Network slice deployment method combining VNF partition and hybrid backup sharing

Abstract

The invention relates to a network slice deployment method combining VNF partition and hybrid backup sharing, which belongs to the technical field of network slice deployment, and comprises the following steps: S1, modeling a physical network model, a network slice model and a network slice pre-deployment model; s2, modeling a network slice reliability calculation model; s3, modeling a VNF hybrid backup method; s4, modeling is combined with a VNF partition and mixed backup sharing method; s5, modeling a network slice end-to-end time delay model and a network slice resource consumption cost model; and S6, modeling a network slice deployment limiting condition, a VNF partition limiting condition and a hybrid backup sharing limiting condition. According to the method, the reliability of the VNF with insufficient reliability in the network slice can be effectively improved, so that the expected reliability of the network slice is met; the end-to-end time delay of the network slice can be effectively reduced, so that the end-to-end time delay requirement is met; while the two requirements are met, the resource consumption of network slice deployment can be obviously reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of network slicing deployment, and relates to a network slicing deployment method combining VNF partitioning and hybrid backup sharing. Background Art

[0002] Compared with the current mobile communication system, 6G and future networks will not only be improvements in basic performance requirements (such as increasing data transmission rate, enhancing spectrum and efficiency, and expanding network coverage), but are also envisioned to have some unique features, such as resource virtualization through network slicing technology and end-user virtualization through digital twin technology, which can flexibly support new application scenarios, including ultra-high reliability and ultra-low latency required for autonomous driving and industrial Internet of Things. As a revolutionary architectural solution, network slicing aims to logically divide the underlying infrastructure into customized and isolated network slices to enable the provision of heterogeneous services, services for countless bandwidth consumers, and hosting for countless vertical industries.

[0003] However, network slicing has created new challenges in terms of availability and service continuity. Compared with traditional hardware-based network functions, VNFs implemented as software modules are more prone to failure. The failure of a single VNF in a network slice may be caused by software errors, malicious attacks, misconfiguration, and hardware failures, which will disrupt the service of the entire slice and cause user dissatisfaction and revenue loss. Therefore, ensuring service availability in a virtualized network slice environment is more complex than in a traditional network. In addition, while considering service availability, network slice deployment requires a lot of resources, so it is particularly important to implement resource-efficient reliability enhancement methods in the current resource-constrained network environment. Existing research has designed corresponding algorithms and strategies to improve network slice reliability by considering VNF redundant backup or migration; and reduced latency and resource consumption by reducing the number of VNF transmission hops in network slices. However, current work has rarely considered the comprehensive optimization of reliability, end-to-end latency, and resource consumption of network slice deployment. Summary of the invention

[0004] In view of this, the purpose of the present invention is to provide a network slice deployment method that combines VNF partitioning and hybrid backup sharing, deploys network slices into a physical network, optimizes the reliability and end-to-end delay performance of network slices, and minimizes the cost of network slice deployment.

[0005] In order to achieve the above object, the present invention provides the following technical solutions:

[0006] A network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing, comprising the following steps:

[0007] S1: Modeling physical network model, network slice model, and network slice pre-deployment model;

[0008] S2: Modeling network slice reliability calculation model;

[0009] S3: Modeling VNF hybrid backup approach;

[0010] S4: Modeling joint VNF ​​partitioning and hybrid backup sharing method;

[0011] S5: Modeling network slicing end-to-end delay model and network slicing resource consumption cost model;

[0012] S6: Modeling network slice deployment constraints, VNF partitioning constraints, and hybrid backup sharing constraints.

[0013] Furthermore, the physical network model is modeled as follows: Let the undirected weighted graph G s =(N,E) represents the physical network topology, where N(n,m∈N) represents the set of physical nodes in the physical network, and E((m,n)∈E) represents the set of physical links in the physical network; let Represents the CPU resource capacity of the physical node. Represents the storage resource capacity of the physical node, let R n Represents the reliability of the physical node, let Represents the bandwidth resource capacity of the physical link (m,n).

[0014] Furthermore, the network slice model is modeled as follows: let I represent a set of network slices; let Denotes the expected reliability of network slice i∈I, let represents the delay requirement of network slice i∈I; let the undirected weighted graph represents a network slice, where V i and L i denote VNF and virtual link set respectively; let Denotes VNFv∈V on network slice i i The CPU resource requirements are Denotes VNFv∈V on network slice i i The storage resource requirements are Denotes a virtual link (u,v)∈L i bandwidth resource requirements.

