VNF deployment method, device and equipment based on network traffic convergence

Abstract

The present application provides a VNF deployment method, device and equipment based on network traffic convergence, which relates to the field of communication technology, including: partitioning the underlying physical network based on the network node distance, calculating the VNF deployment candidate node set; obtaining the network of the VNF node to be deployed, taking each network node in the network of the VNF node to be deployed as the source node in turn, and the candidate node closest to the source node in the VNF deployment candidate node set as the destination node corresponding to the source node, and determining the data transmission link based on each source node and the corresponding destination node; calculating the intermediate centrality of the given destination node set corresponding to each network node in the network of the VNF node to be deployed after the data packet is transmitted on each data transmission link, and determining the VNF deployment target node set based on the intermediate centrality in the given destination node set for VNF deployment. The present application reduces the overall queuing delay of the network and avoids network congestion and interruption.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a VNF deployment method, device and equipment based on network traffic convergence. Background Art

[0002] Network Function Virtualization (NFV) is a technology that implements network functions in a virtualized environment. By virtualizing network functions from dedicated hardware devices to ordinary commodity servers, network flexibility and efficiency can be significantly improved and network costs can be reduced. NFV technology implements network functions in a virtualized environment. Virtual Network Functions (VNF) can be deployed, configured and modified quickly and easily, which helps to improve the sharing and reusability of network components, and is conducive to rapid network deployment, dynamic network allocation, simple network management, etc.

[0003] However, most of the existing VNF deployment algorithms do not start from the topological characteristics of the network and ignore the impact of the underlying topological characteristics on the deployment results; and some studies, although using topological characteristics, do not solve the network congestion and load imbalance problems in VNF deployment. Summary of the invention

[0004] The purpose of this application is to provide a VNF deployment method, device and equipment based on network traffic convergence to alleviate the above-mentioned technical problems existing in the prior art.

[0005] In a first aspect, the present invention provides a VNF deployment method based on network traffic convergence, the method comprising:

[0006] Partition the underlying physical network based on the network node distance and calculate the corresponding VNF deployment candidate node set after partitioning;

[0007] Obtain the network of the VNF node to be deployed, take each network node in the network of the VNF node to be deployed as a source node in turn, take the candidate node closest to the source node in the VNF deployment candidate node set as the destination node corresponding to the source node, and determine the data transmission link based on each source node and the corresponding destination node;

[0008] Calculate the betweenness centrality in a given destination node set corresponding to each network node in the network where the VNF node is to be deployed after the data packet is transmitted on each data transmission link, and determine the VNF deployment target node set based on the betweenness centrality in the given destination node set, so as to deploy the VNF based on the VNF deployment target node set; wherein the betweenness centrality in the given destination node set is used to measure the convergence of network traffic.

[0009] In an optional implementation, partitioning the underlying physical network based on the network node distance and calculating the corresponding VNF deployment candidate node set after the partitioning include:

[0010] Randomly select a network node in the underlying physical network as the first initial clustering center, calculate the network node distances from other network nodes in the underlying physical network to the first initial clustering center, select the network node with the largest network node distance as the next initial clustering center, and repeat this step to determine multiple initial clustering centers;

[0011] Partitioning the underlying physical network based on the initial clustering center, and dividing the network nodes in the underlying physical network into corresponding partition areas based on the distances between the network nodes in the underlying physical network and the initial clustering center contained in the partition area;

[0012] Calculate the closeness centrality of the network nodes in each partition area, and take the network node with the smallest closeness centrality in the partition area as the target cluster center;

[0013] A set of VNF deployment candidate nodes is determined based on the target cluster centers of all partitioned areas; wherein the target cluster center of each partitioned area is a VNF deployment candidate node of the current partitioned area, and each VNF deployment candidate node corresponds to a candidate deployment scheme.

[0014] In an optional implementation, determining multiple data transmission links based on each source node and the corresponding destination node includes:

[0015] Generate a data packet of a first data volume through a source node, and send the data packet to a network of a VNF node to be deployed;

[0016] When a data packet is transmitted to the current node in the network of the VNF node to be deployed, the network node distances of all network nodes adjacent to the current node and the destination node are calculated, and the network node with the smallest network node distance is used as the next hop forwarding node of the current node;

[0017] When all data packets in the network of the VNF node to be deployed arrive at the destination node, the corresponding data transmission link is determined based on the source node, multiple next-hop forwarding nodes and the destination node; different source nodes correspond to different data transmission links, and multiple data transmission links are determined based on different source nodes, next-hop network nodes and destination nodes.

