Deployment method and device of service function chain, equipment and storage medium

Abstract

The invention relates to a service function chain deployment method and device, equipment and a storage medium, and relates to the field of multi-domain network orchestration. The method comprises the following steps: acquiring a target service function sub-chain of a target domain network based on a chain cutting scheme of a service function chain; generating a plurality of candidate paths corresponding to the target service function sub-chain under the constraint of a first constraint condition; taking minimization of intra-domain communication time delay and resource occupancy rate standard deviation as optimization targets, and generating an optimal VNF instantiation scheme corresponding to each candidate path through a particle swarm optimization algorithm; determining a target path and an optimal VNF instantiation scheme of the target path based on the optimal VNF instantiation scheme corresponding to each candidate path; deploying a target service function subchain in the target domain network based on the target path and the optimal VNF instantiation scheme of the target path; according to the method, the intra-domain link distribution effect is improved, and the overall stability and efficiency of the network are improved.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of multi-domain network orchestration, and in particular to a method, apparatus, device, and storage medium for deploying a service function chain. Background Art

[0002] Network Function Virtualization (NFV) enables flexible deployment of network services on servers. A network service in NFV can be represented as a Service Function Chain (SFC), which consists of a series of Virtual Network Functions (VNFs) in a given order. In order to provide efficient services, SFCs are deployed in multiple different servers and guide traffic through a group of VNFs in a specific order.

[0003] In NFV networks, SFC can be flexibly deployed. However, flexible path selection and VNF deployment solution selection also make the SFC deployment problem an NP-hard problem. Summary of the invention

[0004] The embodiments of the present application provide a method, apparatus, device and storage medium for deploying a service function chain, which can improve the distribution effect of links within a domain, achieve balanced distribution of VNFs on each physical node, and improve the overall stability and efficiency of the network. The technical solution is as follows.

[0005] On the one hand, a method for deploying a service function chain is provided, the method being executed by a domain controller of a target domain network, the target domain network being any one domain network in a multi-domain network, the method comprising: A target service function subchain of the target domain network is obtained based on a service function chain severance scheme; the severance scheme is used to indicate that the service function chain is severanced into a plurality of service function subchains corresponding to the multi-domain networks; the target service function subchain includes resource requirements of each virtual network function VNF allocated to the target domain network; Under the constraint of a first constraint condition, a plurality of candidate paths corresponding to the target service function subchain are generated; the first constraint condition is constructed based on the physical nodes in the target domain network and the remaining amount of resources of each physical node; Taking minimizing the intra-domain communication delay and the standard deviation of resource utilization as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF instantiation scheme corresponding to each candidate path; wherein the VNF instantiation scheme is used to indicate the VNF deployment status of each physical node on the candidate path; Determine a target path and an optimal VNF instantiation scheme for the target path based on the optimal VNF instantiation scheme corresponding to each candidate path; Based on the target path and the optimal VNF instantiation scheme for the target path, the target service function subchain is deployed in the target domain network.

[0006] On the other hand, a method for deploying a service function chain is provided, the method being executed by a main controller of a multi-domain network, the multi-domain network comprising at least two domain networks, the method comprising: Generate a chain cutting scheme for a service function chain; the chain cutting scheme is used to indicate that the service function chain is cut into a plurality of service function sub-chains corresponding to the multi-domain network; The chain cutting plan is sent to the intra-domain controllers of each domain network so that each intra-domain controller obtains the corresponding service function sub-chain. For any intra-domain controller of the target domain network, multiple candidate paths corresponding to the target service function sub-chain are generated under the constraint of the first constraint condition; with minimizing the intra-domain communication delay and the standard deviation of resource occupancy rate as the optimization goal, the optimal VNF instantiation plan corresponding to each candidate path is generated through the particle swarm optimization algorithm, and the target path and the optimal VNF instantiation plan of the target path are determined based on the optimal VNF instantiation plan corresponding to each candidate path; based on the optimal VNF instantiation plan corresponding to each candidate path, the target path and the optimal VNF instantiation plan of the target path are determined; based on the target path and the optimal VNF instantiation plan of the target path, the target service function sub-chain is deployed in the target domain network.

[0007] On the other hand, a deployment device for a service function chain is provided, the device is applied in a domain controller of a target domain network, the target domain network is any domain network in a multi-domain network, and the device includes: a link acquisition module, configured to acquire a target service function subchain of the target domain network based on a service function chain severance scheme; the severance scheme is configured to indicate that the service function chain is severanced into a plurality of service function subchains corresponding to the multi-domain networks; the target service function subchain includes resource requirements of each virtual network function VNF allocated to the target domain network; A path generation module, used to generate multiple candidate paths corresponding to the target service function subchain under the constraint of a first constraint condition; the first constraint condition is constructed based on the physical nodes in the target domain network and the resource surplus of each physical node; The first solution generation module is used to generate the optimal VNF instantiation solution corresponding to each candidate path by using a particle swarm optimization algorithm with the optimization goal of minimizing the intra-domain communication delay and the standard deviation of resource occupancy; wherein the VNF instantiation solution is used to indicate the VNF deployment status of each physical node on the candidate path; A determination module, configured to determine a target path and an optimal VNF instantiation scheme for the target path based on the optimal VNF instantiation scheme corresponding to each candidate path; A deployment module is used to deploy the target service function subchain in the target domain network based on the target path and the optimal VNF instantiation scheme of the target path.

[0008] In a possible implementation, the first solution generating module includes: An initialization submodule is used to initialize a particle swarm optimization algorithm based on a target candidate path; a particle population in the particle swarm optimization algorithm is a set of VNF instantiation schemes on the corresponding candidate path, and a particle in the particle population represents a VNF instantiation scheme; the target candidate path is any one of each candidate path; The iterative adjustment submodule is used to iteratively adjust the particle position of each particle based on the particle speed update mechanism in the particle swarm optimization algorithm until the optimization target is met, thereby obtaining the optimal VNF instantiation solution corresponding to the target candidate path.

[0009] In a possible implementation, the iterative adjustment submodule is used to: In each iterative adjustment process, the fitness value of each particle is calculated by the fitness function, and the fitness value is a comprehensive value of the communication delay within the domain and the standard deviation of the resource occupancy rate corresponding to the particle; The VNF instantiation scheme represented by the particle with the smallest fitness value in the iterative adjustment is determined as the optimal VNF instantiation scheme corresponding to the target candidate path.

[0010] In a possible implementation, the iterative adjustment submodule is used to: Under the constraint of the second constraint condition, the particle position of each particle is iteratively adjusted based on the particle velocity update mechanism in the particle swarm optimization algorithm; The second constraint condition includes: The physical node where the VNF is deployed is within the path range of the target candidate path; The execution order between VNFs remains unchanged.

[0011] In a possible implementation, the path generation module includes: A node acquisition submodule, used to acquire a source node and a destination node of the target service function subchain; the source node is a routing node connecting the target service function subchain with a previous domain network; the destination node is a routing node connecting the target service function subchain with a subsequent domain network; The path generation submodule is used to generate the shortest path based on the source node and the destination node of the target service function subchain and under the constraint of the first constraint condition through the KSP algorithm to obtain multiple candidate paths corresponding to the target service function subchain.

[0012] In a possible implementation manner, the first constraint condition includes: VNFs are inseparable; At most one VNF is deployed on each physical node; The candidate path passes through a target physical node, where the target physical node is a physical node for providing VNF services for the target service function subchain; The total resource consumption corresponding to the candidate paths is less than or equal to the remaining resources of the target domain network.

[0013] On the other hand, a deployment device for a service function chain is provided, the device is applied in a main controller of a multi-domain network, the multi-domain network includes at least two domain networks, and the device includes: A second solution generating module generates a chain cutting solution for the service function chain; the chain cutting solution is used to indicate that the service function chain is cut into a plurality of service function sub-chains corresponding to the multi-domain network; A scheme sending module is used to send the chain cutting scheme to the intra-domain controllers of each domain network so that each intra-domain controller obtains the corresponding service function sub-chain. For any intra-domain controller of the target domain network, multiple candidate paths corresponding to the target service function sub-chain are generated under the constraint of the first constraint condition; with minimizing the intra-domain communication delay and the standard deviation of resource occupancy rate as the optimization goal, the optimal VNF instantiation scheme corresponding to each candidate path is generated by the particle swarm optimization algorithm, based on the optimal VNF instantiation scheme corresponding to each candidate path, the target path and the optimal VNF instantiation scheme of the target path are determined, based on the optimal VNF instantiation scheme corresponding to each candidate path, the target path and the optimal VNF instantiation scheme of the target path are determined; based on the target path and the optimal VNF instantiation scheme of the target path, the target service function sub-chain is deployed in the target domain network.

