CN115834392A

CN115834392A - Network capacity determination method and device, electronic equipment and storage medium

Info

Publication number: CN115834392A
Application number: CN202211153777.2A
Authority: CN
Inventors: 赵永利; 宁云潇; 张�杰
Original assignee: Beijing University of Posts and Telecommunications
Current assignee: Beijing University of Posts and Telecommunications
Priority date: 2022-09-21
Filing date: 2022-09-21
Publication date: 2023-03-21

Abstract

The application provides a network capacity determination method, a network capacity determination device, electronic equipment and a storage medium. The method comprises the following steps: establishing a communication network simulation model according to a satellite communication network architecture to determine a satellite communication network topology connection relation; the satellite communication network topology connection relation comprises: a adjacency matrix sequence, the adjacency matrix sequence comprising: a plurality of adjacency matrices; traversing the adjacent matrix sequence according to a preset sequence, and segmenting all adjacent matrices to determine a topological slice sequence; traversing the topology slice sequence according to an abstract rule and a service model, and abstracting the topology slice sequence to determine an abstract topology slice sequence; and determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence, and determining the network capacity according to the capacity sequence and the maximum flow path sequence. The topology abstraction can convert heterogeneous network topology into a general network model, thereby reducing the simulation complexity of network capacity and reducing the consumption of computing resources.

Description

Network capacity determination method and device, electronic equipment and storage medium

Technical Field

The present application relates to the field of network evaluation technologies, and in particular, to a method and an apparatus for determining network capacity, an electronic device, and a storage medium.

Background

In the related art, the traffic of the network is usually evaluated and determined by a link bandwidth superposition estimation method or a discrete event system simulation method, but for a high-dynamic satellite network and service traffic, the discrete event system simulation method has the problems of complex setting, long simulation time and the like, flexible adaptation to a high-dynamic satellite topology cannot be realized, and the simulation setting has the problems of poor flexibility and low result universality.

Disclosure of Invention

In view of the above, an object of the present application is to provide a network capacity determining method, apparatus, electronic device and storage medium.

Based on the object, in a first aspect, the application provides a network capacity determining method, including:

establishing a communication network simulation model according to a satellite communication network architecture to determine a satellite communication network topology connection relation; wherein, the topology connection relationship of the satellite communication network comprises: a adjacency matrix sequence, the adjacency matrix sequence comprising: a plurality of adjacency matrices;

traversing the adjacent matrix sequence according to a preset sequence, and segmenting all the adjacent matrices to determine a topological slice sequence;

traversing the topology slice sequence according to an abstract rule and a service model, and abstracting the topology slice sequence to determine an abstract topology slice sequence;

and determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence, and determining the network capacity according to the capacity sequence and the maximum flow path sequence.

In one possible implementation manner, the establishing a communication network simulation model according to a satellite communication network architecture to determine a satellite communication network topology connection relationship includes:

determining a network node set according to the satellite communication network architecture; wherein the set of network nodes comprises: a satellite node set and a ground station node set;

bidirectionally connecting each node in the network node set to determine a link set;

establishing the communication network simulation model according to the network node set and the link set;

operating the communication network simulation model by taking a satellite orbit period as simulation duration so as to determine the topological connection relation of the satellite communication network; the satellite communication network topology connection relationship comprises: a sequence of adjacency matrices; the adjacency matrix sequence comprises: a plurality of adjacency matrices;

wherein any one of the adjacency matrices is expressed as

Wherein A is _i An adjacency matrix of a satellite and a ground station in the satellite network at the moment i is represented, m is the number of nodes in a network set V, T represents a simulation period, e _jk Representing a node v _j To node v _k The physical distance of the directed link.