[0018] In an optional embodiment, the method further comprises:

[0019] If two or more next-hop forwarding nodes are included at the same time, weighted processing is performed on the data packet: the number of first shortest paths between the current node and the destination node is calculated, the number of second shortest paths between each next-hop node and the destination node is calculated, and the data packet is weighted based on the first data volume of the data packet, the first shortest path number, and the second shortest path number to obtain the second data volume of the data packet sent to the next-hop network node;

[0020] Send the weighted data packet to each next-hop forwarding node.

[0021] In an optional implementation, calculating the betweenness centrality of a given destination node set corresponding to each network node in the network where the VNF node is to be deployed after the data packet is transmitted on each data transmission link includes:

[0022] Each time a data packet generated in the network where the VNF node is to be deployed passes through a network node, the centrality of the given destination node corresponding to the network node is increased by a preset unit;

[0023] When all data packets in the network of the VNF node to be deployed arrive at the destination node, the betweenness centrality in the given destination node set corresponding to each network node in the network of the VNF node to be deployed is determined.

[0024] In an optional implementation, determining a VNF deployment target node set based on the betweenness centrality in a given destination node set includes:

[0025] Determine the network nodes whose betweenness centrality in the given destination node set meets the preset deployment conditions as the VNF deployment nodes of the current candidate deployment solution;

[0026] The VNF deployment node with the smallest betweenness centrality in a given destination node set among multiple candidate deployment schemes is determined as the VNF deployment target node set.

[0027] In an optional embodiment, the method further comprises:

[0028] The network throughput upper limit is determined based on the VNF deployment target node set.

[0029] In a second aspect, the present invention provides a VNF deployment device based on network traffic convergence, the device comprising:

[0030] The deployment candidate module is used to partition the underlying physical network based on the network node distance and calculate the corresponding VNF deployment candidate node set after partitioning;

[0031] The network traffic transmission module is used to obtain the network of the VNF node to be deployed, take each network node in the network of the VNF node to be deployed as the source node in turn, take the candidate node closest to the source node in the VNF deployment candidate node set as the destination node corresponding to the source node, and determine the data transmission link based on each source node and the corresponding destination node;

[0032] The VNF deployment module is used to calculate the betweenness centrality in a given destination node set corresponding to each network node in the network where the VNF node is to be deployed after the data packet is transmitted on each data transmission link, and determine the VNF deployment target node set based on the betweenness centrality in the given destination node set, so as to deploy the VNF based on the VNF deployment target node set; wherein the betweenness centrality in the given destination node set is used to measure the convergence of network traffic.

[0033] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores computer executable instructions that can be executed by the processor, and the processor executes the computer executable instructions to implement the VNF deployment method based on network traffic convergence of any of the aforementioned implementations.

[0034] In a fourth aspect, the present invention provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement any one of the VNF deployment methods based on network traffic convergence of the aforementioned implementation methods.

[0035] The beneficial effects of the VNF deployment method, device and equipment based on network traffic convergence provided by the present application are as follows:

[0036] This application introduces the convergence of business traffic in network structure characteristics into the VNF deployment problem, uses the betweenness centrality of a given destination node set to measure the convergence of business traffic in the network, obtains deployment results close to the upper limit of network throughput, reduces the traffic aggregation effect of certain bottleneck nodes, reduces the traffic load on the nodes, and thus achieves uniform distribution and load balancing of business traffic, while reducing the overall queuing delay of the network and avoiding network congestion and interruption; by improving the traditional betweenness centrality, the betweenness centrality of a given destination node set suitable for the VNF deployment problem is obtained, and the betweenness centrality of a given destination node set is used to measure the convergence of network traffic. The calculation method of betweenness centrality (BC) based on network traffic simulation can calculate the betweenness centrality (BC) of the VNF deployed in the network as a destination node set in a short time; in addition, based on the BC of a given destination node set and the network partitioning algorithm, a VNF rapid deployment algorithm is proposed, which can obtain VNF deployment results close to the upper limit of network throughput in a relatively short time. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the specific implementation methods of the present application or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0038] Figure 1 A flowchart of a VNF deployment method based on network traffic convergence provided in an embodiment of the present application;

[0039] Figure 2 A flow chart of a network traffic simulation calculation BC algorithm provided in an embodiment of the present application;

[0040] Figure 3 A VNF deployment algorithm flow chart provided for an embodiment of the present application;

[0041] Figure 4 A structural diagram of a VNF deployment device based on network traffic convergence provided in an embodiment of the present application;

[0042] Figure 5 A structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations.

