Method and system for optimizing resource allocation in RAN (Radio Access Network) slice

Abstract

The invention belongs to the field of communication, and relates to a method and a system for optimizing resource allocation in an RAN (Radio Access Network) slice. The method comprises the following steps: receiving an RAN (Radio Access Network) slicing request, wherein the RAN slicing request comprises a plurality of virtual network functions and corresponding virtual links; constructing a first priority list based on the resource demand or link degree of each virtual network function in the RAN slice request; constructing a second priority list based on available resources of each underlying node in the underlying network; and mapping each virtual network function to a corresponding bottom layer node by adopting a preset RS configuration scheme based on the first priority list and the second priority list. According to the method, the complex relation and interdependence between the bottom layer network nodes are concerned, so that the resource utilization efficiency is improved, internal fragmentation is avoided, the link requirement and bandwidth requirement between virtual network functions are met, and the overall performance of the network and the user experience are improved.

Description

Technical Field

[0001] The present invention belongs to the field of communications, and in particular relates to a method and system for optimizing resource allocation in RAN slices. Background Art

[0002] In recent years, Radio Access Network (RAN) slicing has become one of the most important and promising technologies in 5G network architecture. RAN slicing achieves efficient resource utilization and flexible management by dividing physical network resources into multiple independent and programmable virtual network slices. Each of these slices operates as an independent logical mobile network, provides specific types of services, and is isolated from other slices. In this way, different service providers can run their own virtual networks on a shared physical infrastructure, thereby reducing costs and improving resource utilization efficiency. Each RAN slice can be optimized and configured according to specific application requirements to provide customized services. For example, more spectrum resources can be allocated for applications with high bandwidth requirements, while the transmission path of the slice can be optimized for low-latency applications. This flexible resource configuration method greatly improves the service capabilities and economic benefits of the network.

[0003] Network Function Virtualization (NFV) plays a key role in the RAN slicing process, enabling various virtual network functions (VNFs) to be flexibly deployed and managed, thereby improving network flexibility and resource utilization. NFV technology decouples traditional network functions from dedicated hardware and runs them on general-purpose computing platforms, making the deployment and management of network functions more flexible and efficient. In this way, operators can dynamically adjust network resources according to demand, improving the adaptability and flexibility of the network. For example, NFV can virtualize functions such as packet processing and signal processing and run them on standard servers, thereby achieving dynamic scheduling and efficient utilization of resources.

[0004] Current solutions mainly focus on resource allocation, ignoring the complex relationships and interdependencies between underlying network nodes. Existing methods usually only focus on how to maximize the use of available resources, while ignoring the link requirements and bandwidth requirements between VNFs. This approach may lead to internal fragmentation of resources, and even if the total amount of resources is sufficient, it cannot meet the mapping requirements of all VNFs. For example, when multiple VNFs need to communicate with high bandwidth between underlying nodes, algorithms that only consider resource allocation may not be able to effectively meet these requirements, resulting in a decrease in network performance. In addition, traditional resource allocation algorithms often show inefficiency and lack of flexibility when dealing with large-scale networks, and are difficult to adapt to the requirements of emerging services for network efficiency and stability. In large-scale networks, the number and complexity of VNFs have greatly increased, and the computational complexity and resource requirements of traditional algorithms have also increased, resulting in limited performance in practical applications. Because these algorithms lack comprehensive consideration of VNF connectivity and bandwidth requirements, it is difficult to achieve ideal resource allocation and utilization efficiency, which affects the overall network performance and user experience. Ignoring the connectivity and bandwidth requirements between VNFs in resource allocation may also lead to an unbalanced network topology, further exacerbating resource waste and bottleneck problems. These problems have emerged in actual deployment, resulting in increased network operation and maintenance costs and reduced service quality. In general, the current technical solutions have significant deficiencies in resource allocation and cannot fully meet the needs of the 5G era for efficient, flexible and stable network services. Summary of the invention

