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or digital signal processor (DSP) can be used in practice to implement some or all of the functions of some or all of the components according to an embodiment of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing a part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0188] It should be noted that the above embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by a person skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

Claims

1. A resource configuration method for a network slice, comprising: Get slice configuration requirement information; Constructing an integer linear programming model according to the slice configuration requirement information; The constraints of the integer linear programming model are determined according to the slice configuration requirement information, and the optimization goal of the integer linear programming model is to maximize the availability weighted capacity of the network slice; The availability-weighted capacity of a network slice is expressed as follows: Among them, S represents the set of network slices, represents the set of K alternative paths mapped by the virtual link v in the network slice, V s represents the set of virtual links in the network slice s, represents a binary variable, and a value of 1 indicates that the virtual link v in the network slice s is mapped to the Kth path. represents the availability of the Kth path mapped by the virtual link v in the network slice s, represents the required capacity of the virtual link v in the network slice s; Determining each candidate network resource by solving the integer linear programming model; Evaluating the utility scores of the respective reserved network paths corresponding to the respective candidate network resources, and determining the target network path according to the utility scores of the respective reserved network paths; Configure network slices according to the target network path.

2. The method according to claim 1, characterized in that The slice configuration requirement information includes: availability requirement information, reliability requirement information and delay requirement information; The constraints include: the availability of network resources meets the availability requirement information; the reliability of network resources meets the reliability requirement information; and the end-to-end delay from the source node to the destination node in the network resources meets the delay requirement information.

3. The method according to claim 2, characterized in that The step of evaluating the utility scores of the respective reserved network paths corresponding to the respective candidate network resources and determining the target network path according to the utility scores of the respective reserved network paths specifically includes: constructing a heuristic algorithm and determining a target network path according to the heuristic algorithm; The process of the heuristic algorithm includes: Traversing each reserved network path corresponding to the candidate network resource, and calculating the utility score of the reserved network path; Determine whether the utility score of the retained network path meets the heuristic condition; If so, the reserved network path is added to the target network path set, and the target network path is filtered from the target network path set.

4. The method according to claim 3, characterized in that The calculating of the utility score of the reserved network path specifically includes: Calculate the availability effect value, reliability effect value, and delay effect value of the reserved network path respectively; Calculating the product of the availability effect value and its first utility coefficient, the reliability effect value and its second utility coefficient, and the delay effect value and its third utility coefficient to obtain a utility score of the retained network path; When the availability corresponding to the reserved network path does not meet the availability requirement information, the availability effect value is 0; otherwise, the availability effect value is not 0; when the reliability corresponding to the reserved network path does not meet the reliability requirement information, the reliability effect value is 0; otherwise, the reliability effect value is not 0; when the delay corresponding to the reserved network path does not meet the delay requirement information, the delay effect value is 0; otherwise, the delay effect value is not 0; If the utility score of the reserved network path is not equal to 0, it is determined that the utility score of the reserved network path meets the heuristic condition.

5. The method according to claim 4, characterized in that The filtering of the target network path from the target network path set further comprises: A reserved network path with the highest utility score is selected from the target network path set as the target network path.

6. The method according to claim 1, characterized in that The method further comprises: Calculate the network slice available capacity of the network slice.

7. A resource configuration device for a network slice, comprising: A demand acquisition module, suitable for obtaining slice configuration demand information; A model building module, adapted to build an integer linear programming model according to the slice configuration requirement information; The constraints of the integer linear programming model are determined according to the slice configuration requirement information, and the optimization goal of the integer linear programming model is to maximize the availability weighted capacity of the network slice; The availability-weighted capacity of a network slice is expressed as follows: Among them, S represents the set of network slices, represents the set of K alternative paths mapped by the virtual link v in the network slice, V s represents the set of virtual links in the network slice s, represents a binary variable, and a value of 1 indicates that the virtual link v in the network slice s is mapped to the Kth path. represents the availability of the Kth path mapped by the virtual link v in the network slice s, represents the required capacity of the virtual link v in the network slice s; a model solving module, adapted to determine each candidate network resource by solving the integer linear programming model; a path solving module adapted to evaluate the utility scores of the respective reserved network paths corresponding to the respective candidate network resources, and determine the target network path according to the utility scores of the respective reserved network paths; A configuration module is suitable for configuring network slices according to the target network path.

8. The device according to claim 7, characterized in that The slice configuration requirement information includes: availability requirement information, reliability requirement information and delay requirement information; The constraints include: the availability of network resources meets the availability requirement information; the reliability of network resources meets the reliability requirement information; and the end-to-end delay from the source node to the destination node in the network resources meets the delay requirement information.

9. A computing device comprising: A processor, a memory, a communication interface, and a communication bus, wherein the processor, the memory, and the communication interface communicate with each other via the communication bus; The memory is used to store at least one executable instruction, and the executable instruction enables the processor to perform operations corresponding to the resource configuration method for network slicing as described in any one of claims 1-6.

10. A computer storage medium, wherein at least one executable instruction is stored in the storage medium, and the executable instruction enables the processor to perform operations corresponding to the resource configuration method for network slicing as described in any one of claims 1-6.

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