[0044] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0045] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0046] Most existing VNF deployment algorithms do not start from the network topology characteristics, ignoring the impact of the underlying topology characteristics on the deployment results. Although some studies have used topology characteristics, they have not solved the network congestion and load imbalance problems in VNF deployment. The existing VNF deployment algorithms that use network topology characteristics can be divided into the following categories:

[0047] (1) Deployment algorithm based on the shortest path. The VNF deployment algorithm based on the shortest path aims to deploy the VNF at the location closest to the target node to reduce communication delay. By selecting the shortest path or the minimum number of hops, the delay of data transmission can be reduced and the response performance of network services can be improved.

[0048] However, when using the shortest path VNF deployment algorithm, traffic may be concentrated on certain nodes or links, resulting in increased data transmission delays, or even packet loss and network interruption. This is because algorithms based on the shortest path usually make decisions based only on the length of the network path, without paying attention to the load of the network nodes and the convergence of business traffic. Therefore, even if some nodes are already carrying a large amount of traffic or service requests, these algorithms still choose to deploy VNFs on these nodes, resulting in load imbalance.

[0049] (2) Deployment algorithm based on close centrality. The deployment goal of the deployment algorithm based on close centrality is to minimize the total distance from all nodes on the network to the VNF node, so as to reduce the total delay and total traffic in the network link propagation. However, the deployment algorithm based on close centrality only considers the average path length from the node to the VNF node in the network, making the information propagation speed between the VNF node and other nodes the fastest, and does not consider the load and traffic distribution of the nodes in the network. Therefore, the deployment algorithm based on close centrality cannot solve the problems of network congestion and load imbalance.

[0050] (3) Deployment algorithm based on connectivity. VNF deployment algorithms based on connectivity often only care about the connectivity between network nodes and network areas, with the goal of achieving maximum coverage of VNF nodes. High node coverage can ensure that most nodes are involved in the connection in the network, which is conducive to the transmission of global information. Low node coverage may lead to isolated nodes in the network, reducing the integrity of the network. However, network connectivity is often used to evaluate the connectivity of the network, and its deployment algorithm often considers using the least VNF ​​nodes to achieve the maximum network coverage without considering the problem of node bearing network load. This may result in not enough VNF nodes being allocated in some node-dense areas, resulting in heavy link bearing pressure and load imbalance.

[0051] Therefore, some existing VNF deployment algorithms do not take into account the topological characteristics of the network. Although other algorithms utilize the network topological characteristics, the topological characteristics used cannot reflect the convergence of network service traffic, which can easily cause some low-load nodes in the network to not be fully utilized, while high-load nodes are overloaded, causing the network load to be concentrated on certain bottleneck nodes, resulting in a sharp increase in the overall queuing delay of the network, leading to network congestion or even interruption.

[0052] Considering that if the VNF deployment result does not match the network topology well, the traffic carried in a local area of ​​the network may exceed the network node limit, resulting in congestion, which seriously affects the throughput and performance of the entire network. Based on this, the embodiment of the present application provides a VNF deployment method, device and equipment based on network traffic convergence, which can disperse the traffic on the entire network, achieve load balancing, improve the overall throughput of the deployed network, and effectively reduce queuing delay.

[0053] The present application embodiment provides a VNF deployment method based on network traffic convergence. Figure 1 As shown, the method mainly includes the following steps:

[0054] Step S110, partition the underlying physical network based on the network node distance, and calculate the corresponding VNF deployment candidate node set after the partition.

[0055] First initialize the underlying physical network ,in Represents a collection of underlying physical nodes, Represents the set of links between physical nodes, the number of nodes , number of links An underlying physical node is represented by , a bidirectional link is represented by VNF is deployed in the underlying physical network. The set of VNFs to be deployed is F, the number of deployments is k, and the cluster center set C is initialized.