[0015] Furthermore, the network slice pre-deployment model is modeled as follows: the network slice deployment is modeled as virtual network embedding, which is divided into virtual link embedding and virtual node embedding; first, the shortest physical path that meets the virtual link resource requirements of the network slice is found in the physical network, and then for all physical nodes in the determined shortest path, the physical nodes are sorted according to their reliability, and the physical nodes with high reliability are selected to deploy the main VNF instance.

[0016] Furthermore, the network slice reliability calculation model is modeled as follows:

[0017] Let binary variable Denotes VNFv∈V in network slice i∈I i Deployed on physical nodes n∈N, Indicates that it is not deployed on the physical node n∈N; let the binary variable Denotes a virtual link (u,v)∈L i Mapped to physical link (n,m)∈E, Indicates that it is not mapped to the physical link (n,m)∈E;

[0018] VNF reliability is expressed as the product of its software reliability and the hardware reliability of the physical node where it is located. Let R i,v Denotes VNF reliability, let P i,v Represents the actual reliability of each VNF, which is modeled as:

[0019]

[0020] Among them, R n Indicates the reliability of the physical node;

[0021] Let P i Represents the actual reliability of each network slice, modeled as:

[0022]

[0023] when When , the network slice does not meet the expected reliability;

[0024] Improve reliability by sharing backups. Decompose the expected reliability of the network slice into the expected reliability of each VNF to simplify the reliability calculation. Denotes the expected reliability of each primary VNF, modeled as:

[0025]

[0026] The reliability allocation method allocates the reliability requirement of the network slice to each VNF.

[0027] Furthermore, the VNF hybrid backup method is modeled as follows: for network slices that do not meet the reliability requirements, the reliability of the network slices is improved by backing up the VNF; the backup VNF is divided into on-site backup and off-site backup; the on-site backup VNF is deployed on the same physical node as the main VNF, and the off-site backup VNF is instantiated on a physical node different from the physical node that carries the main VNF;

[0028] When on-site backup and off-site backup occur simultaneously, it is called a hybrid backup method; let the integer variable Indicates whether VNFv in network slice i is backed up; if so, and It also indicates the number of backups, otherwise Let binary variable Indicates whether VNFv is backed up on physical node n; let P i hybrid The actual reliability of VNF when the hybrid backup solution is adopted is modeled as:

[0029]

[0030] Furthermore, the joint VNF ​​partitioning and hybrid backup sharing approach is modeled as follows:

[0031] When VNFv∈V i When the actual reliability does not meet the expected reliability, first look for shared backup VNFs, and control the maximum number of shared VNFs and the number of hops after backup sharing to meet the requirements of different delay constraints.

[0032] The main VNF is divided into multiple sub-VNFs with lower capacity running in parallel; the sub-VNFs execute the same software application as the main VNF, and the reliability of each VNF after partitioning remains unchanged; let the positive integer variable l i,v ∈N + Denotes VNFv∈V i Whether it is divided into multiple sub-VNFs, i,v =1 means that VNFv is not divided, l i,v >1 means VNFv is divided, and l i,v Indicates the number of VNFvs that are divided;

[0033] Let the binary variable y i,v,n Indicates whether VNFv in network slice i is backed up on physical node n, y i,v,n =0 means that VNFv does not perform backup on node n. i,v,n =1 and Indicates on-site backup. i,v,n =1 and Indicates offsite backup; The actual reliability of VNF under VNF partitioning and hybrid backup scheme is modeled as:

[0034]

[0035] in,

[0036] Furthermore, the end-to-end delay model of the network slice is modeled as follows:

[0037] Each VNF in the network slice is modeled as an M / M / 1 queue, and the entire network slice is considered as a series connection of multiple M / M / 1 queues;

[0038] make represents the average response time of network slice i, which is modeled as:

[0039]

[0040] Among them, μ i,v =c i,v χ / α is the processing rate of VNFv in network slice i, c i,v represents the allocated CPU resources, χ represents the CPU frequency, and α represents a fixed constant for the number of CPU cycles required for each process processing;

