CN115967636A

Movatterモバイル変換

Info

Publication number: CN115967636A
Application number: CN202211637487.5A
Authority: CN
Inventors: 彭修红
Original assignee: Unihub China Information Technology Co Ltd
Current assignee: Unihub China Information Technology Co Ltd
Priority date: 2022-12-16
Filing date: 2022-12-16
Publication date: 2023-04-14
Anticipated expiration: 2042-12-16
Also published as: CN115967636B

Abstract

The invention discloses a flow simulation method and a device for split network node capacity expansion, wherein the method comprises the following steps: importing node splitting planning execution simulation; generating a simulation network topology based on simulation conditions such as splitting of the reference topology superposed nodes; determining the boundary of the network topology simulation; abstracting each province into a network object, and taking the split new nodes as new virtual simulation network objects; acquiring edge traffic, and distributing the original node traffic to split nodes; obtaining a simulation routing table for the simulation network topology based on an SPF algorithm; the edge flow is combined with the simulation routing table to calculate the flow; and comparing the real network flow with the simulated network flow to analyze the influence and obtain a simulation conclusion. The invention combines the current network flow and the route as well as the simulation condition to carry out flow simulation on the expanded network, carries out flow prediction, evaluates the rationality of the expansion scheme according to the prediction result and the real network data, modifies the implementation scheme to carry out simulation prediction, and avoids the repeated construction of the project.

Description

Flow simulation method and device for split network node capacity expansion

Technical Field

The invention relates to the field of network transmission, in particular to a flow simulation method and a flow simulation device for splitting network node capacity expansion.

Background

In an operator network, when traffic flow of some provinces increases dramatically, congestion of some links in an original network may be caused to affect service quality, capacity expansion needs to be performed on the network at this time, and traffic distribution can be implemented by adding device nodes (hereinafter referred to as nodes) to reduce the load of the existing network, but several nodes should be added, how to perform networking between the newly added nodes and the existing nodes, and new problems will not be caused after networking? These are unpredictable.

The simplified operator network model is shown in fig. 1:

by docking IGP (interior gateway protocol)/BGP (border gateway protocol) and other related protocols, the related data are collected and analyzed and processed according to the standard, and the network topology is constructed.

Flow interaction between provinces needs to pass through a group of network nodes, a network formed by the group of nodes is called a backbone network, namely the network needs to be simulated, the backbone network comprises backbone nodes of the provinces, and the backbone nodes are mutually communicated (the communicated lines are called links) to realize flow exchange. The backbone nodes of each province bear the services of different cities of the province. If the traffic of the business in Gansu province only bears the services of all cities, as shown in FIG. 1, the bearing pressure of the node in Gansu province 1 is getting higher and higher, and the business borne by Gansu province 1 needs to be split into a part in order to improve the service quality, so that a new node in Gansu province 2 is planned and is connected with Jiangsu 2, beijing 1 and Gansu province 1 respectively, the newly added node and link are represented by dotted lines to be virtual, and then the businesses in Lanzhou and Jiayuguan province are migrated to Gansu province 2, as shown in FIG. 2.

The traditional mode is that the number of expanded nodes and how to perform networking after expansion are generally evaluated according to personal experience, then engineering implementation is started, and after the engineering implementation is completed, the existing scheme is adjusted according to the actual operation condition and then the construction is repeated.

Disclosure of Invention

In order to solve the problems in the prior art, the invention provides a flow simulation method and a flow simulation device for splitting network node expansion, which are used for carrying out flow simulation on an expanded network by combining the current network flow, the route and the simulation conditions so as to achieve the capacity of flow prediction, evaluating whether an expansion scheme is reasonable or not by comparing the prediction result with real network data, and repeatedly modifying an implementation scheme for carrying out simulation prediction so as to avoid repeated construction of a project.

In order to achieve the purpose, the invention adopts the following technical scheme:

in an embodiment of the present invention, a traffic simulation method for splitting capacity expansion of a network node is provided, where the method includes:

s01, importing a node splitting plan to execute simulation, importing the nodes to be split, the newly added nodes and link information, and forming a new simulation network model on the basis of the current network real network according to the splitting plan;

s02, generating a simulation network topology based on simulation conditions such as splitting of a reference topology superposition node;

s03, determining the boundary of network topology simulation, wherein the nodes do not generate flow and are only used for bearing the flow, nodes connected with each province in a backbone network are called edge nodes, and the edge nodes are the boundary of the network simulation;

s04, abstracting each province into a network object, and taking the split new nodes as new virtual simulation network objects;

s05, acquiring edge flow, and distributing the original node flow to split nodes;

s06, obtaining a simulation routing table for the simulation network topology based on an SPF algorithm;

s07, combining the edge flow with a simulation routing table to calculate the flow;

and S08, comparing the real network flow with the simulated network flow to analyze the influence, and obtaining a simulation conclusion.