[0056] In one implementation, the underlying physical network is partitioned based on the network node distance, and the corresponding VNF deployment candidate node set after the partition is calculated. In the specific implementation, the following steps 1-1 to 1-4 may be included:

[0057] Step 1-1, randomly select a network node in the underlying physical network as the first initial clustering center, calculate the network node distances from other network nodes in the underlying physical network to the first initial clustering center, select the network node with the largest network node distance as the next initial clustering center, and repeat this step to determine multiple initial clustering centers;

[0058] Step 1-2, partitioning the underlying physical network based on the initial cluster center, and dividing the network nodes in the underlying physical network into corresponding partition areas based on the distance between the network nodes in the underlying physical network and the initial cluster center contained in the partition area;

[0059] Step 1-3, calculate the closeness centrality of the network nodes in each partition area, and take the network node with the smallest closeness centrality in the partition area as the target cluster center;

[0060] Step 1-4, determine the set of VNF deployment candidate nodes based on the target cluster centers of all partitioned areas; wherein the target cluster center of each partitioned area is the VNF deployment candidate node of the current partitioned area, and each VNF deployment candidate node corresponds to a candidate deployment scheme.

[0061] In practical applications, the K-means clustering algorithm can be used to partition the network based on the distance between nodes, and the center point of each partition is taken as the set of VNF deployment locations to obtain candidate deployment solutions. Specifically:

[0062] (1) Initial cluster center selection: randomly select a network node in the underlying physical network As the first initial cluster center . Calculate the network node distance from other network nodes in the network to the first initial clustering center , select the network node with the largest network node distance as the next initial clustering center Repeat this step until k initial cluster centers are selected.

[0063] (2) Network node partitioning: Each cluster center Divide a partition area , computing network nodes With all cluster centers Distance , divide the network nodes into the cluster centers that are closest to them. Divide the underlying physical network into k partition areas ,Each partition area consists of a cluster center and other nodes.

[0064] (3) Calculate the target cluster center: Within each partition area, calculate the closeness centrality of the nodes in the partition, and select the node with the smallest closeness centrality as the new cluster center. All new cluster centers generated each time are taken as a node set and added to the candidate deployment scheme.

[0065] (4) Termination condition: When the network no longer generates new cluster centers, the clustering algorithm terminates and the set of candidate nodes for VNF deployment is determined.

[0066] Step S120, obtain the network of the VNF node to be deployed, take each network node in the network of the VNF node to be deployed as the source node in turn, take the candidate node closest to the source node in the VNF deployment candidate node set as the destination node corresponding to the source node, and determine the data transmission link based on each source node and the corresponding destination node.

[0067] The network of the VNF nodes to be deployed is also the underlying physical network of the VNFs to be deployed.

[0068] In one embodiment, the network traffic convergence characteristics can be reflected by calculating the intermediate centrality of the candidate deployment scheme as the destination node set in a network traffic simulation manner. The above-mentioned determination of multiple data transmission links based on each source node and the corresponding destination node can include the following steps 2-1 to 2-3 in specific implementation:

[0069] Step 2-1, generating a data packet of a first data volume through a source node, and sending the data packet to a network of a VNF node to be deployed;

[0070] Step 2-2, when the data packet is transmitted to the current node in the network of the VNF node to be deployed, the network node distances of all network nodes adjacent to the current node and the destination node are calculated, and the network node with the smallest network node distance is used as the next hop forwarding node of the current node;

[0071] Step 2-3, when all data packets in the network of the VNF node to be deployed arrive at the destination node, the corresponding data transmission link is determined based on the source node, multiple next-hop forwarding nodes and the destination node; different source nodes correspond to different data transmission links, and multiple data transmission links are determined based on different source nodes, next-hop network nodes and destination nodes.

[0072] Furthermore, if two or more next-hop forwarding nodes are included at the same time, the data packet is weighted: the first shortest path number between the current node and the destination node is calculated, the second shortest path number between each next-hop node and the destination node is calculated, and the data packet is weighted based on the first data volume of the data packet, the first shortest path number and the second shortest path number to obtain the second data volume of the data packet sent to the next-hop network node; the weighted data packet is sent to each next-hop forwarding node.