[0041] After VNF partitioning, assuming that the processing capacity of each sub-VNF is μ i,v / l i,v , all sub-VNFs of a VNF are modeled as an M / M / m queue, where the minimum value of m is 1 and the maximum value is The average response time of network slice i is modeled as:

[0042]

[0043] in:

[0044]

[0045] The amount of data transmitted by the network slice is expressed as Dt i =f i ·fd i ·du i , where fd i and i They represent the average data volume and life cycle of the flow of network slice i respectively; let Represents the transmission delay of the network slice, which is modeled as:

[0046]

[0047] Let d iRepresents the total latency of the network slice, modeled as:

[0048]

[0049] Furthermore, the network slice resource consumption cost model is modeled as follows:

[0050] Let binary variable Denotes a virtual link (u,v)∈L i Whether to back up on the physical link (m,n)∈E; let The deployment resource consumption of network slice i after joint VNF ​​slicing and hybrid backup is modeled as:

[0051]

[0052] When the actual reliability of VNFv does not meet the expected reliability, first look for shared backup VNFs, and by constraining the maximum number of shares and the number of link hops after backup sharing, meet the requirements of different delay constraints;

[0053] Let the binary variable q i,u,v Denote v∈V i With u∈V i Whether to share backup; The resource consumption of network slice i after joint VNF ​​slicing and hybrid backup sharing is modeled as:

[0054]

[0055] When the number of VNFs increases, the resource consumption of building backup VNFs can be reduced by sharing backup VNFs, thereby reducing the resource consumption of network slice deployment.

[0056] Furthermore, the network slice deployment constraints, VNF partition constraints and hybrid backup sharing constraints are modeled as follows: Let the binary variable p i,u,v Denote v∈V i With u∈V i Are they of the same type?

[0057] (1) Modeling VNF backup instance sharing constraints:

[0058]

[0059] (2) Modeling shared backup instance resource constraints:

[0060]

[0061] (3) Modeling sharing quantity restrictions:

[0062]

[0063] (4) Modeling VNF deployment constraints:

[0064]

[0065] (5) Modeling CPU resource constraints:

[0066]

[0067] (6) Modeling storage resource constraints:

[0068]

[0069] (7) Modeling bandwidth resource constraints:

[0070]

[0071] (8) Modeling flow conservation constraints:

[0072]

[0073] (9) Modeling end-to-end delay constraints:

[0074]

[0075] (10) Modeling reliability constraints:

[0076]

[0077] (11) Modeling Constraints Integrity Restrictions:

[0078]

[0079] The beneficial effects of the present invention are as follows: the present invention can effectively improve the reliability of VNFs with insufficient reliability in network slices, so that they meet the expected reliability of network slices; it can effectively reduce the end-to-end delay of network slices, so that they meet the end-to-end delay requirements; while meeting the above two requirements, it can significantly reduce the resource consumption of network slice deployment.

[0080] Other advantages, objectives and features of the present invention will be described in the following description to some extent, and to some extent, will be obvious to those skilled in the art based on the following examination and study, or can be taught from the practice of the present invention. The objectives and other advantages of the present invention can be realized and obtained through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention will be described in detail below in conjunction with the accompanying drawings, wherein:

[0082] Figure 1 This is a diagram of the joint VNF ​​partitioning and hybrid backup sharing model adopted by the present invention;

[0083] Figure 2 A flow chart of the network slice deployment combining VNF partitioning and hybrid backup sharing according to the present invention. DETAILED DESCRIPTION

[0084] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0085] It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0086] In the following description, numerous details are discussed to provide a more thorough explanation of the embodiments of the present invention. However, it is obvious to those skilled in the art that the embodiments of the present invention can be implemented without these specific details. In other embodiments, well-known structures and devices are shown in the form of block diagrams rather than in detail to avoid making the embodiments of the present invention difficult to understand.

[0087] See also Figure 1-2 , Figure 1 This is a diagram of the joint VNF ​​partitioning and hybrid backup sharing model adopted by the present invention, such as Figure 1 As shown in the figure, the model deploys VNFs on physical machines in the underlying physical network and adopts VNF partitioning and hybrid backup sharing. By combining VNF partitioning and hybrid backup sharing methods to deploy network slices, the network slice deployment cost can be minimized while meeting the network slice reliability requirements and end-to-end delay requirements. Figure 2 The flowchart of the network slice deployment method of the present invention combined with VNF partitioning and hybrid backup sharing is as follows: Figure 2 As shown, the method specifically comprises the following steps:

[0088] Step 1: Physical network modeling;

[0089] Physical network modeling, specifically: let the undirected weighted graph G s =(N,E) represents the physical network topology, where N(n,m∈N) represents the set of physical nodes in the physical network, and E((m,n)∈E) represents the set of physical links in the physical network; let Represents the CPU resource capacity of the physical node. Represents the storage resource capacity of the physical node, let R n Represents the reliability of the physical node, let Represents the bandwidth resource capacity of the physical link (m,n).