Further, the S05 includes:

s051, collecting the flow component information of the edge node inflow port through the Netflow protocol, and obtaining the flow from each source address to each target address.

And S052, splitting the flow components of the virtual nodes from the real nodes through calculation.

Further, the flow component splitting manner in S052 is as follows:

the flow flowing into the real node is divided into two parts, one part is a flow component of the virtual network flowing through the virtual node to other provincial networks, the other part is the flow component of the virtual network flowing through the real node, the flow component flowing through the virtual node is removed, and the flow component information is obtained, wherein the format of the flow component information is as follows: the node comprises a source address, a target address and a flow value.

Further, the S06 includes:

s061, taking a backbone network edge node connected with each province network as a next hop of each province network;

s062, combining with an IGP protocol, obtaining the shortest path from one node to another node in the backbone network through an SPF algorithm, and further obtaining the shortest path from a certain source address in each province network to a certain target address in other province networks;

s063, calculating the shortest path to obtain the simulation routing table, the format is: source address, destination address, next hop node, link 1-link N.

Further, the S07 includes: and obtaining flow components on each link in the backbone network based on the flow components and the routing table, adding the flow components on each link to obtain the flow on each link, and further obtaining the flow size and the flow utilization rate of each link of the simulated backbone network, thereby judging whether network congestion is caused.

Further, the traffic utilization is calculated by calculating a percentage of traffic/link bandwidth.

In an embodiment of the present invention, a traffic simulation apparatus for splitting capacity expansion of a network node is further provided, where the modifying means includes:

the method comprises the steps of importing a node module, importing a node splitting plan to execute simulation, importing nodes needing splitting and newly-added nodes and link information, and forming a new simulation network model on the basis of a current network real network according to the splitting plan;

the simulation network topology generation module generates a simulation network topology based on simulation conditions such as splitting of a reference topology superposition node and the like;

the boundary determining module is used for determining the boundary of network topology simulation, the node does not generate flow and is only used for bearing the flow, nodes connected with each province in a backbone network are called edge nodes, and the edge nodes are the boundary of the network simulation;

the new node splitting module abstracts each province into a network object, and takes the split new nodes as new virtual simulation network objects;

the edge flow acquisition module acquires edge flow and distributes the original node flow to the split node;

the routing table acquisition module is used for acquiring a simulation routing table for the simulation network topology based on an SPF algorithm;

the flow calculation module and the edge flow are combined with the simulation routing table to calculate the flow;

and the simulation conclusion module compares the real network flow with the simulated network flow to carry out influence analysis so as to obtain a simulation conclusion.

Further, the edge traffic acquiring module includes:

the flow size acquisition module acquires flow component information of an edge node inflow port through a Netflow protocol, and acquires the flow size from each source address to each target address;

and the flow component splitting module splits the flow components of the virtual nodes from the real nodes through calculation.

Further, the flow component splitting mode in the flow component splitting module is as follows:

Further, the routing table obtaining module comprises:

the next hop determining module is used for taking the edge node of a backbone network connected with each province network as the next hop of each province network;

the shortest path acquisition module is combined with an IGP (integrated waveguide protocol) to obtain the shortest path from one node to another node in the backbone network through an SPF (specific pathogen free) algorithm, so that the shortest path from a certain source address in each provincial network to a certain target address in other provincial networks can be obtained;

the simulation routing table calculation module calculates the shortest path to obtain the simulation routing table, and the format is as follows: the source address is the target address, the next hop node is the link 1-link N.

Further, the flow calculation module includes: and obtaining flow components on each link in the backbone network based on the flow components and the routing table, adding the flow components on each link to obtain the flow on each link, and further obtaining the flow size and the flow utilization rate of each link of the simulated backbone network, thereby judging whether network congestion is caused.

Further, the flow utilization rate is calculated in the following manner: (throughput/link bandwidth) 100%.

Has the beneficial effects that:

the invention abstracts a complex network in reality into a visual network topology, shows a virtualized split node in the network topology in a visual mode, and combines a real route and a virtual route to obtain a new simulated route; splitting the flow on the link into flow components by using a general division idea to perform simulation calculation, and summarizing simulation results into link total flow; different node splitting schemes can be modified to simulate different construction schemes, and the optimal scheme is selected for construction to avoid rework.