[0073] Step S130, calculate the betweenness centrality in a given destination node set corresponding to each network node in the network where the VNF node is to be deployed after the data packet is transmitted on each data transmission link, and determine the VNF deployment target node set based on the betweenness centrality in the given destination node set, so as to deploy the VNF based on the VNF deployment target node set; wherein the betweenness centrality in the given destination node set is used to measure the convergence of network traffic.

[0074] Each network node in the network v The betweenness centrality is used to characterize the number of shortest paths through the network node. The number of shortest paths between all network node pairs The sum of the ratios of . Node intermediary centrality BC is used to characterize the potential of nodes in the network to control traffic. BC is used to identify traffic convergence points in the network, find bottlenecks or control points of information flow, and predict the influence and communication capabilities of nodes. The larger the BC value of a node, the more business traffic will be carried on the shortest path through the node, and the more congestion will occur, which will reduce the upper limit of network throughput.

[0075] The betweenness centrality of the given destination node set is defined as To the destination node set Passing Node The number of shortest paths With Node To the VNF deployment candidate node set The number of shortest paths between The sum of the ratios of .

[0076] In one embodiment, calculating the betweenness centrality of a given destination node set corresponding to each network node in the network where the VNF node is to be deployed after the data packet is transmitted on each data transmission link may include the following steps 3-1 and 3-2:

[0077] Step 3-1, each time a data packet generated in the network where the VNF node is to be deployed passes through a network node, the centrality of the given destination node corresponding to the network node is increased by a preset unit;

[0078] Step 3-2, when all data packets in the network of the VNF node to be deployed arrive at the destination node, determine the centrality of the given destination node set corresponding to each network node in the network of the VNF node to be deployed.

[0079] Further, the above-mentioned determination of the VNF deployment target node set based on the betweenness centrality in the given destination node set may include the following steps 4-1 and 4-2:

[0080] Step 4-1, determining a network node whose betweenness centrality in a given destination node set meets a preset deployment condition as a VNF deployment node of the current candidate deployment solution;

[0081] Step 4-2, determining the VNF deployment node with the smallest betweenness centrality in a given destination node set among multiple candidate deployment schemes as the VNF deployment target node set.

[0082] In addition, after determining the VNF deployment target node set, the network throughput upper limit can be determined based on the VNF deployment target node set. In practical applications, the inverse of the betweenness centrality can be determined as the network throughput upper limit under the VNF deployment solution.

[0083] In one embodiment, for the above steps S120 and 130, since the BC value describes the convergence of the service traffic on the node, according to the BC calculation principle, the service traffic load carried on the node is calculated by simulating the service traffic, so as to quickly calculate the BC of the given destination node set. , the maximum BC value of all nodes in the current network is calculated by network traffic simulation, that is, .

[0084] See also Figure 2 As shown, the specific steps for calculating BC through network traffic simulation are as follows:

[0085] (1) The network is stored in an adjacency table, and the shortest path length between all node pairs in the network is obtained through distance calculation methods such as the Dijkstra algorithm and the Floyd algorithm. , and given a set of destination nodes .

[0086] (2) All network nodes in the network where the VNF node is to be deployed (such as the underlying physical network) As a source node, the set Middle distance to current node The nearest node As a VNF deployment node, the VNF deployment node is the destination node;

[0087] (3) The unit size generated by the source node is The data packet is sent to the network. The specific process of sending the data packet is in step (4);

[0088] (4) Data packet arrives at the current network node After that, the calculation and node All adjacent nodes Distance to destination node vs, select distance The smallest node is used as the next-hop forwarding node;

[0089] (5) If there are two or more nodes with the same minimum distance , then a weighted data packet will be sent to each node, and the data packet weighting process is in step (6);

[0090] (6) Calculate the current node With the destination node The number of shortest paths between , calculate each next hop node With the destination node The number of shortest paths between , the data packet is sent to the next hop node The weighted value is , i.e. node The amount of data on ;

[0091] (7) Every time a data packet generated in the network passes through a node When the node The given destination node set BC increases units, that is .

[0092] (8) When all packets in the network have reached the destination node, the BC calculation of each node in the network for a given destination node set is completed. Figure 3 The figure shows a specific process of VNF deployment. After determining the center point of each partition, each partition center point is used as a set of candidate nodes, and then the corresponding VNF deployment candidate node set after multiple partitions is obtained. The maximum node BC corresponding to each candidate node is calculated, that is, , as the BC value of the candidate node.