[0014] In a possible implementation manner, the device further includes: A request receiving module, configured to receive a service function chain deployment request before the second solution generating module generates a chain cutting solution for the service function chain, wherein the service function chain deployment request includes the number and execution order of VNFs, the source node and destination node of the service function chain, and the resource demand of each VNF; A resource quantity acquisition module is used to obtain the inter-domain communication delay between each domain network and the remaining resources of each domain network; The link determination module is used to determine the service function chain from the source node to the destination node of the service function chain based on the inter-domain communication delay between each domain network, the remaining resources of each domain network and the resource demand of each VNF; the total inter-domain communication delay of the service function chain is the shortest.

[0015] On the other hand, a computer device is provided, which includes a processor and a memory, wherein the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor to implement any of the above-mentioned service function chain deployment methods.

[0016] On the other hand, a computer-readable storage medium is provided, in which at least one computer program is stored, and the computer program is loaded and executed by a processor to implement any of the above-mentioned service function chain deployment methods.

[0017] On the other hand, a computer program product is provided, which includes at least one computer program, and the computer program is loaded and executed by a processor to implement a deployment method for providing any service function chain in the above-mentioned various optional implementations.

[0018] The technical solution provided by this application may have the following beneficial effects: In the deployment method of the service function chain provided in the embodiment of the present application, the domain controller of any target domain network in the multi-domain network obtains the target service function subchain of the target domain network from the chain cutting plan of the service function chain, and generates multiple candidate paths corresponding to the target service function subchain under the constraint of the first constraint condition constructed by comprehensively considering the physical nodes of the target domain network and the resource surplus of each physical node, and then, with the minimization of the intra-domain communication delay and the standard deviation of the resource occupancy rate as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF solution corresponding to each candidate path, and then the optimal target path and the corresponding optimal VNF solution compared with the target domain network are determined, and the target service function subchain is deployed in the target domain network based on the target path and the optimal VNF instantiation solution of the target path; through the above method, reasonable candidate paths can be generated in combination with the actual physical node resource status of the target domain network to avoid deployment solutions that are infeasible due to resource limitations, and when the VNF is determined When instantiating the solution, the two key indicators of intra-domain communication delay and resource utilization standard deviation were taken into consideration. The particle swarm optimization algorithm was used to determine the solution with better performance, so that the network can not only ensure the timeliness of data transmission during operation, but also improve the allocation effect of intra-domain links, achieve balanced allocation of VNFs on each physical node, and improve the overall stability and efficiency of the network.

[0019] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0021] Figure 1 A flow chart showing a method for deploying a service function chain provided by an exemplary embodiment of the present application is shown; Figure 2 A flowchart showing a method for deploying a service function chain provided by another exemplary embodiment of the present application is shown; Figure 3 A schematic diagram of a multi-domain network architecture provided by an exemplary embodiment of the present application is shown; Figure 4 A flowchart showing a method for deploying a service function chain provided by another exemplary embodiment of the present application is shown; Figure 5 A flowchart of an optimal path selection process based on a KSP algorithm provided by an exemplary embodiment of the present application is shown; Figure 6 A flowchart of an optimal VNF solution for generating candidate paths provided by an exemplary embodiment of the present application is shown; Figure 7 A block diagram of a deployment device for a service function chain provided by an exemplary embodiment of the present application is shown; Figure 8 A block diagram of a deployment device for a service function chain provided by another exemplary embodiment of the present application is shown; Fig. 9 A structural block diagram of a computer device shown in an exemplary embodiment of the present application is shown; Fig.10 A structural block diagram of a computer device shown in another exemplary embodiment of the present application is shown. DETAILED DESCRIPTION

[0022] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0023] The embodiment of the present application provides a deployment method of a service function chain, which involves the cutting of the service function chain and the deployment of the service function sub-chain within the domain. Figure 1 A flowchart of a method for deploying a service function chain provided by an exemplary embodiment of the present application is shown. The method is executed by a domain controller in a target domain network. The target domain network is any domain network in a multi-domain network, such as Figure 1 As shown, the method may include the following steps: Step 110, obtaining a target service function subchain of the target domain network based on a service function chain cutting scheme; the chain cutting scheme is used to indicate that the service function chain is cut into multiple service function subchains corresponding to the multi-domain networks; the target service function subchain includes resource requirements of each virtual network function VNF allocated to the target domain network.

[0024] Service function chaining is a network service architecture concept that connects a series of virtual network functions in a specific order to achieve customized processing of network traffic, such as performing firewall detection, intrusion detection, traffic optimization and other functions on data packets in sequence to ensure that network services can meet diverse needs. Virtual network functions are the functions of traditional physical network devices (such as firewalls, routers, etc.) implemented through software virtualization. They run on general-purpose server and other hardware platforms, can be flexibly deployed and adjusted, and provide basic components for building flexible and changeable network services.

[0025] The service function chain cutting scheme is designed to adapt to the multi-domain network environment. It divides the complete service function chain according to certain rules and strategies. The purpose is to divide the entire service function chain into multiple parts so that each part (i.e., service function sub-chain) can correspond to different domain networks for subsequent processing, so as to facilitate multi-domain collaboration to complete the overall network service function.

[0026] After the domain controller of the target domain network obtains the chain switching plan of the service function chain, it can determine its own target service function sub-chain from the chain switching plan. The target service function sub-chain records the resource requirements of each virtual network function allocated to the target domain network, which includes computing resource requirements and bandwidth resource requirements. Among them, the computing resource requirement is a quantitative indicator of the computing power resources consumed to realize the virtual network function, such as the number of CPU cores, etc.; the bandwidth resource requirement is a quantitative value of the network bandwidth resources occupied to realize the virtual network function, which can be measured in units of the amount of data that can be transmitted per second, indicating the size of the network bandwidth that the VNF expects to use per unit time.

[0027] Step 120, under the constraint of the first constraint condition, generate multiple candidate paths corresponding to the target service function subchain; the first constraint condition is constructed based on the physical nodes in the target domain network and the resource surplus of each physical node.

[0028] Among them, the first constraint condition is a restriction rule constructed by comprehensively considering the physical node conditions in the target domain network and the current remaining available resources of each physical node. It is used to ensure that the generated candidate path is within the range that the actual resources of the target domain network can carry, avoid generating paths that do not conform to the actual resource conditions, and ensure the feasibility of subsequent path selection and VNF deployment.

[0029] Physical nodes are network device nodes in the network environment, such as routers, servers, switches and other hardware devices. They are the actual carriers of VNFs and network traffic transmission.

[0030] After obtaining the target service function subchain, the domain controller generates multiple candidate paths corresponding to the target service function subchain based on the first constraint condition. In one possible implementation, each candidate path needs to satisfy the requirement that the number of physical nodes passed through is greater than or equal to the number of VNFs allocated to the target domain network to ensure that there are enough physical nodes to carry these VNFs, providing multiple possible selection paths for the subsequent reasonable instantiation of VNFs, thereby facilitating the selection of the optimal solution.

[0031] Step 130, with minimizing the intra-domain communication delay and the standard deviation of resource utilization as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF instantiation scheme corresponding to each candidate path; wherein the VNF instantiation scheme is used to indicate the VNF deployment status of each physical node on the candidate path.

[0032] Intra-domain communication delay refers to the time delay taken for network data to be transmitted from the source point to the target point through a series of physical nodes in the target domain network content. It is affected by many factors such as the processing power of the physical nodes, link bandwidth, network congestion, etc. The smaller the communication delay, the higher the real-time performance and service quality of the network.

[0033] The standard deviation of resource occupancy is a statistical indicator used to measure the degree of dispersion of resource occupancy of each physical node, that is, an indicator used to measure the load balancing status of the network. For example, different physical nodes have different occupancy ratios for computing resources, bandwidth resources, etc. The degree of balance of such resource allocation can be reflected by calculating their standard deviation. The smaller the standard deviation, the more balanced the allocation of resources on each physical node, which is conducive to the stable and efficient operation of the entire network.

[0034] Particle Swarm Optimization (PSO) is an optimization algorithm based on swarm intelligence. It simulates the characteristics of group behaviors such as bird foraging. It uses multiple particles (which can be compared to different candidate path solutions in this scenario) to continuously move and update their positions in the search space (that is, continuously adjust the VNF instantiation solution corresponding to the candidate path). In other words, the VNF solution is a solution for planning the VNF deployment of each physical node on the candidate path. It specifies which VNFs should be deployed on each physical node in the candidate path, as well as the specific configuration parameters of each VNF (such as the amount of allocated computing resources, the required network bandwidth quota, etc.); according to the pre-set optimization goal (here, minimizing the communication delay within the domain and the standard deviation of resource utilization), the optimal solution is found, and finally the relatively optimal VNF instantiation solution under each candidate path is determined.