[0005] In order to solve the problem that the prior art ignores the complex relationships and interdependencies between underlying network nodes in resource allocation, and to overcome the shortcomings of low efficiency and insufficient flexibility of traditional algorithms in large-scale networks, the purpose of the present invention is to provide a method and system for optimizing resource allocation in RAN slices, so as to solve the problem that the prior art ignores the complex relationships and interdependencies between underlying network nodes in resource allocation, thereby improving resource utilization efficiency, avoiding internal fragmentation, meeting the link requirements and bandwidth requirements between virtual network functions (VNFs), and overcoming the shortcomings of low efficiency and insufficient flexibility of traditional algorithms in large-scale networks, so as to improve the overall network performance and user experience.

[0006] In a first aspect of the present invention, the present invention provides a method for optimizing resource allocation in a RAN slice, the method comprising:

[0007] Step 1: receiving a RAN slice request, where the RAN slice request includes a plurality of virtual network functions and corresponding virtual links;

[0008] Step 2: construct a first priority list based on the resource requirements or connectivity of each virtual network function in the RAN slice request; the connectivity is the number of other virtual network functions that each virtual network function is directly connected to in the network topology;

[0009] Step 3: construct a second priority list based on the available resources of each underlying node in the underlying network;

[0010] Step 4: Based on the first priority list and the second priority list, a preset RS configuration scheme is used to map each virtual network function to a corresponding underlying node.

[0011] In a second aspect of the present invention, the present invention also provides a system for optimizing resource allocation in a RAN slice, the system comprising:

[0012] A request receiving module, configured to receive a RAN slice request, wherein the RAN slice request includes a plurality of virtual network functions and corresponding virtual links;

[0013] A first priority list building module is used to build a first priority list based on the resource requirements or connectivity of each virtual network function in the RAN slice request; the connectivity is the number of other virtual network functions that each virtual network function is directly connected to in the network topology structure;

[0014] A second priority list building module, configured to build a second priority list based on available resources of each underlying node in the underlying network;

[0015] A mapping module is used to map each virtual network function to a corresponding underlying node based on the first priority list and the second priority list using a preset RS configuration scheme.

[0016] Furthermore, the system also includes:

[0017] The resource calculation module is used to calculate the specific resource requirements of each RAN slice request and check the available resources in the current underlying network to ensure the feasibility of resource allocation; after the mapping module maps each virtual network function to the corresponding underlying node, the resource calculation module will update the remaining available resources of each underlying node in the underlying network.

[0018] Beneficial effects of the present invention:

[0019] The present invention ensures that high-priority requests can be allocated resources first. By dynamically acquiring the available resource situation, the system is ensured to have a real-time understanding of the current resource status, thereby dynamically adjusting the resource allocation method; a suitable base station is selected based on the number of links and resource requirements of the virtual network function. The present invention comprehensively considers the resource requirements, connectivity and bandwidth requirements of the virtual network function (VNF), as well as the implementation method of orderly mapping the virtual network function (VNF) to the underlying node. The best physical node is selected for mapping to ensure efficient use of resources and network stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A RAN slicing architecture provided by an example of the present invention is shown;

[0021] Figure 2 A flow chart showing a method provided by an example of the present invention;

[0022] Figure 3 Indicates the resource allocation of VNF mapping in RAN slices using the random mapping and RS configuration method provided by the example of the present invention;

[0023] Figure 4 A system architecture diagram is shown according to an example of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] In Radio Access Network (RAN), Network Slicing is a key technology that allows the creation of multiple virtual networks on the same physical network infrastructure, each of which can be customized to meet specific Quality of Service (QoS) requirements. Resource allocation is critical in RAN slicing because it directly affects the service quality and user experience of different slices. Current resource allocation schemes ignore the connectivity and bandwidth requirements between VNFs, and may also lead to an imbalance in network topology, further exacerbating resource waste and bottleneck problems.