[0093] Since the VNF deployment candidate node set includes multiple partitions, it includes multiple VNF deployment schemes, and each VNF deployment scheme corresponds to a BC value of a candidate node. In order to avoid network congestion or even interruption as much as possible, the post-deployment BC value (that is, the aforementioned BC value) of all candidate schemes can be taken. ) The smallest set of nodes is used as the final deployment node set.

[0094] Furthermore, the inverse of the BC value 1 / BC can also be calculated as the upper limit of the network throughput under this VNF deployment solution.

[0095] In summary, the BC-based VNF deployment algorithm provided in the embodiment of the present application can quickly calculate the BC of a given destination node set in a short time by counting the number of data packets passing through each node through network traffic simulation. It can achieve the dispersion and load balancing of business traffic in the network and maximize the upper limit of throughput without network congestion.

[0096] Based on the above method embodiment, the present application embodiment also provides a VNF deployment device based on network traffic convergence, see Figure 4 As shown, the device mainly includes the following parts:

[0097] A deployment candidate module 410 is used to partition the underlying physical network based on the network node distance and calculate the corresponding VNF deployment candidate node set after the partition;

[0098] The network traffic transmission module 420 is used to obtain the network of the VNF node to be deployed, take each network node in the network of the VNF node to be deployed as a source node in turn, take the candidate node closest to the source node in the VNF deployment candidate node set as the destination node corresponding to the source node, and determine the data transmission link based on each source node and the corresponding destination node;

[0099] The VNF deployment module 430 is used to calculate the betweenness centrality in a given destination node set corresponding to each network node in the network where the VNF node is to be deployed after the data packet is transmitted on each data transmission link, and determine the VNF deployment target node set based on the betweenness centrality in the given destination node set, so as to deploy the VNF based on the VNF deployment target node set; wherein the betweenness centrality in the given destination node set is used to measure the convergence of network traffic.

[0100] In a feasible implementation manner, the deployment candidate module 410 is further used to:

[0101] Randomly select a network node in the underlying physical network as the first initial clustering center, calculate the network node distances from other network nodes in the underlying physical network to the first initial clustering center, select the network node with the largest network node distance as the next initial clustering center, and repeat this step to determine multiple initial clustering centers;

[0102] Partitioning the underlying physical network based on the initial clustering center, and dividing the network nodes in the underlying physical network into corresponding partition areas based on the distances between the network nodes in the underlying physical network and the initial clustering center contained in the partition area;

[0103] Calculate the closeness centrality of the network nodes in each partition area, and take the network node with the smallest closeness centrality in the partition area as the target cluster center;

[0104] A set of VNF deployment candidate nodes is determined based on the target cluster centers of all partitioned areas; wherein the target cluster center of each partitioned area is a VNF deployment candidate node of the current partitioned area, and each VNF deployment candidate node corresponds to a candidate deployment scheme.

[0105] In a feasible implementation manner, the network traffic transmission module 420 is further used to:

[0106] Generate a data packet of a first data volume through a source node, and send the data packet to a network of a VNF node to be deployed;

[0107] When a data packet is transmitted to the current node in the network of the VNF node to be deployed, the network node distances of all network nodes adjacent to the current node and the destination node are calculated, and the network node with the smallest network node distance is used as the next hop forwarding node of the current node;

[0108] When all data packets in the network of the VNF node to be deployed arrive at the destination node, the corresponding data transmission link is determined based on the source node, multiple next-hop forwarding nodes and the destination node; different source nodes correspond to different data transmission links, and multiple data transmission links are determined based on different source nodes, next-hop network nodes and destination nodes.

[0109] In a feasible implementation manner, the above device further includes a data packet processing module, which is used to:

[0110] If two or more next-hop forwarding nodes are included at the same time, weighted processing is performed on the data packet: the number of first shortest paths between the current node and the destination node is calculated, the number of second shortest paths between each next-hop node and the destination node is calculated, and the data packet is weighted based on the first data volume of the data packet, the first shortest path number, and the second shortest path number to obtain the second data volume of the data packet sent to the next-hop network node;

[0111] Send the weighted data packet to each next-hop forwarding node.

[0112] In a feasible implementation manner, the VNF deployment module 430 is further configured to:

[0113] Each time a data packet generated in the network where the VNF node is to be deployed passes through a network node, the centrality of the given destination node corresponding to the network node is increased by a preset unit;

[0114] When all data packets in the network of the VNF node to be deployed arrive at the destination node, the betweenness centrality in the given destination node set corresponding to each network node in the network of the VNF node to be deployed is determined.