[0035] For each candidate path generated, the particle swarm optimization algorithm is used to generate the corresponding optimal VNF instantiation scheme with the optimization goal of minimizing the intra-domain communication delay and the standard deviation of resource occupancy. In this process, each candidate path can be used as a search space, and the particles in the particle swarm optimization algorithm (representing different VNF ​​deployment attempts) continuously explore and adjust in the search space. According to the resource conditions of each physical node on the current path, the connection relationship between nodes and other information, different VNF ​​deployment position combinations (i.e. different VNF ​​instantiation schemes) are tried. Through repeated iterative calculations, the VNF instantiation scheme that minimizes the intra-domain communication delay and the standard deviation of resource occupancy is found, so as to optimize the performance of the candidate path, which is more in line with the requirements of efficient and stable network operation, and finally the optimal VNF instantiation scheme corresponding to each path is obtained.

[0036] Step 140, based on the optimal VNF instantiation scheme corresponding to each candidate path, determine the target path and the optimal VNF instantiation scheme for the target path.

[0037] After obtaining the optimal VNF instantiation scheme corresponding to each candidate path through the particle swarm optimization algorithm, it is necessary to comprehensively compare these candidate paths and determine the most suitable target path and its corresponding optimal VNF instantiation scheme. This determination process can be a comprehensive comparison of the performance of each candidate path in terms of communication delay, resource occupancy balance, etc., such as comparing the numerical values ​​of intra-domain communication delay and resource occupancy standard deviation corresponding to different candidate paths, selecting the candidate path with the best overall performance as the target path, and determining its corresponding VNF instantiation scheme as the optimal VNF instantiation scheme for the target path, so as to prepare for the subsequent actual deployment in the target domain network.

[0038] Step 150, based on the target path and the optimal VNF instantiation scheme for the target path, deploy the target service function subchain in the target domain network.

[0039] Based on the determined target path and the optimal VNF instantiation scheme for the target path, the intra-domain controller of the target domain network performs actual deployment operations within the target domain network, that is, according to the optimal VNF instantiation scheme, the corresponding VNF is deployed to each physical node involved in the target path, ensuring that the target service function sub-chain can operate normally as expected in the target domain network and realize its corresponding functions in the entire multi-domain network service function chain system, thereby ensuring the service quality and business processing capabilities of the entire multi-domain network.

[0040] In summary, in the deployment method of the service function chain provided by the embodiment of the present application, the intra-domain controller of any target domain network in the multi-domain network obtains the target service function sub-chain of the target domain network from the chain cutting plan of the service function chain, and generates multiple candidate paths corresponding to the target service function sub-chain under the constraint of the first constraint condition constructed by comprehensively considering the physical nodes of the target domain network and the resource surplus of each physical node, and then, with the minimization of the intra-domain communication delay and the standard deviation of the resource occupancy rate as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF solution corresponding to each candidate path, and then the optimal target path and the corresponding optimal VNF solution compared with the target domain network are determined, and the target service function sub-chain is deployed in the target domain network based on the target path and the optimal VNF instantiation solution of the target path; through the above method, reasonable candidate paths can be generated in combination with the actual physical node resource status of the target domain network to avoid deployment solutions that are infeasible due to resource limitations, and when the VNF is determined When instantiating the solution, the two key indicators of intra-domain communication delay and resource utilization standard deviation were taken into consideration. The particle swarm optimization algorithm was used to determine the solution with better performance, so that the network can not only ensure the timeliness of data transmission during operation, but also improve the allocation effect of intra-domain links, achieve balanced allocation of VNFs on each physical node, and improve the overall stability and efficiency of the network.

[0041] The deployment method of the service function chain provided in the present application includes two stages: formulation of a cutting plan for the service function chain and deployment of a service function sub-chain in a domain. When formulating a cutting plan for the service function chain, the chain cutting plan can be generated based on the load balancing of the domain network as a constraint. Figure 2 A flowchart of a method for deploying a service function chain provided by another exemplary embodiment of the present application is shown. The method can be composed of the cutting of the service function chain and the deployment of the service function sub-chain within the domain, such as Figure 2 As shown, the method may include the following steps.

[0042] Step 210, generating a chain cutting scheme for the service function chain; the chain cutting scheme is used to indicate that the service function chain is cut into a plurality of service function sub-chains corresponding to the multi-domain network.

[0043] In a possible implementation, the main controller may generate a chain-cutting scheme for the service function chain based on load balancing as a constraint, wherein the number of service function sub-chains in the chain-cutting scheme is the same as the number of domain networks in the multi-domain network.

[0044] Load balancing is a resource allocation strategy that can evenly distribute network loads (such as network traffic, computing tasks, etc.) to multiple network resources (such as servers, links, etc.) to avoid the situation where some resources are overused and lead to performance degradation, while other resources are idle. In the process of generating the service function chain slicing solution, using load balancing as a constraint means ensuring that the resource allocation of each service function sub-chain after slicing is relatively balanced in different domain networks, so that each domain network can reasonably undertake part of the work of the service function chain, and there will be no phenomenon that a domain network is overloaded or underloaded, thereby ensuring the stable operation and efficient service of the entire multi-domain network.

[0045] In the embodiment of the present application, the main controller can cut the service function chain according to the number of domain networks, and the cutting formula can be expressed as:

[0046] Among them, k represents the number of domain networks, and the domain networks are ordered. Indicates the load balancing of the network. The amount of computing resources that a domain network should provide, Indicates The remaining amount of computing resources owned by the domain network, It represents the remaining amount of computing resources of all domain networks. The ratio of the two can be used to obtain the resource share that the domain network should provide. Indicates the total computing resources required by the service function chain.

[0047] Assume that the computing resource requirements of each VNF in a service function chain of length M are expressed as In order to reduce the bandwidth resources and latency of inter-domain links, the chain cutting algorithm in the embodiment of the present application comprehensively considers the remaining computing resources of each domain network and the remaining computing resources of each VNF, and cuts the SFC into multiple sub-chains with the same number of domain networks, thereby determining the SFC sub-chains allocated to each domain network. Under the premise of ensuring that the number of service function sub-chains divided is the same as the number of domain networks, the computing resource requirements of each VNF are traversed in order. If and , then it can be determined that the service function subchain assigned to the first domain network is from the first VNF ​​to the VNFs, and so on, ultimately achieving maximum multi-domain network load balancing and reasonable SFC segmentation.

[0048] Step 220, sending the chain cutting plan to the intra-domain controllers of each domain network so that each intra-domain controller obtains the corresponding service function sub-chain. For any intra-domain controller of the target domain network, multiple candidate paths corresponding to the target service function sub-chain are generated under the constraint of the first constraint condition; with minimizing the intra-domain communication delay and the standard deviation of resource occupancy as the optimization goal, the optimal VNF instantiation plan corresponding to each candidate path is generated through the particle swarm optimization algorithm, based on the optimal VNF instantiation plan corresponding to each candidate path, the target path and the optimal VNF instantiation plan of the target path are determined, based on the optimal VNF instantiation plan corresponding to each candidate path, the target path and the optimal VNF instantiation plan of the target path are determined; based on the target path and the optimal VNF instantiation plan of the target path, the target service function sub-chain is deployed in the target domain network.

[0049] The main controller sends the chain cutting plan to the domain controllers of each domain network. After receiving the chain cutting plan, the domain controllers of each domain network can Figure 1 The scheme shown in the illustrated embodiment deploys the service function subchain within the domain. After each domain network completes the deployment of the corresponding service function subchain, the deployment of the service function chain is completed. The above process of determining the service function chain can comprehensively consider the inter-domain communication delay between each domain network, the remaining resources of each domain network, and the resource demand of each VNF in the service function chain in a multi-domain network environment. After receiving the service function chain deployment request containing the number of VNFs, the execution order, and the source node and destination node of the service function chain, the inter-domain communication delay between each domain network and the remaining resources of each domain network are obtained. On this basis, based on this information, the service function chain with the shortest total inter-domain communication delay from the source node to the destination node of the service function chain is determined. With load balancing as a constraint, a chain cutting scheme is generated to indicate that the service function chain is cut into multiple service function subchains corresponding to the multi-domain network, which can effectively improve the rationality and efficiency of the entire multi-domain network resource utilization, enhance the ability of the multi-domain network to cope with diversified business loads, and ensure the stability of the operation of the entire network system.

[0050] In a possible implementation, before generating a disconnection solution for the service function chain, the main controller is further configured to generate a corresponding service function chain after receiving a service function chain deployment request. The process may be implemented as follows: S201, receive a service function chain deployment request, which includes the number and execution order of VNFs, the source node and destination node of the service function chain, and the resource requirements of each VNF.