[0026] Figure 1 It represents a RAN slice architecture provided by an example of the present invention, such as Figure 1As shown, it includes an underlying network, a mobile network operator, a slice controller and an enterprise, etc. The underlying network is responsible for providing hardware and software solutions that support slices, including but not limited to base stations, antennas, routers, switches, etc.; ensuring that the equipment can allocate resources according to different slice requirements. The mobile network operator is responsible for managing and operating the entire RAN slice network, including planning, deployment, monitoring and optimization. In this embodiment, it is mainly responsible for providing RS configuration solutions and network monitoring; the slice controller is responsible for the management of the entire network slice life cycle, including the design, creation, monitoring, modification and deletion of slices. The enterprise is used to communicate according to the resources allocated by the network; the slices may include IoT slices, Internet of Vehicles slices, and mobile broadband slices, etc. Based on the above problems, the method for optimizing resource allocation in RAN slices provided by the present invention is as follows: Figure 2 As shown, the following steps are included:

[0027] Step 1: receiving a RAN slice request, where the RAN slice request includes a plurality of virtual network functions and corresponding virtual links;

[0028] Step 2: construct a first priority list based on the resource requirements or connectivity of each virtual network function in the RAN slice request; the connectivity is the number of other virtual network functions that each virtual network function is directly connected to in the network topology;

[0029] Step 3: construct a second priority list based on the available resources of each underlying node in the underlying network;

[0030] Step 4: Based on the first priority list and the second priority list, a preset RS configuration scheme is used to map each virtual network function to a corresponding underlying node.

[0031] In step 1, the mobile network operator interacts with the enterprise and receives a RAN slice request from the enterprise. RAN slices divide the underlying resources into a set of independent programmable RAN slices through network function virtualization (NFV). A RAN slice consists of various virtual network functions (VNFs) and virtual network links, which are embedded as instances on the underlying nodes. The resource requirements of the virtual network function (VNF) include computing resources and virtual link bandwidth.

[0032] In step 2, the first priority list is constructed based on the required resources or connection degree of each virtual network function (VNF) in descending order.

[0033] In step 2, the link degree of a virtual network function refers to the number of other virtual network functions (VNFs) directly linked to a virtual network function (VNF) in the network topology, represented by |N u| represents. Each direct link between a VNF and other VNFs is called a link. For example, if a VNF is directly linked to three other VNFs, then the link degree of this VNF is 3. The resulting descending set of VNFs is represented by ξ v express.

[0034] In step 3, the construction of the base station priority list is based on the available resource value of each base station in descending order, where one base station is represented by s and its available resource value is represented by R s The resulting descending set is represented by ξ s express.

[0035] In step 4, an embodiment of the present invention proposes an RS configuration method to map a virtual network function (VNF) to a base station, and the specific steps include:

[0036] Step 4.1 builds a theoretical model of RS configuration for mapping virtual network functions (VNFs);

[0037] Assume that a given underlying network P S =(N S ,E S ), where N S represents the set of underlying nodes, E S Represents a set of links. Consider a node s∈N S , the total available resources of node s is defined as R s Among them, the underlying network represents the ground network, the underlying nodes represent the base stations on the ground network, and the links represent the connections between base stations.

[0038] Let P V For the underlying network P S The set of RAN slices running on V = {P V1 ,P V2 ,...P Vγ}.

[0039] A single RAN slice consists of P Vi =(N Vi ,E Vi )∈P V Indicates that, N Vi represents a set of virtual network functions (VNFs), E Vi Represents the set of virtual links between virtual network functions (VNFs), and the subsequent i is omitted.

[0040] For any virtual network function (VNF) u∈N V, the amount of available resources that need to be embedded on the underlying node is Θ u For any virtual link (u,v)∈E V , the required bandwidth is B (u,v) Similarly, the embodiment of the present invention considers a more general situation: limiting the underlying network P S The links in have an available capacity constraint matrix C, which specifies the maximum bandwidth C that can be allocated to all virtual links mapped to (s, t). (s,t) .