[0115] In a feasible implementation manner, the VNF deployment module 430 is further configured to:

[0116] Determine the network nodes whose betweenness centrality in the given destination node set meets the preset deployment conditions as the VNF deployment nodes of the current candidate deployment solution;

[0117] The VNF deployment node with the smallest betweenness centrality in a given destination node set among multiple candidate deployment schemes is determined as the VNF deployment target node set.

[0118] In a feasible implementation manner, the above device further includes a throughput determination module, which is used to:

[0119] The network throughput upper limit is determined based on the VNF deployment target node set.

[0120] The VNF deployment device based on network traffic convergence provided in the embodiment of the present application has the same implementation principle and technical effects as those of the aforementioned method embodiment. For the sake of brief description, for parts not mentioned in the embodiment of the VNF deployment device based on network traffic convergence, reference may be made to the corresponding contents in the aforementioned VNF deployment method embodiment based on network traffic convergence.

[0121] The present application also provides an electronic device, such as Figure 5 As shown, it is a structural diagram of the electronic device, wherein the electronic device 100 includes a processor 51 and a memory 50, the memory 50 stores computer executable instructions that can be executed by the processor 51, and the processor 51 executes the computer executable instructions to implement any of the above-mentioned VNF deployment methods based on network traffic convergence.

[0122] exist Figure 5 In the illustrated embodiment, the electronic device further includes a bus 52 and a communication interface 53 , wherein the processor 51 , the communication interface 53 and the memory 50 are connected via the bus 52 .

[0123] Among them, the memory 50 may include a high-speed random access memory (RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The communication connection between the system network element and at least one other network element is realized through at least one communication interface 53 (which can be wired or wireless), and the Internet, wide area network, local area network, metropolitan area network, etc. can be used. The bus 52 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 52 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 5 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0124] The processor 51 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the hardware integrated logic circuit or software instructions in the processor 51. The above processor 51 can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in the embodiment of the present application can be directly embodied as a hardware decoding processor to execute, or the hardware and software modules in the decoding processor are combined and executed. The software module can be located in a mature storage medium in the field such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor 51 reads the information in the memory and combines its hardware to complete the steps of the VNF deployment method based on network traffic convergence in the aforementioned embodiment.

[0125] An embodiment of the present application also provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are called and executed by a processor, the computer-executable instructions prompt the processor to implement the above-mentioned VNF deployment method based on network traffic convergence. The specific implementation can be found in the aforementioned method embodiment, which will not be repeated here.

[0126] The computer program product of the VNF deployment method, apparatus and device based on network traffic convergence provided in the embodiments of the present application includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods in the previous method embodiments. The specific implementation can be found in the method embodiments, which will not be repeated here.