[0051] The service function chain deployment request may be initiated by an external system or user, and is a set of instruction information for creating and deploying a specific service function chain in a multi-domain network environment. The service function chain deployment request contains various parameters of the service function chain so that the multi-domain network can perform subsequent resource planning and deployment operations based on these parameters. Among them, the number of VNFs specifies the number of VNF components that need to be connected in series in the entire service function chain; the execution order of VNFs specifies the order in which network traffic flows through each VNF, and different execution orders will produce different network service effects; the source node and destination node information of the service function chain determines the entry and exit locations of the network traffic; the resource requirements of each VNF, including computing resource requirements (such as the number of CPU cores and memory capacity required for each VNF to run) and bandwidth resource requirements (the network bandwidth required for each VNF to process data traffic), etc., this information provides a basic basis for the subsequent reasonable allocation of resources and planning of service function chain paths in the multi-domain network.

[0052] The source node is the starting point for network traffic to enter the service function chain processing flow. It can be a specific server, router interface or other device with network access function in the network; the destination node is the final output point of network traffic after being processed by a series of virtual network functions (VNFs) in the service function chain. After the data packet enters the service function chain through the source node and is processed in sequence according to the prescribed VNF sequence, it finally flows to the destination node, completing the processing flow of the entire service function chain and entering the subsequent network transmission link.

[0053] In a possible implementation, the main control network can first model the underlying physical network (including intra-domain and inter-domain network topologies) and define the underlying physical network as a weighted undirected graph ,in, N Represents a collection of physical network nodes, E Represents a collection of links between physical nodes. The resource capacity is expressed as , for physical links , bandwidth resources and delay are expressed as and . Figure 3 A schematic diagram of a multi-domain network architecture provided by an exemplary embodiment of the present application is shown. Figure 3As shown, taking a multi-domain network including 5 domain networks as an example, when establishing a network, the physical nodes include two types of nodes: routing nodes and processing nodes. The routing nodes are complex in forwarding data streams between various domain networks, and the processing nodes are responsible for providing virtual network functions. Each network can include at least two routing nodes; the underlying physical network includes multiple networks and inter-domain links. In the embodiment of the present application, Indicates The network structure of a domain network, Indicates A collection of nodes in a domain network, Indicates The link set in a domain network is Represents the set of inter-domain links. Therefore, the entire multi-domain network can be connected through the set of domain networks and inter-domain links. Representation; define the service function chain as a linear chain consisting of ordered virtual network functions (VNFs) and links between them, represented as ,in They represent the source node and destination node of the service function chain respectively. At the beginning, the source node and destination node of the SFC are initialized according to the nodes in the network; It represents the demand of SFC for network functions, including the number and order of virtual network functions (VNFs) that SFC needs to use, as well as the computing resources required by each VNF, which can be expressed as ; They represent the bandwidth resource requirements of SFC respectively. Although each VNF has different computing resource requirements for physical nodes, each virtual link of a service function chain has the same bandwidth resource requirements.

[0054] Afterwards, the main controller can construct the cross-domain deployment problem of the service function chain based on the underlying modeling of the multi-domain network and the service function chain. This problem includes two sub-problems: service function chain cutting and intra-domain sub-chain deployment. S202, obtaining the inter-domain communication delay between each domain network and the remaining amount of resources of each domain network. Inter-domain communication delay refers to the time delay caused by data transmission between different domain networks in a multi-domain network architecture. Since different domain networks may differ in geographical location, network topology, network equipment performance, etc., data will be affected by many factors when it is transmitted across domain boundaries, such as link bandwidth, intermediate node processing speed, transmission distance, etc. These factors together lead to the generation of inter-domain communication delay. Inter-domain communication delay is an important indicator for measuring the efficiency of multi-domain network collaboration.

[0055] For each domain network, the remaining resources indicate the number of various network resources currently available for allocation and use in the domain network. The remaining resources include the remaining computing resources (such as the number of idle CPU cores, unoccupied memory space, etc.) and the remaining network bandwidth resources (such as the unused bandwidth capacity of each link).

[0056] S203, based on the inter-domain communication delay between each domain network, the remaining resources of each domain network and the resource demand of each VNF, determine the service function chain from the source node to the destination node of the service function chain; the total inter-domain communication delay of the service function chain is the shortest.

[0057] The main controller determines the service function chain based on the inter-domain communication delay between each network, the remaining resources of each domain network, and the resource requirements of each VNF in the service function chain deployment request. When determining the service function chain, the main controller can obtain the optimal inter-domain path from the source node to the destination node by traversing feasible paths based on the inter-domain connectivity and inter-domain communication delay, that is, the service function chain with the shortest total inter-domain communication delay, that is, the network domain passed by the obtained service function chain.

[0058] In summary, in the deployment method of the service function chain provided by the embodiment of the present application, after the main control network generates the chain cutting plan of the service function chain, it sends the chain cutting plan to each domain network, and the domain controller of any target domain network in the multi-domain network obtains the target service function subchain of the target domain network from the chain cutting plan of the service function chain, and generates multiple candidate paths corresponding to the target service function subchain under the constraint of the first constraint condition constructed by comprehensively considering the physical nodes of the target domain network and the resource surplus of each physical node, and then, with the minimization of the intra-domain communication delay and the standard deviation of the resource occupancy rate as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF solution corresponding to each candidate path, and then the optimal target path and the corresponding optimal VNF solution compared with the target domain network are determined, and the target service function subchain is deployed in the target domain network based on the target path and the optimal VNF instantiation solution of the target path; through the above method, reasonable candidate paths can be generated in combination with the actual physical node resource status of the target domain network to avoid deployment solutions that are infeasible due to resource limitations, and when the VNF is determined When instantiating the solution, the two key indicators of intra-domain communication delay and resource utilization standard deviation were taken into consideration. The particle swarm optimization algorithm was used to determine the solution with better performance, so that the network can not only ensure the timeliness of data transmission during operation, but also improve the allocation effect of intra-domain links, achieve balanced allocation of VNFs on each physical node, and improve the overall stability and efficiency of the network.

[0059] based on Figure 1 and Figure 2The embodiment shown, Figure 4 A flowchart of a method for deploying a service function chain provided by another exemplary embodiment of the present application is shown. The method can be collaboratively executed by a main controller of a multi-domain network and a domain controller in each domain network, such as Figure 4 As shown, the method may include the following steps.

[0060] Step 401, receive a service function chain deployment request, which includes the number and execution order of VNFs, the source node and destination node of the service function chain, and the resource requirements of each VNF.

[0061] Step 402: Obtain the inter-domain communication delay between each domain network and the remaining amount of resources of each domain network. Step 403, based on the inter-domain communication delay between each domain network, the remaining resources of each domain network and the resource demand of each VNF, determine the service function chain from the source node to the destination node of the service function chain; the total inter-domain communication delay of the service function chain is the shortest.

[0062] Step 404: Generate a chain cutting plan for the service function chain; the chain cutting plan is used to indicate that the service function chain is cut into multiple service function sub-chains corresponding to the multi-domain network.

[0063] Among them, a chain-cutting solution for generating a service function chain with load balancing as a constraint, the number of service function sub-chains is the same as the number of domain networks in the multi-domain network.

[0064] Step 405: Send the chain switching plan to the domain controllers of each domain network. Correspondingly, each domain controller receives the chain switching plan of the service function chain.

[0065] The relevant contents of step 401 to step 405 can be referred to as Figure 2 The description of the corresponding steps of the illustrated embodiment will not be repeated here.

[0066] For each domain network, after receiving the service function chain cutting plan, the corresponding service function sub-chain is deployed; taking the deployment process of the service function sub-chain of any target network as an example, the process of service function sub-chain deployment in each domain network can be implemented as follows: Step 406, based on the service function chain cutting plan, obtain the target service function subchain of the target domain network; the target service function subchain includes the resource requirements of each virtual network function VNF allocated to the target domain network. Step 407, under the constraint of the first constraint condition, generate multiple candidate paths corresponding to the target service function subchain; the first constraint condition is constructed based on the physical nodes in the target domain network and the resource surplus of each physical node.

[0067] The first constraint condition may include: VNFs are inseparable; At most one VNF is deployed on each physical node; The candidate path passes through a target physical node, which is a physical node used to provide VNF services for the target service function subchain; The total resource consumption corresponding to the candidate path is less than or equal to the resource surplus of the target domain network.