[0041] Introduce a binary variable M vt , if M vt =1, it means that the virtual network function (VNF) v is currently embedded in the underlying node t, otherwise it is 0. At the same time, another binary variable mapping variable M is introduced us To represent the decision of mapping a virtual network function (VNF) u to the underlying node s, when M us =1, indicating that the virtual network function (VNF) u is mapped to the underlying node s, otherwise M us =0.

[0042] When setting up a network, all virtual network functions (VNFs) must be mapped to the underlying nodes. To ensure that all VNFs can be embedded, the value of the binary mapping variable can be obtained as follows:

[0043]

[0044] The embodiment of the present invention judges the performance of the mapping plan according to the number of successfully embedded virtual network functions (VNFs), and defines the optimization problem of RS configuration as:

[0045]

[0046] The embodiment of the present invention defines a mapping plan MC={M us} represents a possible mapping solution in RAN slice.

[0047] The resource allocation of VNF mapping in RAN slices using the random mapping and RS configuration method provided in the embodiment of the present invention is as follows Figure 3 As shown in FIG. 1 . The underlying network consists of five base stations. Each base station provides four resource blocks (two frequency units in two time slots) for the RAN slice. In the figure, there are also two RAN slices, each of which consists of multiple virtual network functions (VNFs). Both slices use the same underlying cellular network resources. The embodiment of the present invention takes into account the resource requirements of VNFs. Each VNF requires a certain amount of resources when embedded in the underlying node, where Θ U1 = 2 resource blocks, Θ U2 =ΘG1 =Θ G3 , Θ G2 = 1 resource block (25% of the underlying node resources).

[0048] Specifically, if a virtual network function (VNF) requires 25% of the spectrum resources, the underlying node should provide 25% of the resource blocks to the virtual network function (VNF). In the figure, the solid line between any two virtual network functions (VNF) in a slice indicates that they are neighbors (e.g., (U1, U2), (G1, G2), (G1, G3) and (G2, G3)). The above relationship means that for any virtual network function (VNF) u∈N v , the underlying node it can embed must be the underlying node embedded by its neighbor or one of its neighbors. At the same time, the following constraints need to be met:

[0049]

[0050]

[0051] in, It means that two virtual network functions (VNFs) u and v are simultaneously mapped to two underlying nodes s and t.

[0052]

[0053] That is, the total bandwidth allocated on the underlying link does not exceed its link capacity.

[0054]

[0055] That is, the available resources of any underlying node s are sufficient.

[0056] Step 4.2 uses an efficient mapping algorithm;

[0057] Among them, the RS configuration method proposes four algorithms to solve the resource allocation and virtual network function (VNF) embedding problems. The four algorithms can be executed in the following ways:

[0058] The resource priority algorithm is to prioritize embedding virtual network functions (VNFs) with large resource requirements based on the amount of resources required by the virtual network functions (VNFs).

[0059] Input: P S (Basic Network Diagram), P V (Virtual Network Functional Diagram);

[0060] Output: MC (mapping plan);

[0061] Initialize an empty mapping collection:

[0062] Build a priority list based on the resource requirements of virtual network functions (VNFs) v ;

[0063] According to the available resource value of the node, build a priority list ξ s ;

[0064] When V If not empty, perform the following steps:

[0065] Take V The element u with the highest resource demand;

[0066] Execute EmbeddingVNF(u,ξ S ,MC) process;

[0067] From V Remove u from the

[0068] Return to MC.

[0069] In this embodiment, an empty mapping set (MC) is first initialized; a first priority list ξ can be constructed according to the resource requirements of the virtual network function (VNF). v ; According to the available resource value of the node, build the second priority list ξ s ; By traversing the first priority list ξ v , mapping each virtual network function (VNF) to the underlying node with optimal resources and meeting the conditions.

[0070] The link priority algorithm is as follows: based on the link degree of the virtual network function (VNF), the virtual network function (VNF) with high link degree is preferentially embedded.