In a possible implementation manner, the traversing the adjacency matrix sequence according to a preset order and segmenting all the adjacency matrices to determine a topology slice sequence includes:

sequentially traversing and analyzing the sequence of the adjacency matrix according to the sequence of the sequence numbers of the adjacency matrix from small to large;

determining a first topological slice corresponding to the current adjacency matrix;

determining whether the feed link of the next adjacent matrix is changed in on-off;

determining the topology slice of the next adjacent matrix as a second topology slice in response to the on-off change of the feeder link of the next adjacent matrix; wherein the first topological slice is different from the second topological slice;

and determining the topological slice sequence according to the topological slices corresponding to all the adjacency matrixes.

In one possible implementation, the topological slice sequence includes: a plurality of topological slices; the adjacency matrix includes: accessing a satellite node and a gateway station node;

traversing the topology slice sequence according to an abstraction rule and a business model, and abstracting the topology slice sequence to determine an abstract topology slice sequence, including:

for each topological slice and the corresponding adjacency matrix,

adding a virtual input node and a virtual output node to the adjacency matrix, connecting the virtual input node with the access satellite node according to the attribute of a network node, and connecting the virtual output node with the gateway station node to determine an abstract topological adjacency matrix;

determining a plurality of abstract topological adjacent matrixes according to the adjacent matrix sequence and the topological slice sequence, and determining a plurality of abstract topological slices according to the plurality of abstract topological adjacent matrixes;

determining the sequence of abstract topology slices from the plurality of abstract topology slices.

In one possible implementation, the determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence, and determining a network capacity according to the capacity sequence and the maximum flow path sequence includes:

determining a maximum flow and a maximum flow path between the virtual input node and the virtual output node in each abstract topology slice by using a Boykov-Kolmogorov algorithm, determining the capacity sequence C according to the maximum flow of each abstract topology slice, and determining the maximum flow path sequence GF according to the maximum flow path of each abstract topology slice;

determining the network capacity according to a determination formula; wherein the determination formula is expressed as

C _network ＝min(C)

Wherein, C _network Representing network capacity.

In a possible implementation manner, after determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence and determining a network capacity according to the capacity sequence and the maximum flow path sequence, the method further includes:

and configuring a node routing table entry according to the network capacity, and guiding a forwarding path of network traffic by the network capacity so as to enable the actual traffic of the satellite communication network to reach the network capacity.

In a second aspect, the present application provides a network capacity determination apparatus, comprising:

the first determination module is configured to establish a communication network simulation model according to the satellite communication network architecture so as to determine the topological connection relation of the satellite communication network; wherein, the topology connection relationship of the satellite communication network comprises: a adjacency matrix sequence, the adjacency matrix sequence comprising: a plurality of adjacency matrices;

a segmentation module configured to traverse the adjacency matrix sequence according to a preset order and segment all the adjacency matrices to determine a topological slice sequence;

an abstraction module configured to traverse the sequence of topology slices according to an abstraction rule and a business model and abstract the sequence of topology slices to determine an abstract sequence of topology slices;

a second determining module configured to determine a capacity sequence and a maximum flow path sequence from the abstract topology slice sequence, and determine a network capacity from the capacity sequence and the maximum flow path sequence.

In one possible implementation, the first determining module is further configured to:

operating the communication network simulation model by taking a satellite orbit period as simulation duration to determine the topological connection relation of the satellite communication network; the satellite communication network topology connection relationship comprises: a sequence of adjacency matrices; the adjacency matrix sequence comprises: a plurality of adjacency matrices;

wherein any one adjacency matrix is represented as

Wherein A is _i Representing the adjacency matrix of satellites and ground stations in the satellite network at time i, T representing the simulation period, e _jk Representing a node v _j To node v _k The physical distance of the directed link.

In a third aspect, the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the network capacity determination method according to the first aspect when executing the program.

In a fourth aspect, the present application provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the network capacity determination method of the first aspect.