[0090] Step 2: Network slice modeling;

[0091] Network slicing modeling is as follows: let I represent the set of network slices; let Denotes the expected reliability of network slice i∈I, let represents the delay requirement of network slice i∈I; let the undirected weighted graph represents a network slice, where V i and L i denote VNF and virtual link set respectively; let Denotes VNFv∈V on network slice i i The CPU resource requirements are Denotes VNFv∈V on network slice i i The storage resource requirements are Denotes a virtual link (u,v)∈L i bandwidth resource requirements;

[0092] Step 3: Network slice pre-deployment modeling;

[0093] The network slice pre-deployment modeling is as follows: the network slice deployment is carried out by virtual network embedding, using a non-coordinated method, which is divided into virtual link embedding and virtual node embedding. Because the end-to-end delay of the network slice must be guaranteed, the number of hops between the VNFs in the network slice must be as small as possible, so it is necessary to first embed the virtual network, and find the shortest physical path that meets the virtual link resource requirements in the network slice through the K-shortest path algorithm in the physical network; then for all physical nodes in the determined shortest path, sort them according to the reliability of the physical nodes, and select the physical nodes with high reliability to reasonably deploy the main VNF instance.

[0094] Step 4: Network slice reliability calculation modeling;

[0095] The network slice reliability calculation model is as follows: Denotes VNFv∈V in network slice i∈I i Deployed on physical nodes n∈N, Indicates that it is not deployed on the physical node n∈N; let the binary variable Denotes a virtual link (u,v)∈L i Mapped to physical link (n,m)∈E, Indicates that it is not mapped to the physical link (n,m)∈E.

[0096] VNF reliability is expressed as the product of its software reliability and the hardware reliability of the physical node where it is located. Let R i,v Denotes VNF reliability, let P i,v The actual reliability of each VNF can be modeled as:

[0097]

[0098] Among them, R n Represents the reliability of the physical node. Let P i The actual reliability of each network slice can be modeled as:

[0099]

[0100] when When , the network slice does not meet the expected reliability. This solution improves reliability by sharing backups and decomposes the expected reliability of the network slice into the expected reliability of each VNF to simplify the reliability calculation. The expected reliability of each main VNF can be modeled as:

[0101]

[0102] The reliability allocation method allocates the reliability requirement of the network slice to each VNF.

[0103] Step 5: Modeling of VNF hybrid backup method;

[0104] The hybrid backup method of VNF is modeled as follows: For network slices that do not meet the reliability requirements, the reliability of the network slice can be improved by backing up VNFs. Backup VNFs can be divided into two forms: on-site backup and off-site backup. The on-site backup VNF is deployed on the same physical node as the primary VNF, and the off-site backup VNF is instantiated on a different physical node from the one that carries the primary VNF. When on-site backup and off-site backup occur simultaneously, it is called a hybrid backup method. Let the integer variable Indicates whether VNFv in network slice i is backed up. If yes, then and It also indicates the number of backups, otherwise Let binary variable Indicates whether VNFv is backed up on physical node n. Therefore, let P i hybrid The actual reliability of VNF when the hybrid backup solution is adopted can be modeled as:

[0105]

[0106] Step 6: Modeling of joint VNF ​​partitioning and hybrid backup sharing method;