[0071] Input: P S (Basic Network Diagram), P V (Virtual Network Functional Diagram);

[0072] Output: MC (mapping plan);

[0073] Initialize an empty mapping collection:

[0074] Construct a descending set of virtual network functions (NFV) according to the link degree value ξ V ;

[0075] Construct a descending set of basic nodes based on the available resource values ​​ξ S ;

[0076] When V When not empty, perform the following steps:

[0077] TakeV The element with the highest link degree value;

[0078] Execute EmbeddingVNF(u,ξ S ,MC) process;

[0079] From V Remove u from the

[0080] Return to MC.

[0081] In this embodiment, an empty mapping set (MC) is first initialized; a first priority list ξ is constructed according to the link degree value of the virtual network function (VNF). v ; According to the available resource value of the node, build the second priority list ξ s ; Traverse the first priority list ξ v , mapping each virtual network function (VNF) to the underlying node with optimal resources and meeting the conditions.

[0082] The group priority algorithm considers the resource requirements of a virtual network function (VNF) and the resource requirements of its neighboring virtual network functions (VNFs) and embeds them in groups.

[0083] Input: P S (Basic Network Diagram), P V (Virtual Network Functional Diagram);

[0084] Output: MC (mapping plan);

[0085] Initialize an empty mapping collection:

[0086] Construct descending set ξ according to cluster size V ;

[0087] (here Among them, each Is a VNFu i and its associated VNF collection. )

[0088] Construct a descending set of basic nodes based on the available resource values ​​ξ S ;

[0089] When V When not empty, perform the following steps:

[0090] Take V The first element in ;

[0091] To N u+ For each element u in , the EmbeddingGroup(u,MC) process is executed;

[0092] From V Remove N u+ ;

[0093] Return to MC.

[0094] In this embodiment, an empty mapping set (MC) is first initialized; the virtual network function (VNF) is divided into multiple groups, and a descending set (ξ v );Build a priority list based on the available resource value of the nodeξ s ; Traverse ξ v , mapping each virtual network function (VNF) to the underlying node with optimal resources and meeting the conditions.

[0095] The group link priority algorithm combines the link degree and resource requirements of the virtual network function (VNF) and optimizes the embedding in groups.

[0096] Input: P S (Basic Network Diagram), P V (Virtual Network Functional Diagram);

[0097] Output: MC (mapping plan);

[0098] Initialize an empty mapping collection:

[0099] Evaluate the value v(T) of all virtual network functions;

[0100] (here represents the sum of the resource values ​​of all virtual network functions, where v * Represents v's neighbor VNF)

[0101] Build a descending list of clustersξ V ;

[0102] When V When not empty, perform the following steps:

[0103] Take V The first element N in u+ ;

[0104] To N u+ For each element u in , the EmbeddingGroup(u,MC) process is executed;

[0105] From V Remove N u+ ;

[0106] Return to MC.

[0107] This embodiment first initializes an empty mapping set (MC); constructs a descending set based on the size and linkage degree of each cluster (ξ v );Build a priority list based on the available resource value of the nodeξ s ; Traverse ξ v , mapping each virtual network function (VNF) to the underlying node with optimal resources and meeting the conditions.

[0108] The above four algorithms need to perform the following steps during the traversal process:

[0109] Calculate the remaining resource value M of each node s ;

[0110] Update the remaining resource value of the node (R S =M s ).

[0111] In a preferred embodiment of the present invention, the present invention can also use a machine learning algorithm to optimize the resource allocation process, including: collecting historical data, training a machine learning model to predict future resource requirements, and dynamically adjusting the resource allocation strategy based on the prediction results. The machine learning algorithm includes a reinforcement learning algorithm, which improves the efficiency of resource allocation through continuous learning and adjustment.

[0112] The resource allocation system for optimizing RAN slices provided by the present invention is as follows: Figure 4 As shown, it includes the following modules:

[0113] A request receiving module, configured to receive a RAN slice request, wherein the RAN slice request includes a plurality of virtual network functions and corresponding virtual links;

[0114] The request receiving module is responsible for receiving resource requests from various enterprises or users, including the required virtual network functions (VNFs) and their related resource requirements and performance requirements. This module can receive multiple slice requests and pass these requests to the first priority list building module and the second priority list module for processing.