[0068] That is to say, in the process of deploying the intra-domain service function subchain, it is not allowed to split the VNF, that is, each VNF is placed on one physical node and is not allowed to be placed on two or more physical nodes. This constraint can be expressed as:

[0069] in, Represents a service function subchain The VNFs, is a binary variable representing VNF Whether it is placed on a physical node superior, Represents a service function subchain A collection of VNFs.

[0070] In addition, it is also required that each physical node deploys at most one VNF for each SFC. This constraint can be expressed as:

[0071] Considering the virtual link mapping of the service function chain, the transmission path needs to pass through the physical node used to provide VNF services for the service function subchain, that is, the target physical node. This constraint can be expressed as:

[0072] in, Represents a service function subchain The transmission path, Represents the placement of VNFs in the service function subchain. The above constraints indicate that the transmission path must pass through the service function subchain. A physical node that provides VNF services.

[0073] Finally, considering the resource upper limit constraint in the domain network, a binary variable is defined To express Whether to map to a physical link On, among them Represents a physical node With physical nodes Each virtual link in the same service function subchain has the same bandwidth resource requirements. Make physical node Consumed computing resources and physical links The bandwidth resources consumed are:

[0074]

[0075] in, Represents a service function subchain Middle The computing resource requirements of each VNF, Represents a service function subchain bandwidth resource requirements.

[0076] use Represents a physical node The remaining computing resources on Indicates link The remaining bandwidth resources on the service function subchain Within the VNF, the computing resource requirements are unchanged. Therefore, for the physical nodes and physical links where the VNF is deployed, the capacity constraints on computing resources and bandwidth resources can be expressed as:

[0077]

[0078] When deploying a service function subchain in a single domain network, under the constraint of the first constraint condition, the process of the intra-domain controller generating multiple candidate paths corresponding to the target service function subchain can be implemented as follows: Obtain the source node and destination node of the target service function subchain; the source node is the routing node connecting the target service function subchain with the previous domain network; the destination node is the routing node connecting the target service function subchain with the next domain network; Based on the source node and the destination node of the target service function subchain, under the constraint of the first constraint condition, the shortest path is generated by the KSP algorithm to obtain multiple candidate paths corresponding to the target service function subchain.

[0079] In the context of deploying service function subchains in a single domain network, the source node is the routing node that connects the target service function subchain with the previous domain network. It is the entry point for network traffic to enter the target service function subchain processing flow in the current target domain network from other domain networks. This node plays the role of receiving data from other domain networks and guiding it into the specific service function subchain of the local network in the entire multi-domain network service function chain system. Corresponding to the source node, the destination node is the routing node that connects the target service function subchain with the next domain network. It marks the exit position where the network traffic processed by the target service function subchain in the current target domain network is about to leave the local network and enter the next domain network. It is the transfer point for data transmission after completing the service function subchain processing flow in the local network. By clarifying these two key nodes, the key positions of the start and end are determined for the subsequent generation of reasonable candidate paths in the single domain network, so that path generation can be planned in a targeted manner around the traffic entrance and exit of the service function subchain.

[0080] Since the deployment problem of the service function subchain is an NP-hard problem, this problem has many constraints and high computational complexity. Therefore, when generating multiple candidate paths for the service function subchain, the domain controller can calculate K paths that meet the first constraint based on the KSP (K-Shortest Paths) algorithm as multiple candidate paths for the service function subchain, where K is a positive integer. The KSP algorithm is an algorithm for finding multiple shortest paths (the first K shortest paths) from a source node to a destination node in a network. It is based on the idea of ​​the shortest path algorithm in graph theory and can calculate multiple different shortest paths based on the consideration of network topology, link weights (such as link bandwidth, delay, etc., which can be used as weights). In this scenario, these paths are the candidate paths corresponding to the service function subchain. By finding multiple candidate paths, more selection space can be provided for subsequent further screening and optimization.

[0081] When executing the KSP algorithm, the domain controller can regard each physical node in the network topology as a vertex in the graph, and the connection links between the physical nodes as edges in the graph, and assign corresponding weights to these edges (the weights can comprehensively consider factors such as the bandwidth and delay of the link, while satisfying the restrictions on the remaining amount of physical node resources in the first constraint condition). Through the calculation process of the algorithm, starting from the source node, according to the established rules and weight calculation method, multiple paths to the destination node are gradually explored. These paths are multiple candidate paths corresponding to the service function subchain that meet the first constraint condition.

[0082] In a possible implementation, when applying the KSP algorithm, the embodiment of the present application may be provided with two different storage lists, one of which is used to place the shortest path and the corresponding offset path fitted based on the KSP algorithm, and the first storage list is "shortest_paths", and the other is used to place the shortest path that satisfies the first constraint condition after screening by the first constraint condition, and the second storage list is "ksp_paths". Figure 5 FIG. 4 shows a flowchart of an optimal path selection process based on a KSP algorithm provided by an exemplary embodiment of the present application. Figure 5 As shown, the process of the controller in the domain selecting a path based on the KSP algorithm may include: S501, adding the first shortest path to the first storage list shortest_paths; S502, calculating the deviation path of the last path in shortest_paths; S503, adding the shortest offset path to shortest_paths; S504, determine whether the shortest offset path satisfies the first constraint condition, if so, execute S505, otherwise, return to S502; S505, adding the shortest offset path to the second storage list ksp_paths; S506, determine whether the number of paths in ksp_paths is less than K, if so, return to S502, otherwise execute S507; S507, determine and output the K paths in ksp_paths as multiple candidate paths of the service function subchain, and end the path selection process.

[0083] Step 508, with minimizing the intra-domain communication delay and the standard deviation of resource utilization as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF instantiation scheme corresponding to each candidate path; wherein the VNF instantiation scheme is used to indicate the VNF deployment status of each physical node on the candidate path.

[0084] Among them, taking the process of determining the optimal VNF instantiation solution of any candidate path among the candidate paths as an example, the process of generating the optimal VNF instantiation solution corresponding to each candidate path by using the particle swarm optimization algorithm can be implemented as follows: Initialize the particle swarm optimization algorithm based on the target candidate path; the particle population in the particle swarm optimization algorithm is a set of VNF instantiation schemes on the corresponding candidate path, and one particle in the particle population represents a VNF instantiation scheme; the target candidate path is any one of each candidate path; Based on the particle velocity update mechanism in the particle swarm optimization algorithm, the particle position of each particle is iteratively adjusted until the optimization goal is met, and the optimal VNF instantiation solution corresponding to the target candidate path is obtained.

[0085] In the particle swarm optimization algorithm, a particle population is a collection of multiple particles. In the embodiment of the present application, the particle population refers to the collection of various VNF instantiation schemes on the corresponding candidate path. Each particle represents a possible VNF instantiation scheme, and the entire particle population covers many different VNF ​​deployment possibilities. The size of the particle population can be set based on factors such as computing resources, expected search accuracy, and algorithm convergence speed. For example, if the computing resources are sufficient and it is expected to search for the optimal solution more comprehensively, the particle population size can be appropriately increased; otherwise, the size needs to be appropriately reduced to ensure the algorithm operation efficiency. This application does not limit the size of the particle population; if the size of the particle population is set to N, the particle population can be expressed as:

[0086] in, represents the number of iterations of the particle population, Indicates the transmission path of the service function subchain, represents the particle population corresponding to the instantiation scheme under this path, represents the particle population Particles, representing a VNF instantiation scheme, The specific contents are as follows:

[0087] in, Indicates that the VNF instantiation solution has deployed The node M is the number of VNFs contained in the service function subchain.

[0088] Since the instantiation scheme itself has no concept of position and speed, in an embodiment of the present application, the node position and particle speed of the VNF deployment in the instantiation scheme can be given to make it move. By trying different deployment schemes and judging the pros and cons of different deployment schemes, the optimal VNF instantiation scheme can be obtained.

[0089] definition Represents VNF The speed indicates the moving method of the VNF in the next iteration, that is, the deployment node of the mth VNF will change, moving forward or backward along the transmission path of the service function subchain.

[0090] The speed of the particle It consists of three parts, including the original speed of the particle, the adjustment of the speed by the particle learning the optimal position of the individual, and the adjustment of the speed by the particle learning the optimal position of the population. The particle speed update mechanism can be expressed as:

[0091] in, Represents particles The speed value of the mth VNF in, Represents particles The individual optimal position of the mth VNF in , Represents the optimal population position of the mth VNF of the entire particle swarm. and is a random number between 0 and 1, in order to expand the search space of particles; is the inertia weight, which indicates how much the particle values ​​the original velocity when performing iterations; is the individual learning factor, is the population learning factor, which indicates the importance attached to individual experience and group experience.