[0107] The joint VNF ​​partitioning and hybrid backup sharing method is modeled as follows: when VNFv∈V i When the actual reliability does not meet the expected reliability, we first look for shared backup VNFs, and control the maximum number of shared VNFs and the number of hops after backup sharing to meet the requirements of different delay constraints. In order to improve resource utilization and ensure the reliability of network slices with fewer backups, the main VNF is divided into multiple sub-VNFs with lower capacity running in parallel. The sub-VNFs execute the same software applications as the main VNF, and the reliability of each VNF after partitioning remains unchanged. Let the positive integer variable l i,v ∈N + Denotes VNF v∈V i Whether it is divided into multiple sub-VNFs, i,v =1 means that VNFv is not divided, l i,v >1 means VNFv is divided, and l i,v Indicates the number of VNFvs that are divided. Let the binary variable y i,v,n Indicates whether VNFv in network slice i is backed up on physical node n, y i,v,n =0 means that VNFv does not perform backup on node n. i,v,n =1 and Indicates on-site backup. i,v,n =1 and represents off-site backup. i h+d The actual reliability of VNF under VNF partitioning and hybrid backup scheme can be modeled as:

[0108]

[0109] in,

[0110] Step 7: Network slice end-to-end delay modeling;

[0111] The end-to-end delay modeling of network slices is as follows: each VNF in network slice i is modeled as an M / M / 1 queue, and the entire network slice is regarded as a series of multiple M / M / 1 queues. According to Burke's theorem, the flow arrival rate f of all VNFs in the series of multiple M / M / 1 queues is i Same. represents the average response time of network slice i, which can be modeled as:

[0112]

[0113] Among them, μ i,v =c i,v χ / α is the processing rate of VNFv in network slice i. i,v represents the allocated CPU resources, χ represents the CPU frequency (cycles / second), and α represents a fixed constant for the number of CPU cycles required for each process processing.

[0114] After VNF partitioning, assuming that the processing capacity of each sub-VNF is μ i,v / l i,v , all sub-VNFs of a VNF are modeled as an M / M / m queue, where the minimum value of m is 1 and the maximum value is Therefore, the average response time of network slice i can be modeled as:

[0115]

[0116] in:

[0117]

[0118] As for the transmission delay of the virtual link in the network slice, it is mainly related to the transmission data volume Dt of the network slice. i It is related to the bandwidth of the virtual link. The amount of data transmitted by the network slice is expressed as Dt i =f i ·fd i ·du i , where fd i and i They represent the average data volume and life cycle of the flow of network slice i respectively. The transmission delay of the network slice can be modeled as:

[0119]

[0120] Let d i The total latency of the network slice can be modeled as:

[0121]

[0122] Step 8: Modeling network slice resource consumption costs;

[0123] The network slice resource consumption cost modeling is as follows: let the binary variable Denotes a virtual link (u,v)∈L i Whether to back up on the physical link (m,n)∈E. So let The deployment resource consumption of network slice i after joint VNF ​​slicing and hybrid backup can be modeled as:

[0124]

[0125] In order to further reduce resource consumption during slice deployment, a backup sharing solution is added on the basis of the above. When the actual reliability of VNF v does not meet the expected reliability, first find out whether there is a backup VNF that can be shared, and by constraining the maximum number of shares and the number of link hops after backup sharing, the requirements of different delay constraints can be met.

[0126] Let the binary variable q i,u,v Denote v∈V i With u∈V i Whether to share the backup. The resource consumption of network slice i after joint VNF ​​slicing and hybrid backup sharing can be modeled as:

[0127]

[0128] When the number of VNFs increases, by sharing backup VNFs, the resource consumption of building backup VNFs can be reduced, thereby reducing the resource consumption of network slice deployment.

[0129] Step 9: Modeling of network slice deployment, VNF partitioning, and hybrid backup sharing constraints;

[0130] The network slice deployment and backup sharing constraint modeling is as follows: Let the binary variable p i,u,v Denote v∈V i With u∈V i Are they of the same type?

[0131] (1) Modeling VNF backup instance sharing constraints:

[0132]

[0133] (2) Modeling shared backup instance resource constraints:

[0134]

[0135] (3) Modeling sharing quantity restrictions:

[0136]

[0137] (4) Modeling VNF deployment constraints:

[0138]

[0139] (5) Modeling CPU resource constraints:

[0140]

[0141] (6) Modeling storage resource constraints:

[0142]

[0143] (7) Modeling bandwidth resource constraints:

[0144]

[0145] (8) Modeling flow conservation constraints:

[0146]

[0147] (9) Modeling end-to-end delay constraints:

[0148]

[0149] (10) Modeling reliability constraints:

[0150]

[0151] (11) Modeling Constraints Integrity Restrictions:

[0152]

[0153] In the above embodiments, the description's reference to "this embodiment" indicates that a particular feature, structure, or characteristic described in conjunction with the embodiment is included in at least some embodiments, but not necessarily all embodiments. Multiple occurrences of "this embodiment" do not necessarily all refer to the same embodiment.