[0115] A first priority list building module is used to build a first priority list based on the resource requirements or connectivity of each virtual network function in the RAN slice request; the connectivity is the number of other virtual network functions that each virtual network function is directly connected to in the network topology structure;

[0116] In the embodiment of the present invention, the first priority list construction module generates a priority list according to the received request for priority sorting of resource allocation to ensure that high priority requests can obtain resource allocation first.

[0117] A second priority list building module, configured to build a second priority list based on available resources of each underlying node in the underlying network;

[0118] In an embodiment of the present invention, the second priority list construction module constructs a second priority list based on the first priority list and based on the available resources of each underlying node in the underlying network; it can be used for priority sorting of resource allocation to ensure that high priority requests can get priority resource allocation.

[0119] A mapping module is used to map each virtual network function to a corresponding underlying node based on the first priority list and the second priority list using a preset RS configuration scheme.

[0120] The mapping module is responsible for mapping virtual network functions (VNFs) and virtual links to actual physical resources to achieve resource allocation. This module selects appropriate base stations based on the number of links and resource requirements of the virtual network functions. It comprehensively considers the resource requirements and link conditions of each virtual network function (VNF) and selects the best physical node for mapping to ensure efficient resource utilization and network stability.

[0121] In a preferred embodiment of the present invention, the present invention may further include a resource calculation module:

[0122] The resource calculation module calculates the specific resource requirements for each request and checks the available resources in the current network to ensure the feasibility of resource allocation. After the mapping module performs the mapping operation, the resource calculation module updates the remaining resource value of the base station to reflect the changes in resource usage. This ensures that the system has real-time understanding of the current resource status and can make dynamic adjustments.

[0123] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0124] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical module division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0125] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be obtained according to actual needs to achieve the purpose of the solution of this embodiment.

[0126] In addition, each module unit in each embodiment of the present application can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software module units.

[0127] If the integrated unit is implemented in the form of a software module unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program code.

[0128] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the present invention may be implemented in hardware, software, firmware, or any combination thereof. When implemented using software, the functions may be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of a computer program from one place to another. The storage medium may be any available medium that a general or special-purpose computer can access.

[0129] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for optimizing resource allocation in a RAN slice, characterized in that: The method comprises: Step 1: receiving a RAN slice request, where the RAN slice request includes a plurality of virtual network functions and corresponding virtual links; Step 2: construct a first priority list based on the resource requirements or connectivity of each virtual network function in the RAN slice request; the connectivity is the number of other virtual network functions that each virtual network function is directly connected to in the network topology; Step 3: construct a second priority list based on the available resources of each underlying node in the underlying network; Step 4: Based on the first priority list and the second priority list, a preset RS configuration scheme is used to map each virtual network function to a corresponding underlying node.

2. The method for optimizing resource allocation in RAN slices according to claim 1, characterized in that: The solution model of the preset RS configuration scheme includes: Among them, M us represents the decision of mapping virtual network function u to the underlying node s. us =1, indicating that the virtual network function u is mapped to the underlying node s, otherwise M us =0; N S Represents the set of underlying nodes; N V Represents a collection of virtual network functions; represents the decision of mapping two virtual network functions u and v to two underlying nodes s and t at the same time; when , it means that the virtual network functions u and v are mapped to two underlying nodes s and t at the same time, otherwise M vt represents the decision of the virtual network function v currently embedded in the underlying node t. vt =1, indicating that the virtual network function v is currently embedded in the underlying node t, otherwise M vt =0;P V Represents the set of RAN slices running on the underlying network; B (u,v) represents the bandwidth resources required by the virtual link (u, v) composed of two virtual network functions u and v, C (s,t) represents the maximum bandwidth resource required to allocate to the physical link mapped to the two underlying nodes s and t, (s, t) represents the physical link composed of the two underlying nodes s and t, E S represents the set of physical links of the underlying node s; Θ u represents the amount of available resources embedded in the underlying node s; R s Indicates the total amount of available resources of the underlying node s.