Drawings

FIG. 1 is a schematic diagram of a prior art operator network model;

FIG. 2 is a schematic diagram of an operator simulation network model;

FIG. 3 is a schematic diagram of a simulation network model for carrying a split-out virtual network in an embodiment;

FIG. 4 is a flow diagram illustrating a flow simulation method for split network node capacity expansion according to the present invention;

FIG. 5 is a schematic structural diagram of a traffic simulation apparatus for capacity expansion of split network nodes according to the present invention;

fig. 6 is a schematic structural diagram of a computer device according to an embodiment of the present invention.

Detailed Description

The principles and spirit of the present invention will be described below with reference to several exemplary embodiments, which should be understood to be presented only to enable those skilled in the art to better understand and implement the present invention, and not to limit the scope of the present invention in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

As will be appreciated by one skilled in the art, embodiments of the present invention may be embodied as a system, apparatus, device, method, or computer program product. Accordingly, the present disclosure may be embodied in the form of: entirely hardware, entirely software (including firmware, resident software, micro-code, etc.), or a combination of hardware and software.

The terms and explanations relating to the present invention:

SPF shortest Path first algorithm.

Node one device can be regarded as one node.

Network here is an abstraction, a province can be regarded as a network, and a prefix can also be regarded as a network.

According to the embodiment of the invention, the flow simulation method and the flow simulation device for split network node expansion are provided, the running state of CPE can be monitored in real time, and enterprises can conveniently and timely eliminate obstacles and reduce enterprise loss.

The principles and spirit of the present invention are explained in detail below with reference to several exemplary embodiments of the present invention.

As shown in fig. 4, the method includes:

s01, importing a node splitting plan to execute simulation, importing the nodes to be split and the newly added nodes and link information, and forming a new simulation network model on the basis of the current network real network according to the splitting plan;

s03, determining the boundary of network topology simulation, wherein the nodes do not generate flow and are only used for bearing the flow, nodes connected with provinces in a backbone network are called edge nodes, and the edge nodes are the boundary of the network simulation;

The S05 comprises:

s051, acquiring flow component information of an edge node inflow port through a Netflow protocol, and acquiring the flow from each source address to each target address;

The flow component splitting mode in the S052 is as follows:

The S06 includes:

The S07 comprises: and obtaining flow components on each link in the backbone network based on the flow components and the routing table, adding the flow components on each link to obtain the flow on each link, and further obtaining the flow size and the flow utilization rate of each link of the simulated backbone network so as to judge whether network congestion is caused.

The traffic utilization is calculated as a percentage from traffic/link bandwidth.

It should be noted that although the operations of the method of the present invention have been described in the above embodiments and the accompanying drawings in a particular order, this does not require or imply that these operations must be performed in this particular order or that all of the illustrated operations must be performed to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.

For a clearer explanation of the above traffic simulation method for capacity expansion of split network nodes, a specific embodiment is described below, but it should be noted that this embodiment is only for better illustrating the present invention, and is not to be construed as an undue limitation on the present invention.

Taking the background technology as an example to explain:

the introduced node splitting rule is superimposed on the basis of the basic topology of fig. 1 to generate a simulated network topology as shown in fig. 2. The simulation network is equivalent to that 1 node Gansu 2, three links Gansu 2-Gansu 1, gansu 2-Jiangsu 2 and Gansu 2-Beijing 1 are newly added on the basis of basic topology.

as shown in fig. 2, nodes of Jiangsu 1, jiangsu 2, gansu 1, gansu 2, beijing 1 and Beijing 2 in the network do not generate traffic but are used for carrying traffic, nodes connected with various provinces in a backbone network are called edge nodes, and the edge nodes are boundaries of network simulation. We simulate how incoming traffic from border nodes is transported in the backbone network.

referring to fig. 3, the backbone network is regarded as a large network, and provinces and cities connected with the backbone network can be regarded as small networks. We are ready to split out part of the traffic in the gansu network, and we can create a virtual network such as the gansu virtual network for carrying the split-out traffic.

after the edge of the backbone network and each provincial network thereof are determined, the simulation is actually changed into the simulation that the flow of each provincial network reaches other provincial networks after passing through the backbone network through the edge node of the backbone network.

Each provincial network is actually a set of IP addresses, which is known information of the operator that can be used as the underlying data.