As can be seen from the foregoing, according to the network capacity determining method, device, electronic device and storage medium provided by the present application, a communication network simulation model is established according to a satellite communication network architecture to determine a satellite communication network topology connection relationship; wherein, the topology connection relationship of the satellite communication network comprises: a adjacency matrix sequence, the adjacency matrix sequence comprising: a plurality of adjacency matrices; traversing the adjacent matrix sequence according to a preset sequence, and segmenting all the adjacent matrices to determine a topological slice sequence; traversing the topology slice sequence according to an abstract rule and a service model, and abstracting the topology slice sequence to determine an abstract topology slice sequence; and determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence, and determining the network capacity according to the capacity sequence and the maximum flow path sequence. By dividing the dynamic satellite communication network topology into a series of topology slices, converting the topology slices into a generalized abstract topology, and further utilizing a network flow algorithm to calculate the flow value which can be borne by the abstract topology, the evaluation performance of network evaluation on a high-dynamic satellite network is met while the refined evaluation of the network capacity is ensured, and the flexible adaptation of the heterogeneous network and the multi-service requirements existing in a satellite network scene is realized. The topology abstraction technology can convert heterogeneous network topology into a general network model, so as to simplify the network topology, further reduce the simulation complexity of network capacity, reduce the consumption of computing resources, and provide flexible adaptation capability to different service models.

Drawings

In order to more clearly illustrate the technical solutions in the present application or the related art, the drawings needed to be used in the description of the embodiments or the related art will be briefly introduced below, and it is obvious that the drawings in the following description are only embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.

Fig. 1 shows a schematic structural diagram of a satellite communication network architecture.

Fig. 2 shows an exemplary flowchart of a network capacity determination method provided in an embodiment of the present application.

Fig. 3 shows a schematic structural diagram of a satellite communication network topology.

Fig. 4 shows a schematic structural diagram of an abstract topology of a satellite communication network.

Fig. 5 shows a schematic structure diagram of a satellite communication network-space segment architecture.

Fig. 6 shows an abstract topological diagram corresponding to a topological slice.

Figure 7 shows a schematic diagram of a terrestrial gateway station network architecture.

Fig. 8 shows an abstract topological diagram corresponding to another topological slice.

Fig. 9 shows an exemplary structural diagram of a network capacity determining apparatus provided in an embodiment of the present application.

Fig. 10 shows an exemplary structural schematic diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is further described in detail below with reference to specific embodiments and the accompanying drawings.

It should be noted that technical terms or scientific terms used in the embodiments of the present application should have a general meaning as understood by those having ordinary skill in the art to which the present application belongs, unless otherwise defined. The use of "first," "second," and similar terms in the embodiments of the present application do not denote any order, quantity, or importance, but rather the terms are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element or item listed before the word covers the element or item listed after the word and its equivalents, but does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.

Referring to fig. 1, currently, the mainstream low-earth orbit satellite constellation is mostly located in a low-earth orbit of 1000-1400 km, and data information is transmitted in a space segment and a ground segment of a satellite network by means of microwave or laser links. Data can be transmitted from the ground terminal to the access satellite, forwarded through the satellite network, and finally transmitted to the ground gateway station by the feed satellite. In the data transmission process, the single-hop communication transmission delay is about 7 milliseconds after passing through the access link, the inter-satellite link and the feeder link, and the transmission delay of data from the terminal to the gateway station can be maintained within 50 milliseconds considering the influence of other factors on the delay, and is equivalent to the delay of a ground optical fiber network.

As described in the background section, in the related art, when evaluating the traffic of the network, two methods are generally adopted, one is a link bandwidth superposition estimation method, and the other is a discrete event system simulation method.

The applicant finds, through research, that in the link bandwidth superposition estimation method, link bandwidth resources in a network are linearly superposed and used as an estimation value of network capacity, the influence of factors such as a service forwarding mode and the like on the network capacity cannot be considered, and a large error exists between an estimation result and actual network service carrying capacity.