[0092] According to the position and speed of VNF, the position update formula can be obtained:

[0093] When making iterative adjustments, certain constraints need to be met so that the generated VNF instantiation solution meets the path requirements. The process of iteratively adjusting the particle position of each particle based on the particle velocity update mechanism in the particle swarm optimization algorithm can be implemented as follows: Under the constraint of the second constraint, the particle position of each particle is iteratively adjusted based on the particle velocity update mechanism in the particle swarm optimization algorithm; The second constraint condition includes: The physical node where the VNF is deployed is within the path range of the target candidate path; The execution order between VNFs remains unchanged.

[0094] That is to say, under the constraint of the second condition, it can be ensured that the new position of the VNF during the iteration process does not exceed the path range, and the movement of the VNF does not change the execution order of each VNF.

[0095] The optimization goal of iterative adjustment in the service function subchain is to minimize the standard deviation of resource occupancy and minimize the intra-domain communication delay. In a possible implementation, a fitness function can be designed based on the above optimization goals to quantitatively evaluate the above optimization goals. In this case, in each iterative adjustment process, the fitness value of each particle is calculated by the fitness function, and the fitness value is the comprehensive value of the intra-domain communication delay and the standard deviation of resource occupancy corresponding to the particle; The VNF instantiation scheme represented by the particle with the smallest fitness value in the iterative adjustment is determined as the optimal VNF instantiation scheme corresponding to the target candidate path.

[0096] Schematically, the fitness function can be expressed as:

[0097] in, represents the fitness function of the nth particle; represents the standard deviation of resource utilization of the entire network, Represents a service function subchain Through the candidate path Normalized intra-domain communication delay; in the scenario of service function sub-chain deployment, the optimization goal is to minimize the intra-domain communication delay and the standard deviation of resource occupancy rate. The fitness value is calculated based on these two key indicators (intra-domain communication delay and standard deviation of resource occupancy rate). Therefore, the smaller the fitness value, the better the performance of the VNF instantiation solution on these two optimization goals.

[0098] Service Function Subchain Intra-domain communication delay The calculation method can be expressed as:

[0099] in, represents the link communication delay between physical node i and physical node j, that is, link The link communication delay.

[0100] Resource utilization standard deviation The calculation method can be expressed as:

[0101] The resource utilization standard deviation is the sum of the node resource utilization standard deviation and the link resource utilization standard deviation. The smaller the value, the more balanced the deployment of the service function subchains in the network and the better the network status. Represents a physical node The resource utilization rate, Indicates the average resource usage of all nodes. Indicates link Resource utilization, Indicates the average resource utilization of all links.

[0102] After that, define Represents particles The individual optimal position of is the fitness value of the individual optimal position of the nth particle; definition represents the optimal position of the particle swarm, is the fitness value of the optimal position of the population, that is, the optimal deployment method on a path; definition Represents the optimal deployment solution for the service function subchain, It is the fitness value of the optimal deployment solution of the service function subchain.

[0103] Figure 6 A flowchart of an optimal VNF solution for generating candidate paths provided by an exemplary embodiment of the present application is shown. Figure 6 As shown, the process can be implemented as: S601, initializing the particle population of the candidate path; S602, initializing the optimal position of the individual and the optimal position of the population; S603, updating particle position and particle velocity; S604, updating the individual optimal position; S605, updating the optimal position of the population; S606, determine whether the termination condition is met; if so, end; otherwise, return to S603.

[0104] Among them, when the termination condition is met, it means that the current VNF ​​instantiation scheme has achieved the optimization goal, and the current VNF ​​instantiation scheme is determined as the optimal VNF instantiation scheme corresponding to the candidate path.

[0105] That is to say, for each particle in the current particle swarm (i.e., each VNF instantiation scheme), firstly, the intra-domain communication delay and resource utilization standard deviation corresponding to the scheme are calculated according to the network topology of the target candidate path, the resource status of each physical node, and the VNF deployment status represented by the current particle, and then the fitness value is calculated through the preset fitness function. This fitness value can comprehensively reflect the performance of the VNF instantiation scheme in terms of optimization objectives.

[0106] For each particle, compare the current fitness value with the fitness value corresponding to its own individual optimal position; if the current fitness value is better, update the current position to the individual optimal position, and record the better VNF instantiation scheme this time; then, compare the fitness values ​​of all particles in the entire particle population, find the particle with the best fitness value, if its fitness value is better than the fitness value corresponding to the current global optimal position, then update the position of the particle to the global optimal position, which means that the VNF instantiation scheme with the best performance in the optimization objective in the entire population has been found.

[0107] The speed of each particle is updated according to the particle speed update mechanism of the particle swarm optimization algorithm, and the position of the particle is updated according to the updated speed and the position update formula.

[0108] Repeat the above iterative process, continuously update the particle's speed, position, individual optimal position and global optimal position, continuously calculate the fitness value and compare the optimization status until the preset optimization goal is met, and obtain the optimal VNF instantiation solution corresponding to the candidate path.

[0109] The above process is repeated to obtain the optimal VNF instantiation solution for each candidate path.

[0110] Step 409, based on the optimal VNF instantiation scheme corresponding to each candidate path, determine the target path and the optimal VNF instantiation scheme for the target path.

[0111] After completing the path selection, each service function subchain has K candidate paths to choose from for deployment, and the domain controller can select an optimal path and an optimal VNF instantiation solution from them. In this process, the domain controller can compare the fitness values ​​of the K candidate paths, and determine the candidate path with the smallest fitness as the target path, thereby obtaining the optimal VNF instantiation solution for the target path.

[0112] Step 410, based on the target path and the optimal VNF instantiation scheme for the target path, deploy the target service function subchain in the target domain network.

[0113] In summary, in the deployment method of the service function chain provided by the embodiment of the present application, the intra-domain controller of any target domain network in the multi-domain network obtains the target service function sub-chain of the target domain network from the chain cutting plan of the service function chain, and generates multiple candidate paths corresponding to the target service function sub-chain under the constraint of the first constraint condition constructed by comprehensively considering the physical nodes of the target domain network and the resource surplus of each physical node, and then, with the minimization of the intra-domain communication delay and the standard deviation of the resource occupancy rate as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF solution corresponding to each candidate path, and then the optimal target path and the corresponding optimal VNF solution compared with the target domain network are determined, and the target service function sub-chain is deployed in the target domain network based on the target path and the optimal VNF instantiation solution of the target path; through the above method, reasonable candidate paths can be generated in combination with the actual physical node resource status of the target domain network to avoid deployment solutions that are infeasible due to resource limitations, and when the VNF is determined When instantiating the solution, the two key indicators of intra-domain communication delay and resource utilization standard deviation were taken into consideration. The particle swarm optimization algorithm was used to determine the solution with better performance, so that the network can not only ensure the timeliness of data transmission during operation, but also improve the allocation effect of intra-domain links, achieve balanced allocation of VNFs on each physical node, and improve the overall stability and efficiency of the network.

[0114] Figure 7 A block diagram of a deployment device for a service function chain provided by an exemplary embodiment of the present application is shown. The device is applied in a domain controller in a target domain network to perform the following steps: Figure 1 or Figure 4 In the embodiment shown, all or part of the steps executed by the controller in the domain, the target domain network is any domain network in the multi-domain network, such as Figure 7 As shown, the device comprises: The link acquisition module 710 is used to acquire a target service function subchain of the target domain network based on a service function chain severance scheme; the severance scheme is used to indicate that the service function chain is divided into a plurality of service function subchains corresponding to the multi-domain networks; the target service function subchain includes resource requirements of each virtual network function VNF allocated to the target domain network; A path generation module 720, configured to generate a plurality of candidate paths corresponding to the target service function subchain under the constraint of a first constraint condition; the first constraint condition is constructed based on the physical nodes in the target domain network and the remaining amount of resources of each physical node; The first solution generation module 730 is used to generate the optimal VNF instantiation solution corresponding to each candidate path by using a particle swarm optimization algorithm with the optimization goal of minimizing the intra-domain communication delay and the standard deviation of resource occupancy; wherein the VNF instantiation solution is used to indicate the VNF deployment status of each physical node on the candidate path; A determination module 740 is used to determine a target path and an optimal VNF instantiation scheme for the target path based on the optimal VNF instantiation scheme corresponding to each candidate path; The deployment module 750 is used to deploy the target service function subchain in the target domain network based on the target path and the optimal VNF instantiation scheme of the target path.

[0115] In a possible implementation, the first solution generating module 730 includes: An initialization submodule is used to initialize a particle swarm optimization algorithm based on a target candidate path; a particle population in the particle swarm optimization algorithm is a set of VNF instantiation schemes on the corresponding candidate path, and a particle in the particle population represents a VNF instantiation scheme; the target candidate path is any one of each candidate path; The iterative adjustment submodule is used to iteratively adjust the particle position of each particle based on the particle speed update mechanism in the particle swarm optimization algorithm until the optimization target is met, thereby obtaining the optimal VNF instantiation solution corresponding to the target candidate path.