The influence of node splitting on the existing network can be obtained by comparing the traffic utilization rate of each link before and after simulation, and the traffic of the virtual link can be obtained so as to obtain the bandwidth required by the capacity expansion link. According to the simulation data, whether the splitting scheme is reasonable or not can be evaluated. Meanwhile, a plurality of splitting schemes can be prepared, and the simulation results of the plurality of splitting schemes are compared to select the optimal splitting scheme.

The S05 comprises:

s051, collecting the flow component information of the edge node inflow port through the Netflow protocol, and obtaining the flow from each source address to each target address. But we just know that the traffic data of the real node cannot directly acquire the traffic component of the split virtual node Gansu 2.

The flow component splitting mode in the S052 is as follows:

the flow flowing into the real node is divided into two parts, one part is the flow component of the virtual network flowing through the virtual node to other provincial networks, the other part is the flow component of the real node, the flow component flowing through the virtual node is removed, the flow component information is obtained, and the format is as follows: the node comprises a source address, a target address and a flow value.

The traffic flowing into Gansu 1 from Gansu network is split into two parts, one part is that the Gansu virtual network (a group of IP addresses) flows through Gansu 2 to other provincial networks and the original traffic flowing through Gansu 1 is removed from the traffic flowing through Gansu 2. We can obtain flow component information of the following structure: the node comprises a source address, a target address and a flow value.

The S06 includes:

s061, using a backbone network edge node connected with each province network as a next hop of each province network;

s062, combining an IGP protocol to obtain the shortest path from one node to another node in the backbone network through an SPF algorithm, and further obtaining the shortest path from a certain source address in each provincial network to a certain target address in other provincial networks;

For the split Gansu virtual network, the address of which the target address is the range of the Gansu virtual network in all the flow components can be set as the next hop of the address to be node Gansu 2. Calculating the shortest path, the simulation routing table with the following structure can be obtained: the source address is the target address, the next hop node is the link 1, the link 2, and the link is a connecting line between the two nodes.

The traffic utilization is calculated as a percentage from traffic/link bandwidth. The port bandwidth of each node can be collected through the snmp protocol.

Based on the same invention concept, the invention also provides a flow simulation device for splitting the capacity expansion of the network nodes. The implementation of the device can be referred to the implementation of the method, and repeated details are not repeated. The term "module," as used below, may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Fig. 5 is a schematic structural diagram of a traffic simulation apparatus for capacity expansion of split network nodes according to the present invention. As shown in fig. 5, the apparatus includes:

theimport node module 110, the import node splitting plan and the execution simulation, importing the nodes to be split and the newly added nodes and link information, and forming a new simulation network model based on the splitting plan on the basis of the current network real network;

the simulation networktopology generation module 120 generates a simulation network topology based on simulation conditions such as splitting of a reference topology superposition node;

theboundary determining module 130 determines the boundary of the network topology simulation, the node itself does not generate traffic and is only used for bearing the traffic, and nodes connected with each province in the backbone network are called edge nodes, and the edge nodes are the boundary of the network simulation;

the newnode splitting module 140 abstracts each province into a network object, and takes the split new nodes as new virtual simulation network objects;

the edgetraffic acquiring module 150 acquires edge traffic and distributes the original node traffic to split nodes;

the routingtable acquisition module 160 obtains a simulation routing table for the simulation network topology based on an SPF algorithm;

theflow calculation module 170, the edge flow and the simulation routing table are combined to calculate the flow;

thesimulation conclusion module 180 compares the real network traffic with the simulated network traffic to perform impact analysis, so as to obtain a simulation conclusion.

The edgetraffic obtaining module 150 includes:

The flow component splitting mode in the flow component splitting module is as follows:

The routingtable obtaining module 160 includes:

the shortest path acquisition module is combined with an IGP protocol to obtain the shortest path from one node to another node in the backbone network through an SPF algorithm, and further the shortest path from a certain source address in each provincial network to a certain target address in other provincial networks can be obtained;

the simulation routing table calculation module calculates the shortest path to obtain the simulation routing table, and the format of the simulation routing table is as follows: source address, destination address, next hop node, link 1-link N.

Theflow calculation module 170 includes: and obtaining flow components on each link in the backbone network based on the flow components and the routing table, adding the flow components on each link to obtain the flow on each link, and further obtaining the flow size and the flow utilization rate of each link of the simulated backbone network, thereby judging whether network congestion is caused.

The flow utilization rate calculation mode is as follows: (throughput/link bandwidth) 100%.