In the discrete event system simulation method, a network operation model is generated in a software simulation tool, and discrete time simulation test is performed on dynamically generated service flows to finally obtain network capacity. The low earth orbit satellite network link duration is from second level to minute level, and the link quantity and node connection will be greatly changed between two adjacent topological states, which causes a great deal of service interruption and requires dynamic rerouting of services. In the high-dynamic scene of the satellite network, discrete event simulation is to count the resource states of the affected services and the network in real time, release path resources, recalculate a routing path, and issue signaling to deploy and activate service pipelines. As the network scale increases, the time for a single traffic path calculation increases exponentially, resulting in a simulation time that is much higher than the real-time requirement, e.g., when evaluating the network state within ten minutes, the running time of discrete event simulation reaches the order of hours. For a high-dynamic satellite network and service flow, the discrete event system simulation method has the problems of complex setting, long simulation time and the like, flexible adaptation of a high-dynamic satellite topology cannot be realized, and the high-speed development requirement of a satellite communication network cannot be met.

In addition, the setting of the service model has a great influence on the simulation result of the discrete event system, so that various networks and service models need to be tested and evaluated in practical application, and the simulation setting has the problems of poor flexibility, low result universality and the like due to the adoption of the discrete event system simulation method, and the flexible test and evaluation requirements of the networks are difficult to meet, so that the engineering guidance is poor.

Therefore, according to the network capacity determining method, the network capacity determining device, the electronic equipment and the storage medium, a communication network simulation model is established according to a satellite communication network architecture to determine a satellite communication network topology connection relation; wherein, the topology connection relationship of the satellite communication network comprises: a adjacency matrix sequence, the adjacency matrix sequence comprising: a plurality of adjacency matrices; traversing the adjacent matrix sequence according to a preset sequence, and segmenting all the adjacent matrices to determine a topological slice sequence; traversing the topology slice sequence according to an abstract rule and a service model, and abstracting the topology slice sequence to determine an abstract topology slice sequence; and determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence, and determining the network capacity according to the capacity sequence and the maximum flow path sequence. By dividing the dynamic satellite communication network topology into a series of topology slices, converting the topology slices into a generalized abstract topology, and further utilizing a network flow algorithm to calculate the flow value which can be borne by the abstract topology, the evaluation performance of network evaluation on a high-dynamic satellite network is met while the refined evaluation of the network capacity is ensured, and the flexible adaptation of the heterogeneous network and the multi-service requirements existing in a satellite network scene is realized. The topology abstraction technology can convert heterogeneous network topology into a general network model, so as to simplify the network topology, further reduce the simulation complexity of network capacity, reduce the consumption of computing resources, and provide flexible adaptation capability to different service models.

The network capacity determining method provided by the embodiment of the present application is specifically described below by using a specific embodiment.

Fig. 2 illustrates an exemplary flowchart of a network capacity determining method provided in an embodiment of the present application.

Referring to fig. 2, a method for determining network capacity provided in an embodiment of the present application specifically includes the following steps:

s202: establishing a communication network simulation model according to a satellite communication network architecture to determine a satellite communication network topology connection relation; wherein, the topology connection relationship of the satellite communication network comprises: a adjacency matrix sequence, the adjacency matrix sequence comprising: a plurality of adjacency matrices.

S204: traversing the adjacency matrix sequence according to a preset sequence, and segmenting all the adjacency matrices to determine a topology slice sequence.

S206: traversing the topology slice sequence according to an abstraction rule and a business model, and abstracting the topology slice sequence to determine an abstract topology slice sequence.

S208: and determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence, and determining the network capacity according to the capacity sequence and the maximum flow path sequence.

In some embodiments, with respect to step S202, a set of network nodes may be determined from the satellite communications network architecture; wherein the set of network nodes comprises: a satellite node set and a ground station node set; further, each node in the network node set is connected in a bidirectional mode to determine a link set; further, establishing the communication network simulation model according to the network node set and the link set; and then, operating the communication network simulation model by taking the satellite orbit period as the simulation duration so as to determine the topological connection relation of the satellite communication network.