3. The method for optimizing resource allocation in RAN slices according to claim 2, characterized in that: The solution method of the preset RS configuration scheme includes a resource priority algorithm, a link priority algorithm, a group priority algorithm or a group link priority algorithm.

4. The method for optimizing resource allocation in RAN slices according to claim 2, characterized in that: The preset RS configuration scheme includes embedding a virtual network function and embedding a virtual network group.

5. The method for optimizing resource allocation in RAN slices according to claim 4, characterized in that: The embedded virtual network function includes calculating the resource accumulation value of each bottom-level node according to the total available resources of each bottom-level node and the total available resources of its neighboring nodes; Calculate the cumulative value of resource requirements of the current virtual network function according to the resource requirements of each virtual network function; if all neighbor nodes of the current virtual network function are not mapped to any underlying node, select an underlying node from the underlying resource set so that the difference between the cumulative value of resources of the selected underlying node and the cumulative value of resource requirements of the current virtual network function is minimized, update the available resource capacity of the selected underlying node, map the current virtual network function to the selected underlying node, and update the mapping set; If some neighbor nodes of the current virtual network function have been mapped to some underlying nodes, the adjacent nodes of some neighbor nodes are constructed into a new underlying node set; an underlying node is selected from the new underlying node set so that the difference between the resource accumulation value of the selected underlying node and the resource demand accumulation value of the current virtual network function is minimized and the bandwidth requirement is met, the available resource capacity of the selected underlying node is updated, and the current virtual network function is mapped to the selected underlying node, and the mapping set is updated.

6. The method for optimizing resource allocation in RAN slices according to claim 4, characterized in that: The embedding of the virtual network group includes calculating the resource accumulation value of each underlying node according to the total available resources of each underlying node and the total available resources of its neighboring nodes; calculating the resource demand accumulation value of the current virtual network function according to the resource demand of each virtual network function in the virtual network function; if all neighboring nodes of the current virtual network function are not mapped to any underlying node, selecting an underlying node from the underlying resource set so that the difference between the resource accumulation value of the selected underlying node and the resource demand accumulation value of the current virtual network function is minimized, updating the available resource capacity of the selected underlying node, and mapping the current virtual network function to the selected underlying node, and updating the mapping set; If some neighbor nodes of the current virtual network function have been mapped to some underlying nodes, the adjacent nodes of some neighbor nodes are constructed into a new underlying node set; a bottom-level node is selected from the new bottom-level node set so that the difference between the resource accumulation value of the selected bottom-level node and the resource demand accumulation value of the current virtual network function is minimized and the bandwidth requirement is met, the available resource capacity of the selected bottom-level node is updated, and the current virtual network function is mapped to the selected bottom-level node, and the mapping set is updated.

7. A system for optimizing resource allocation in a RAN slice, characterized in that: The system comprises: A request receiving module, configured to receive a RAN slice request, wherein the RAN slice request includes a plurality of virtual network functions and corresponding virtual links; A first priority list building module is used to build a first priority list based on the resource requirements or connectivity of each virtual network function in the RAN slice request; the connectivity is the number of other virtual network functions that each virtual network function is directly connected to in the network topology structure; A second priority list building module, configured to build a second priority list based on available resources of each underlying node in the underlying network; A mapping module is used to map each virtual network function to a corresponding underlying node based on the first priority list and the second priority list using a preset RS configuration scheme.

8. A system for optimizing resource allocation in RAN slices according to claim 7, characterized in that: The system further comprises: The resource calculation module is used to calculate the specific resource requirements of each RAN slice request and check the available resources in the current underlying network to ensure the feasibility of resource allocation; after the mapping module maps each virtual network function to the corresponding underlying node, the resource calculation module will update the remaining available resources of each underlying node in the underlying network.

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