[0116] In a possible implementation, the iterative adjustment submodule is used to: In each iterative adjustment process, the fitness value of each particle is calculated by the fitness function, and the fitness value is a comprehensive value of the communication delay within the domain and the standard deviation of the resource occupancy rate corresponding to the particle; The VNF instantiation scheme represented by the particle with the smallest fitness value in the iterative adjustment is determined as the optimal VNF instantiation scheme corresponding to the target candidate path.

[0117] In a possible implementation, the iterative adjustment submodule is used to: Under the constraint of the second constraint condition, the particle position of each particle is iteratively adjusted based on the particle velocity update mechanism in the particle swarm optimization algorithm; The second constraint condition includes: The physical node where the VNF is deployed is within the path range of the target candidate path; The execution order between VNFs remains unchanged.

[0118] In a possible implementation, the path generation module 720 includes: A node acquisition submodule, used to acquire a source node and a destination node of the target service function subchain; the source node is a routing node connecting the target service function subchain with a previous domain network; the destination node is a routing node connecting the target service function subchain with a subsequent domain network; The path generation submodule is used to generate the shortest path based on the source node and the destination node of the target service function subchain and under the constraint of the first constraint condition through the KSP algorithm to obtain multiple candidate paths corresponding to the target service function subchain.

[0119] In a possible implementation manner, the first constraint condition includes: VNFs are inseparable; At most one VNF is deployed on each physical node; The candidate path passes through a target physical node, where the target physical node is a physical node for providing VNF services for the target service function subchain; The total resource consumption corresponding to the candidate paths is less than or equal to the remaining resources of the target domain network.

[0120] In summary, in the deployment device of the service function chain provided by the embodiment of the present application, the intra-domain controller of any target domain network in the multi-domain network obtains the target service function sub-chain of the target domain network from the chain cutting plan of the service function chain, and generates multiple candidate paths corresponding to the target service function sub-chain under the constraint of the first constraint condition constructed by comprehensively considering the physical nodes of the target domain network and the resource surplus of each physical node, and then, with the minimization of the intra-domain communication delay and the standard deviation of the resource occupancy rate as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF solution corresponding to each candidate path, and then the optimal target path and the corresponding optimal VNF solution compared with the target domain network are determined, and the target service function sub-chain is deployed in the target domain network based on the target path and the optimal VNF instantiation solution of the target path; through the above-mentioned device, reasonable candidate paths can be generated in combination with the actual physical node resource status of the target domain network to avoid deployment solutions that are infeasible due to resource limitations, and when the VNF is determined When instantiating the solution, the two key indicators of intra-domain communication delay and resource utilization standard deviation were taken into consideration. The particle swarm optimization algorithm was used to determine the solution with better performance, so that the network can not only ensure the timeliness of data transmission during operation, but also improve the allocation effect of intra-domain links, achieve balanced allocation of VNFs on each physical node, and improve the overall stability and efficiency of the network.

[0121] Figure 8 A block diagram of a deployment device for a service function chain provided by another exemplary embodiment of the present application is shown. The device is applied in a main controller of a multi-domain network to perform the following steps: Figure 2 or Figure 4 In the embodiment shown, all or part of the steps performed by the main controller, the multi-domain network includes at least two domain networks, such as Figure 8 As shown, the device comprises: A second solution generating module 810 generates a chain cutting solution for a service function chain; the chain cutting solution is used to indicate that the service function chain is cut into a plurality of service function sub-chains corresponding to the multi-domain network; The solution sending module 820 is used to send the chain cutting solution to the intra-domain controllers of each domain network so that each intra-domain controller obtains the corresponding service function sub-chain. For any intra-domain controller of the target domain network, multiple candidate paths corresponding to the target service function sub-chain are generated under the constraint of the first constraint condition; with minimizing the intra-domain communication delay and the standard deviation of resource occupancy rate as the optimization goal, the optimal VNF instantiation solution corresponding to each candidate path is generated through the particle swarm optimization algorithm, and the target path and the optimal VNF instantiation solution of the target path are determined based on the optimal VNF instantiation solution corresponding to each candidate path, and the target path and the optimal VNF instantiation solution of the target path are determined based on the optimal VNF instantiation solution corresponding to each candidate path; based on the target path and the optimal VNF instantiation solution of the target path, the target service function sub-chain is deployed in the target domain network.

[0122] In a possible implementation manner, the device further includes: A request receiving module, configured to receive a service function chain deployment request before the second solution generating module generates a chain cutting solution for the service function chain, wherein the service function chain deployment request includes the number and execution order of VNFs, the source node and destination node of the service function chain, and the resource demand of each VNF; A resource quantity acquisition module is used to obtain the inter-domain communication delay between each domain network and the remaining resources of each domain network; The link determination module is used to determine the service function chain from the source node to the destination node of the service function chain based on the inter-domain communication delay between each domain network, the remaining resources of each domain network and the resource demand of each VNF; the total inter-domain communication delay of the service function chain is the shortest.

[0123] In summary, in the deployment device of the service function chain provided by the embodiment of the present application, after the main control network generates the chain cutting plan of the service function chain, it sends the chain cutting plan to each domain network, and the domain controller of any target domain network in the multi-domain network obtains the target service function subchain of the target domain network from the chain cutting plan of the service function chain, and generates multiple candidate paths corresponding to the target service function subchain under the constraint of the first constraint condition constructed by comprehensively considering the physical nodes of the target domain network and the resource surplus of each physical node, and then, with the minimization of the intra-domain communication delay and the standard deviation of the resource occupancy rate as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF solution corresponding to each candidate path, and then the optimal target path and the corresponding optimal VNF solution compared with the target domain network are determined, and the target service function subchain is deployed in the target domain network based on the target path and the optimal VNF instantiation solution of the target path; through the above-mentioned device, reasonable candidate paths can be generated in combination with the actual physical node resource status of the target domain network to avoid deployment solutions that are infeasible due to resource limitations, and when the VNF is determined When instantiating the solution, the two key indicators of intra-domain communication delay and resource utilization standard deviation were taken into consideration. The particle swarm optimization algorithm was used to determine the solution with better performance, so that the network can not only ensure the timeliness of data transmission during operation, but also improve the allocation effect of intra-domain links, achieve balanced allocation of VNFs on each physical node, and improve the overall stability and efficiency of the network.

[0124] Fig. 9 The structural block diagram of a computer device 900 shown in an exemplary embodiment of the present application is shown. The computer device can be implemented as a main controller or a domain controller in the above-mentioned solution of the present application. The computer device 900 includes a central processing unit (CPU) 901, a system memory 904 including a random access memory (RAM) 902 and a read-only memory (ROM) 903, and a system bus 905 connecting the system memory 904 and the central processing unit 901. The computer device 900 also includes a large-capacity storage device 906 for storing an operating system 909, an application program 910 and other program modules 911.

[0125] According to various embodiments of the present application, the computer device 900 can also be connected to a remote computer on the network through a network such as the Internet. That is, the computer device 900 can be connected to the network 908 through the network interface unit 907 connected to the system bus 905, or the network interface unit 907 can be used to connect to other types of networks or remote computer systems (not shown).

[0126] The memory also includes at least one instruction, at least one program, code set or instruction set, and the at least one instruction, at least one program, code set or instruction set is stored in the memory. The central processing unit 901 implements all or part of the steps in the material recommendation method shown in the above-mentioned embodiments by executing the at least one instruction, at least one program, code set or instruction set.

[0127] Fig.10 FIG. 1 is a block diagram of a computer device 1000 according to another exemplary embodiment of the present application. The computer device 1000 may be implemented as the above-mentioned main controller or domain controller.

[0128] Typically, the computer device 1000 includes a processor 1001 and a memory 1002 .

[0129] In some embodiments, the computer device 1000 may also optionally include: a peripheral device interface 1003 and at least one peripheral device. The processor 1001, the memory 1002 and the peripheral device interface 1003 may be connected via a bus or a signal line. Each peripheral device may be connected to the peripheral device interface 1003 via a bus, a signal line or a circuit board. Specifically, the peripheral device includes: at least one of a radio frequency circuit 1004, a display screen 1005, a camera assembly 1006, an audio circuit 1007 and a power supply 1008.

[0130] In some embodiments, the computer device 1000 further includes one or more sensors 1009 , including but not limited to: an acceleration sensor 1010 , a gyroscope sensor 1011 , a pressure sensor 1012 , an optical sensor 1013 , and a proximity sensor 1014 .