Specifically, in this example, the number of satellite layers, the constellation type, the orbit height, the number of orbits, the number of orbiting satellites, the phase factor, the RAAN (Right Ascension of the Ascending Node) and the ground station coordinates are used as network parameters to establish a network simulation model. The simulation comprises two network nodes, namely a satellite node and a ground station node, wherein a network node set is marked as V = { Vs $ Vx }, a satellite node set is marked as Vs, and a ground station set is marked as Vx; the connections between the network nodes are bidirectional connections, and the set of links in the network is denoted as

E _jk Representing the actual presence of slaves v in the network _j Node to v _k One directed edge of the number node; the topology in the network is represented by graph G = (V, E). Generating an adjacent matrix sequence A = { A) by taking one satellite period T as simulation duration ₁ ,A ₂ ,…,A _T }; wherein the adjacency matrix A _i Comprises the following steps:

wherein A is _i Representing an adjacency matrix of satellites and ground stations in the time-i satellite network, i.e. the topological connection relationship G between the satellites and the ground stations in the time-i satellite network _i ＝(V _i ,E _i ),i∈[1,T]T denotes the simulation period, e _jk Representing a node v _j To node v _k When the network exists, the physical distance of the directed link is determined by the node v _j To node v _k When there is a directed link, e _jk Not 0, when there is no node v _j To node v _k Directed link time of e _jk ＝0。

In some embodiments, for step S204, the topology slices may be divided according to the increase or decrease of feeder links in the topology, that is, when one feeder link in the satellite network is established or removed, the slice is regarded as one slice. Traversing the network connection relation sequence A to obtain a topological slice sequence S = { S ] containing n slices ₁ ,S ₂ ,…,S _n }, in which:

wherein S is _i Representing the topological relation G in the ith slice _i ＝(V _i ,E _i ),i∈[1,n]N is the number of slices; each network slice comprises elements such as a satellite constellation, an inter-satellite link, a satellite-ground feeder link, a ground station and the like, and the satellite topological connection relation in each slice is not considered to be changed.

Referring to fig. 3, the satellite communication network capacity dynamic evaluation method based on topology abstraction solves the problem of complex simulation setup existing in the network capacity evaluation method based on discrete event system simulation under the condition of ensuring the rationality of network capacity evaluation, and overcomes the defect of poor engineering guidance caused by the dependence of simulation setup on a service model.

In some embodiments, for step S206, the adjacency matrix sequence may be sequentially analyzed in a traversal manner according to the sequence numbers of the adjacency matrices from small to large; determining a first topological slice corresponding to the current adjacency matrix; determining whether the feed link of the next adjacent matrix is changed in on-off state; determining the topology slice of the next adjacent matrix as a second topology slice in response to the on-off change of the feeder link of the next adjacent matrix; wherein the first topological slice is different from the second topological slice; and determining the topological slice sequence according to the topological slices corresponding to all the adjacency matrixes.

Referring to fig. 4, an abstract topology of a satellite communication network is composed of a plurality of terminals, a satellite, and a ground station, wherein service data enters the network at the terminals and is transmitted to the ground station through an access link, an inter-satellite link, and a feeder link.

In some embodiments, for each topology slice and corresponding adjacency matrix, a virtual input node and a virtual output node may be added to the adjacency matrix for step S208, and the virtual input node is connected to the access satellite node and the virtual output node is connected to the gateway station node according to the attribute of the network node to determine an abstract topology adjacency matrix; determining a plurality of abstract topological adjacency matrixes according to the adjacency matrix sequence and the topological slice sequence, and determining a plurality of abstract topological slices according to the plurality of abstract topological adjacency matrixes; determining the sequence of abstract topology slices from the plurality of abstract topology slices.