[0127] Unless otherwise specifically stated, the relative steps, numerical expressions and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0128] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0129] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, or the positions or positional relationships in which the invented product is usually placed when in use. They are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific position, be constructed and operated in a specific position, and therefore cannot be understood as a limitation on the present application. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0130] In addition, the terms "horizontal", "vertical", "overhanging" and the like do not mean that the components are required to be absolutely horizontal or overhanging, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0131] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A VNF deployment method based on network traffic convergence, characterized in that: The method comprises: Partition the underlying physical network based on the network node distance and calculate the corresponding VNF deployment candidate node set after partitioning; Obtain a network of the VNF node to be deployed, take each network node in the network of the VNF node to be deployed as a source node in turn, take the candidate node closest to the source node in the VNF deployment candidate node set as the destination node corresponding to the source node, and determine a data transmission link based on each source node and the corresponding destination node; Calculate the betweenness centrality of a given destination node set corresponding to each network node in the network of the VNF node to be deployed after the data packet is transmitted on each data transmission link, and determine the VNF deployment target node set based on the betweenness centrality of the given destination node set, so as to deploy the VNF based on the VNF deployment target node set; wherein the betweenness centrality of the given destination node set is used to measure the convergence of network traffic; The underlying physical network is partitioned based on the network node distance, and the corresponding VNF deployment candidate node set after the partition is calculated, including: randomly selecting a network node in the underlying physical network as the first initial clustering center, calculating the network node distance from other network nodes in the underlying physical network to the first initial clustering center, selecting the network node with the largest network node distance as the next initial clustering center, and repeating this step to determine multiple initial clustering centers; partitioning the underlying physical network based on the initial clustering center, and dividing the network nodes in the underlying physical network into corresponding partition areas based on the distance between the network nodes in the underlying physical network and the initial clustering centers contained in the partition area; calculating the proximity center of the network nodes in each partition area, and taking the network node with the smallest proximity center in the partition area as the target clustering center; determining the VNF deployment candidate node set based on the target clustering centers of all partition areas; wherein the target clustering center of each partition area is the VNF deployment candidate node of the current partition area, and each VNF deployment candidate node corresponds to a candidate deployment scheme; Calculating the betweenness centrality in a given destination node set corresponding to each network node in the network of the VNF node to be deployed after the data packet is transmitted on each data transmission link, including: increasing the betweenness centrality in a given destination node set corresponding to the network node by a preset unit each time a data packet generated in the network of the VNF node to be deployed passes through a network node; when all data packets in the network of the VNF node to be deployed have arrived at the destination node, determining the betweenness centrality in a given destination node set corresponding to each network node in the network of the VNF node to be deployed; Determine the VNF deployment target node set based on the betweenness centrality in the given destination node set, including: determine the network node whose betweenness centrality in the given destination node set meets the preset deployment conditions as the VNF deployment node of the current candidate deployment scheme; determine the VNF deployment node with the smallest betweenness centrality in the given destination node set among multiple candidate deployment schemes as the VNF deployment target node set.

2. The VNF deployment method based on network traffic convergence according to claim 1, characterized in that: Multiple data transmission links are determined based on each source node and the corresponding destination node, including: Generate a data packet of a first data volume through a source node, and send the data packet to a network of a VNF node to be deployed; When the data packet is transmitted to the current node in the network of the VNF node to be deployed, the network node distances of all network nodes adjacent to the current node and the destination node are calculated, and the network node with the smallest network node distance is used as the next hop forwarding node of the current node; When all data packets in the network of the VNF node to be deployed arrive at the destination node, the corresponding data transmission link is determined based on the source node, multiple next-hop forwarding nodes and the destination node; different source nodes correspond to different data transmission links, and multiple data transmission links are determined based on different source nodes, next-hop network nodes and destination nodes.

3. The VNF deployment method based on network traffic convergence according to claim 2, characterized in that: The method further comprises: If two or more next-hop forwarding nodes are included at the same time, weighted processing is performed on the data packet: the first shortest path number between the current node and the destination node is calculated, the second shortest path number between each next-hop node and the destination node is calculated, and the data packet is weighted based on the first data volume of the data packet, the first shortest path number, and the second shortest path number to obtain the second data volume of the data packet sent to the next-hop network node; The weighted data packet is sent to each of the next-hop forwarding nodes.

4. The VNF deployment method based on network traffic convergence according to claim 1, characterized in that: The method further comprises: The network throughput upper limit is determined based on the VNF deployment target node set.

5. A VNF deployment device based on network traffic convergence, characterized in that: For implementing the method according to claim 1, the device comprises: The deployment candidate module is used to partition the underlying physical network based on the network node distance and calculate the corresponding VNF deployment candidate node set after partitioning; A network traffic transmission module is used to obtain a network of a VNF node to be deployed, take each network node in the network of the VNF node to be deployed as a source node in turn, take the candidate node closest to the source node in the VNF deployment candidate node set as a destination node corresponding to the source node, and determine a data transmission link based on each source node and the corresponding destination node; The VNF deployment module is used to calculate the betweenness centrality in a given destination node set corresponding to each network node in the network of the VNF node to be deployed after the data packet is transmitted on each data transmission link, and determine the VNF deployment target node set based on the betweenness centrality in the given destination node set, so as to deploy the VNF based on the VNF deployment target node set; wherein the betweenness centrality in the given destination node set is used to measure the convergence of network traffic.

6. An electronic device, characterized in that: It includes a processor and a memory, the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the VNF deployment method based on network traffic convergence as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions. When the computer-executable instructions are called and executed by the processor, the computer-executable instructions prompt the processor to implement the VNF deployment method based on network traffic convergence as described in any one of claims 1 to 4.

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