It should be noted that although several modules of the traffic simulation apparatus that split the capacity of the network node are mentioned in the above detailed description, such partitioning is merely exemplary and not mandatory. Indeed, the features and functionality of two or more of the modules described above may be embodied in one module according to embodiments of the invention. Conversely, the features and functions of one module described above may be further divided into embodiments by a plurality of modules.

Based on the aforementioned inventive concept, as shown in fig. 6, the present invention further provides acomputer device 200, which includes amemory 210, aprocessor 220, and acomputer program 230 stored in thememory 210 and capable of running on theprocessor 220, where when theprocessor 220 executes thecomputer program 230, the traffic simulation method for capacity expansion of the split network node is implemented.

Based on the above inventive concept, the present invention further provides a computer-readable storage medium, where a computer program for executing the traffic simulation method for capacity expansion of the split network node is stored in the computer-readable storage medium.

The invention abstracts a complex network in reality into a visual network topology, shows a virtualized split node in the network topology in a visual form, and combines a real route and a virtual route to obtain a new simulated route; splitting the flow on the link into flow components by using a general branch idea to perform simulation calculation, and summarizing simulation results into total flow of the link; different node splitting schemes can be modified to simulate different construction schemes, and the optimal scheme is selected for construction to avoid rework.

While the spirit and principles of the invention have been described with reference to several particular embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, nor is the division of aspects, which is for convenience only as the features in such aspects may not be combined to benefit. The invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.

It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.

The limitation of the protection scope of the present invention is understood by those skilled in the art, and various modifications or changes which can be made by those skilled in the art without inventive efforts based on the technical solution of the present invention are still within the protection scope of the present invention.

Claims

1. A flow simulation method for splitting capacity expansion of network nodes is characterized by comprising the following steps:

2. The traffic simulation method for capacity expansion of split network nodes according to claim 1, wherein the S05 includes:

3. The capacity expansion traffic simulation method for splitting network nodes according to claim 2, wherein the traffic component splitting manner in S052 is:

splitting the flow flowing into the real node into two parts, wherein one part is a flow component of the virtual network flowing through the virtual node to other provincial networks, and the other part is the flow component of the virtual network flowing through the real node, and the flow component of the virtual node is removed to obtain flow component information, and the format of the flow component information is as follows: the node comprises a source address, a target address and a flow value.

4. The traffic simulation method for capacity expansion of split network node according to claim 1, wherein the S06 includes:

5. The capacity expansion traffic simulation method for split network nodes according to claim 1, wherein the S07 includes:

s071, obtaining flow components on each link in the backbone network based on the flow components and the routing table;

s072, adding the flow components on each link to obtain the flow on each link;

s073, obtaining the flow of each link of the simulated backbone network and the flow utilization rate thereof, thereby judging whether network congestion is caused.

6. The capacity-expansion traffic simulation method for split network nodes according to claim 1, wherein the traffic utilization is calculated in a manner that: (throughput/link bandwidth) 100%.

7. A flow simulation device for capacity expansion of split network nodes is characterized by comprising:

the method comprises the steps of importing a node module, importing a node splitting plan to execute simulation, importing nodes needing splitting, newly-added nodes and link information, and forming a new simulation network model on the basis of a current network real network according to the splitting plan;

the edge flow acquisition module acquires edge flow and distributes the original node flow to the split nodes;

8. The capacity-expansion traffic simulation apparatus for split network nodes according to claim 7, wherein the edge traffic obtaining module includes:

9. The capacity-expanded traffic simulation apparatus for splitting network nodes according to claim 8, wherein the traffic component splitting module performs the following traffic component splitting modes:

10. The traffic simulation apparatus for capacity expansion of split network nodes according to claim 7, wherein the routing table obtaining module includes:

the simulation routing table calculation module calculates the shortest path to obtain the simulation routing table, and the format is as follows: source address, destination address, next hop node, link 1-link N.

11. The capacity-expanded traffic simulation device according to claim 7, wherein the traffic calculation module includes: and obtaining flow components on each link in the backbone network based on the flow components and the routing table, adding the flow components on each link to obtain the flow on each link, and further obtaining the flow size and the flow utilization rate of each link of the simulated backbone network so as to judge whether network congestion is caused.

12. The capacity-expansion traffic simulation apparatus for splitting network nodes according to claim 11, wherein the traffic utilization calculation manner is: (throughput/link bandwidth) 100%.

13. A computer arrangement comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 1-6 when executing the computer program.

14. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program for executing the method of any one of claims 1-6.