In this example, the service model specifies parameters such as access satellites and feeder satellites in the network, and link bandwidth. Respectively mapping a satellite set Vs to an access satellite set Va, a feed satellite set Vf and a transmission satellite set Vn according to a service model, abstracting all terminals of a satellite network into a virtual input node s, connecting the virtual input node with all elements in a preset access satellite set Va in the service model, and setting a link bandwidth according to a preset access bandwidth set(ii) a Reserving all inter-satellite connection relations and inter-satellite link bandwidths in the topology; connecting all elements in the ground station set Vx with the same virtual output node t, and setting the link bandwidth to be infinite; and a set V ' = { Va { [ Vn { [ Vf { [ Vx ] } Vs { [ Vx ]) represents an abstracted network node set, a set E ' represents an abstracted network link set, and a topology obtained by abstraction is represented by a graph G ' = (V ', E '). Traversing the topology slice sequence S, abstracting the obtained topology to generate an abstract topology slice sequence S' = { S ″) ₁ ,S` ₂ ,…,S` _n }, wherein:

wherein, S ″ _i Abstract topology G' representing the ith slice _i ＝(V` _i ,E` _i ),i∈[1,n]N is the number of abstract topology slices, and m is the number of nodes in the network set V; when the network exists by the node v ″) _j To node v _k Directed link time of b _jk Representing the bandwidth of the link, the bandwidth value being specified by the traffic model; when there is no node v _j To node v ″ _k Directed link time of b _jk ＝0。

In some embodiments, the ith abstract topological slice S' in the sequence S _i ,(i∈[1,n]) Calculating the maximum flow C from a virtual input node Vs to a virtual output node Vt in a slice using the Boykov-Kolmogorov algorithm _i (ii) a Traversing the sequence S' to obtain a capacity sequence C = { C) corresponding to the sequence S = { (C) } ₁ ,C ₂ ,…,C _n In this example, the service model calculates the network capacity C of the network using a deterministic formula _network 。

C _network ＝min(C)。

Fig. 5 shows a schematic structural diagram of a satellite communication network-space segment architecture.

Referring to fig. 5, in a particular embodiment, a network capacity assessment for a satellite communications network-space segment may be characterized by the architecture of fig. 5 for the satellite communications network.

In this embodiment, firstA network simulation model is established based on the satellite communication network architecture. The simulation comprises two network nodes, namely a satellite node and a ground station node, wherein a set of the network nodes is marked as V = { Vs = { Vx }, and a set of the satellite nodes is marked as Vs = { V } ₁ ,v ₂ ,…,v ₉ (set contains all satellite nodes like satellite v1, satellite v2, etc.), set of ground stations as Vx = { v } ₁₀ ,v ₁₁ ,v ₁₂ (a set contains all ground station nodes like ground station v10, ground station 11, etc.); the connections between the network nodes are bidirectional connections, and the link sets (inter-satellite links and feeder links) in the network are recorded as

E _jk Representing the actual presence of slaves v in the network _j Node to v _k One directed edge of the number node; performing satellite network operation simulation by using a satellite orbit period T as total simulation duration and 1 second as a simulation step length to obtain a network node adjacency corresponding to each simulation step length in a simulation period, in this embodiment, describing the adjacency of network nodes in an adjacency matrix manner, obtaining a set simulation period and a simulation step length through network operation simulation, and obtaining an adjacency matrix sequence A = { A } of a network operation condition ₁ ,A ₂ ,…,A _T In which the adjacency matrix A adjoins _i Comprises the following steps:

A _i showing the topological connection relation G between the satellite and the ground station in the satellite network at the moment i _i ＝(V _i ,E _i ),i∈[1,T]T is a simulation period, and the total number of nodes in the network set V is 12; when network exists, node v _j To node v _k Directed link time of e _jk Is equal to the physical distance of the link; when no node v exists _j To node v _k Directed link time of e _jk ＝0。