[0131] Those skilled in the art will understand that Fig.10 The structure shown in the figure does not constitute a limitation on the computer device 1000, and the computer device 1000 may include more or less components than those shown in the figure, or combine some components, or adopt a different component arrangement.

[0132] In an exemplary embodiment, a computer-readable storage medium is also provided, in which at least one computer program is stored, and the computer program is loaded and executed by a processor to implement all or part of the steps in the deployment method of the above-mentioned service function chain. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0133] In an exemplary embodiment, a computer program product is also provided, the computer program product comprising at least one computer program, the computer program being loaded and executed by a processor Figure 2 or Figure 3 All or part of the steps of the service function chain deployment method shown in any embodiment.

[0134] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0135] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for deploying a service function chain, characterized in that: The method is executed by a domain controller of a target domain network, the target domain network is any domain network in a multi-domain network, and the method includes: A target service function subchain of the target domain network is obtained based on a service function chain severance scheme; the severance scheme is used to indicate that the service function chain is severanced into a plurality of service function subchains corresponding to the multi-domain networks; the target service function subchain includes resource requirements of each virtual network function VNF allocated to the target domain network; Under the constraint of a first constraint condition, a plurality of candidate paths corresponding to the target service function subchain are generated; the first constraint condition is constructed based on the physical nodes in the target domain network and the remaining amount of resources of each physical node; Taking minimizing the intra-domain communication delay and the standard deviation of resource utilization as the optimization goal, the particle swarm optimization algorithm is used to generate the optimal VNF instantiation scheme corresponding to each candidate path; wherein the VNF instantiation scheme is used to indicate the VNF deployment status of each physical node on the candidate path; Determine a target path and an optimal VNF instantiation scheme for the target path based on the optimal VNF instantiation scheme corresponding to each candidate path; Based on the target path and the optimal VNF instantiation scheme for the target path, the target service function subchain is deployed in the target domain network.

2. The method according to claim 1, characterized in that The optimization goal is to minimize the intra-domain communication delay and the standard deviation of resource occupancy, and to generate the optimal VNF instantiation scheme corresponding to each candidate path through the particle swarm algorithm, including: Initialize the particle swarm optimization algorithm based on the target candidate path; the particle population in the particle swarm optimization algorithm is a set of VNF instantiation schemes on the corresponding candidate path, and one particle in the particle population represents a VNF instantiation scheme; the target candidate path is any one of each candidate path; Based on the particle velocity update mechanism in the particle swarm optimization algorithm, the particle position of each particle is iteratively adjusted until the optimization goal is met, thereby obtaining the optimal VNF instantiation solution corresponding to the target candidate path.

3. The method according to claim 2, characterized in that The method further comprises: In each iterative adjustment process, the fitness value of each particle is calculated by the fitness function, and the fitness value is a comprehensive value of the communication delay within the domain and the standard deviation of the resource occupancy rate corresponding to the particle; The VNF instantiation scheme represented by the particle with the smallest fitness value in the iterative adjustment is determined as the optimal VNF instantiation scheme corresponding to the target candidate path.

4. The method according to claim 2, characterized in that: The iterative adjustment of the particle position of each particle based on the particle velocity update mechanism in the particle swarm optimization algorithm includes: Under the constraint of the second constraint condition, the particle position of each particle is iteratively adjusted based on the particle velocity update mechanism in the particle swarm optimization algorithm; The second constraint condition includes: The physical node where the VNF is deployed is within the path range of the target candidate path; The execution order between VNFs remains unchanged.

5. The method according to claim 1, characterized in that The step of generating a plurality of candidate paths corresponding to the target service function subchain under the constraint of the first constraint condition includes: Acquire the source node and the destination node of the target service function subchain; the source node is the routing node connecting the target service function subchain with the previous domain network; the destination node is the routing node connecting the target service function subchain with the next domain network; Based on the source node and the destination node of the target service function subchain, under the constraint of the first constraint condition, the shortest path is generated by the KSP algorithm to obtain multiple candidate paths corresponding to the target service function subchain.

6. The method according to claim 1, characterized in that The first constraint condition includes: VNFs are inseparable; At most one VNF is deployed on each physical node; The candidate path passes through a target physical node, where the target physical node is a physical node for providing VNF services for the target service function subchain; The total resource consumption corresponding to the candidate paths is less than or equal to the remaining resources of the target domain network.

7. A method for deploying a service function chain, characterized in that: The method is performed by a master controller of a multi-domain network, the multi-domain network comprising at least two domain networks, and the method comprises: Generate a chain cutting scheme for a service function chain; the chain cutting scheme is used to indicate that the service function chain is cut into a plurality of service function sub-chains corresponding to the multi-domain network; The chain cutting plan is sent to the intra-domain controllers of each domain network so that each intra-domain controller obtains the corresponding service function sub-chain. For any intra-domain controller of the target domain network, multiple candidate paths corresponding to the target service function sub-chain are generated under the constraint of the first constraint condition; with minimizing the intra-domain communication delay and the standard deviation of resource occupancy rate as the optimization goal, the optimal VNF instantiation plan corresponding to each candidate path is generated through the particle swarm optimization algorithm, and the target path and the optimal VNF instantiation plan of the target path are determined based on the optimal VNF instantiation plan corresponding to each candidate path; based on the optimal VNF instantiation plan corresponding to each candidate path, the target path and the optimal VNF instantiation plan of the target path are determined; based on the target path and the optimal VNF instantiation plan of the target path, the target service function sub-chain is deployed in the target domain network.

8. The method according to claim 7, characterized in that Before generating a chain cutting scheme for the service function chain, the method further includes: Receive a service function chain deployment request, wherein the service function chain deployment request includes the number and execution order of VNFs, the source node and destination node of the service function chain, and the resource demand of each VNF; Obtain the inter-domain communication delay between each domain network and the remaining resources of each domain network; Based on the inter-domain communication delay between each domain network, the remaining resources of each domain network and the resource demand of each VNF, the service function chain from the source node to the destination node of the service function chain is determined; the total inter-domain communication delay of the service function chain is the shortest.

9. A deployment device for a service function chain, characterized in that: The device is applied in a domain controller of a target domain network, the target domain network is any domain network in a multi-domain network, and the device includes: a link acquisition module, configured to acquire a target service function subchain of the target domain network based on a service function chain severance scheme; the severance scheme is configured to indicate that the service function chain is severanced into a plurality of service function subchains corresponding to the multi-domain networks; the target service function subchain includes resource requirements of each virtual network function VNF allocated to the target domain network; A path generation module, used to generate multiple candidate paths corresponding to the target service function subchain under the constraint of a first constraint condition; the first constraint condition is constructed based on the physical nodes in the target domain network and the resource surplus of each physical node; The first solution generation module is used to generate the optimal VNF instantiation solution corresponding to each candidate path by using a particle swarm optimization algorithm with the optimization goal of minimizing the intra-domain communication delay and the standard deviation of resource occupancy; wherein the VNF instantiation solution is used to indicate the VNF deployment status of each physical node on the candidate path; A determination module, configured to determine a target path and an optimal VNF instantiation scheme for the target path based on the optimal VNF instantiation scheme corresponding to each candidate path; A deployment module is used to deploy the target service function subchain in the target domain network based on the target path and the optimal VNF instantiation scheme of the target path.

10. A deployment device for a service function chain, characterized in that: The device is applied to be executed by a main controller of a multi-domain network, the multi-domain network includes at least two domain networks, and the device includes: A second solution generating module is used to generate a chain cutting solution of the service function chain; the chain cutting solution is used to indicate that the service function chain is cut into a plurality of service function sub-chains corresponding to the multi-domain network; A scheme sending module is used to send the chain cutting scheme to the intra-domain controllers of each domain network so that each intra-domain controller obtains the corresponding service function sub-chain. For any intra-domain controller of the target domain network, multiple candidate paths corresponding to the target service function sub-chain are generated under the constraint of the first constraint condition; with minimizing the intra-domain communication delay and the standard deviation of resource occupancy rate as the optimization goal, the optimal VNF instantiation scheme corresponding to each candidate path is generated by the particle swarm optimization algorithm, based on the optimal VNF instantiation scheme corresponding to each candidate path, the target path and the optimal VNF instantiation scheme of the target path are determined, based on the optimal VNF instantiation scheme corresponding to each candidate path, the target path and the optimal VNF instantiation scheme of the target path are determined; based on the target path and the optimal VNF instantiation scheme of the target path, the target service function sub-chain is deployed in the target domain network.

11. A computer device, characterized in that: The computer device includes a processor and a memory, the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor to implement the service function chain deployment method as described in any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that: At least one computer program is stored in the computer-readable storage medium, and the computer program is loaded and executed by the processor to implement the service function chain deployment method as described in any one of claims 1 to 9.

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