[0154] In the above-described embodiments, although the invention has been described in conjunction with specific embodiments of the invention, many substitutions, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art based on the foregoing description. For example, other storage structures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed. Embodiments of the invention are intended to encompass all such substitutions, modifications, and variations that fall within the broad scope of the appended claims.

[0155] This embodiment further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, any one of the methods in this embodiment is implemented.

[0156] This embodiment also provides an electronic terminal, including: a processor and a memory;

[0157] The memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes any one of the methods in this embodiment.

[0158] The computer-readable storage medium in this embodiment can be understood by ordinary technicians in this field: all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to the computer program. The aforementioned computer program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk and other media that can store program codes.

[0159] The electronic terminal provided in this embodiment includes a processor, a memory, a transceiver and a communication interface. The memory and the communication interface are connected to the processor and the transceiver and complete communication with each other. The memory is used to store computer programs, the communication interface is used to communicate, and the processor and the transceiver are used to run computer programs so that the electronic terminal executes each step of the above method.

[0160] In this embodiment, the memory may include a random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0161] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0162] The present invention can be used in many general or special computing system environments or configurations, such as personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, and the like.

[0163] The present invention may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present invention may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0164] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. A network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing, characterized in that: The following steps are involved: S1: Modeling physical network model, network slice model, and network slice pre-deployment model; S2: Modeling network slice reliability calculation model; S3: Modeling VNF hybrid backup approach; S4: Modeling joint VNF ​​partitioning and hybrid backup sharing method; S5: Modeling network slicing end-to-end delay model and network slicing resource consumption cost model; S6: Modeling network slice deployment constraints, VNF partitioning constraints, and hybrid backup sharing constraints.

2. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The physical network model is modeled as follows: Let the undirected weighted graph G s =(N,E) represents the physical network topology, where N(n,m∈N) represents the set of physical nodes in the physical network, and E((m,n)∈E) represents the set of physical links in the physical network; let Represents the CPU resource capacity of the physical node. Represents the storage resource capacity of the physical node, let R n Represents the reliability of the physical node, let Represents the bandwidth resource capacity of the physical link (m,n).

3. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The network slice model is modeled as follows: Let I represent the set of network slices; let Denotes the expected reliability of network slice i∈I, let represents the delay requirement of network slice i∈I; let the undirected weighted graph represents a network slice, where V i and L i denote VNF and virtual link set respectively; let Denotes VNFv∈V on network slice i i The CPU resource requirements are represents VNF v∈V on network slice i i The storage resource requirements are Denotes a virtual link (u,v)∈L i bandwidth resource requirements.

4. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The network slice pre-deployment model is modeled as follows: the network slice deployment is modeled as virtual network embedding, which is divided into virtual link embedding and virtual node embedding; first, the shortest physical path that meets the virtual link resource requirements of the network slice is found in the physical network, and then for all physical nodes in the determined shortest path, the physical nodes are sorted according to their reliability, and the physical nodes with high reliability are selected to deploy the main VNF instance.

5. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The network slice reliability calculation model is modeled as follows: Let binary variable Denotes VNFv∈V in network slice i∈I i Deployed on physical nodes n∈N, Indicates that it is not deployed on the physical node n∈N; let the binary variable Denotes a virtual link (u,v)∈L i Mapped to physical link (n,m)∈E, Indicates that it is not mapped to the physical link (n,m)∈E; VNF reliability is expressed as the product of its software reliability and the hardware reliability of the physical node where it is located. Let R i,v Denotes VNF reliability, let P i,v Represents the actual reliability of each VNF, which is modeled as: Among them, R n Indicates the reliability of the physical node; Let P i Represents the actual reliability of each network slice, modeled as: when When , the network slice does not meet the expected reliability; Improve reliability by sharing backups. Decompose the expected reliability of the network slice into the expected reliability of each VNF to simplify the reliability calculation. Denotes the expected reliability of each primary VNF, modeled as: The reliability allocation method allocates the reliability requirement of the network slice to each VNF.

6. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The VNF hybrid backup method is modeled as follows: for network slices that do not meet the reliability requirements, the reliability of the network slices is improved by backing up the VNF; Backup VNFs are divided into on-site backup and off-site backup. On-site backup VNFs are deployed on the same physical node as the primary VNF, while off-site backup VNFs are instantiated on a different physical node from the one that carries the primary VNF. When onsite backup and offsite backup occur simultaneously, it is called a hybrid backup method; Let integer variable Indicates whether VNFv in network slice i is backed up; if so, and It also indicates the number of backups, otherwise Let binary variable Indicates whether VNFv is backed up on physical node n; The actual reliability of VNF when the hybrid backup solution is adopted is modeled as:

7. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The joint VNF ​​partitioning and hybrid backup sharing approach is modeled as follows: When VNFv∈V i When the actual reliability does not meet the expected reliability, first look for shared backup VNFs, and control the maximum number of shared VNFs and the number of hops after backup sharing to meet the requirements of different delay constraints. The main VNF is divided into multiple sub-VNFs with lower capacity running in parallel; the sub-VNFs execute the same software application as the main VNF, and the reliability of each VNF after partitioning remains unchanged; let the positive integer variable l i,v ∈N + Denotes VNFv∈V i Whether it is divided into multiple sub-VNFs, i,v =1 means that VNFv is not divided, l i,v >1 means VNFv is divided, and l i,v Indicates the number of VNFvs that are divided; Let the binary variable y i,v,n Indicates whether VNFv in network slice i is backed up on physical node n, y i,v,n =0 means that VNFv does not perform backup on node n. i,v,n =1 and Indicates on-site backup. i,v,n =1 and Indicates offsite backup; The actual reliability of VNF under VNF partitioning and hybrid backup scheme is modeled as: in, 8. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The network slice end-to-end delay model is modeled as follows: Each VNF in the network slice is modeled as an M / M / 1 queue, and the entire network slice is considered as a series connection of multiple M / M / 1 queues; make represents the average response time of network slice i, which is modeled as: Among them, μ i,v =c i,v χ / α is the processing rate of VNFv in network slice i, c i,v represents the allocated CPU resources, χ represents the CPU frequency, and α represents a fixed constant for the number of CPU cycles required for each process processing; After VNF partitioning, assuming that the processing capacity of each sub-VNF is μ i,v / l i,v , all sub-VNFs of a VNF are modeled as an M / M / m queue, where the minimum value of m is 1 and the maximum value is The average response time of network slice i is modeled as: in: The amount of data transmitted by the network slice is expressed as Dt i =f i ·fd i ·du i , where fd i and i They represent the average data volume and life cycle of the flow of network slice i respectively; let Represents the transmission delay of the network slice, which is modeled as: Let d i Represents the total latency of the network slice, which is modeled as:

9. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The network slice resource consumption cost model is modeled as follows: Let binary variable Denotes a virtual link (u,v)∈L i Whether to back up on the physical link (m,n)∈E; let The deployment resource consumption of network slice i after joint VNF ​​slicing and hybrid backup is modeled as: When the actual reliability of VNFv does not meet the expected reliability, first look for shared backup VNFs, and by constraining the maximum number of shares and the number of link hops after backup sharing, meet the requirements of different delay constraints; Let the binary variable q i,u,v Denote v∈V i With u∈V i Whether to share backup; The resource consumption of network slice i after joint VNF ​​slicing and hybrid backup sharing is modeled as: When the number of VNFs increases, the resource consumption of building backup VNFs can be reduced by sharing backup VNFs, thereby reducing the resource consumption of network slice deployment.

10. The network slice deployment method for joint VNF ​​partitioning and hybrid backup sharing according to claim 1 is characterized in that: The network slice deployment constraints, VNF partition constraints and hybrid backup sharing constraints are modeled as follows: Let the binary variable p i,u,v Denote v∈V i With u∈V i Are they of the same type? (1) Modeling VNF backup instance sharing constraints: (2) Modeling shared backup instance resource constraints: (3) Modeling sharing quantity restrictions: (4) Modeling VNF deployment constraints: (5) Modeling CPU resource constraints: (6) Modeling storage resource constraints: (7) Modeling bandwidth resource constraints: (8) Modeling flow conservation constraints: (9) Modeling end-to-end delay constraints: (10) Modeling reliability constraints: (11) Modeling Constraints Integrity Restrictions:

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