Further, according to the adjacency matrix A _i Sequence number i of the adjacent moment is traversed and analyzed from small to largeArray sequence a = { a = ₁ ,A ₂ ,…,A _T Will matrix A ₁ As the first slice S ₁ ＝A ₁ (ii) a During traversal, assume the current sequence A _i The corresponding slice is S _q When the latter sequence A _i+1 If the on-off change of the middle feed link does not occur, the sequence A _i+1 The corresponding slice is still S _q (ii) a If the feeder link in the latter sequence is subject to link tear down (e) _jk ≠0→e _jk = 0) or link establishment (e) _jk ＝0→e _jk Not equal to 0), the latter sequence a is then added _i+1 As a new section S _q+1 (ii) a The slice division process integrates the network connection relation sequence A into a topological slice sequence S = { S } containing n slices ₁ ,S ₂ ,…,S _n }, wherein:

Still further, referring to fig. 6, the topology abstraction is performed on the slices according to the abstraction rule and the service model. In the present embodiment, it is preferred that, for topological slice sequence S = { S = { S } ₁ ,S ₂ ,…,S _n And (4) adding a virtual input node and a virtual output node to each slice adjacency matrix, connecting the virtual input node with an access satellite node according to the attribute of the network node, and connecting the virtual output node with a gateway station to obtain an abstract topological adjacency matrix set. Slicing S with topology _q For example, the business model designates satellite 1-1 and satellite 1-2 as access satellites, the satellite 3-1 and the satellite 3-2 are feed satellites, and the satellite set Vs is divided into an access satellite set Va = { v = ₁ ,v ₂ And a feed satellite set Vf = { v = } ₇ ,v ₈ And a set of delivery satellites Vn = Vs- (Va @ Vf); abstracting all terminals of a satellite network into a virtual input node s, connecting the node s with all elements in a set Va, and setting a link bandwidth according to a preset access bandwidth set; reserving all inter-satellite connection relations and inter-satellite link bandwidths in the topology; connecting all elements in the set Vx with a virtual output node t, and setting the link bandwidth to be infinite; the set E 'represents the abstracted network link set, and the topology obtained by abstraction is represented by G' = (V ', E'). Traversing the topology slice sequence S, abstracting the obtained topology to generate an abstract topology slice sequence S' = { S ″) ₁ ,S` ₂ ,…,S` _n }, wherein:

wherein, S ″ _i Abstract topology G' representing the ith slice _i ＝(V` _i ,E` _i ),i∈[1,n]N is the number of abstract topological slices; when the network exists by the node v ″) _j To node v ″ _k Directed link time of b _jk Representing the bandwidth of the link; when there is no node v ″) _j To node v ″ _k When there is a directed link b _jk ＝0。

Still further, the process of traversing the abstract topological slice sequence S' = { S ″) ₁ ,S` ₂ ,…,S` _n }; in the present example, the ith abstract topological slice S' in the sequence S _i ,(i∈[1,n]) Calculating the maximum flow C from the virtual input node s to the virtual output node t in the abstract topological slice by using a Boykov-Kolmogorov algorithm _i And a maximum flow path GF _i (ii) a Traversing the sequence S' to obtain a capacity sequence C = { C } corresponding to the sequence S ₁ ,C ₂ ,…,C _n And maximum stream path sequence CF = { GF = } ₁ ,GF ₂ ,…,GF _n In this example, the service model calculates the network capacity C of the network using a formula _network 。

C _network ＝min(C)。

In another specific embodiment, referring to fig. 7, the method for dynamically estimating the capacity of the satellite communication network based on the topology abstraction is also applicable to the scenario of "ground station connected to core network" in the satellite network system. Fig. 7 shows a typical terrestrial gateway station network architecture, in which there are 20 network nodes, including 5 service access nodes (i.e. gateway station nodes), 3 secondary optical cross-connect nodes, 2 primary optical cross-connect nodes, and 1 service aggregation node; the service flow enters the network from the service access point, passes through the primary optical traffic and the secondary optical traffic, and is finally sent to the superior network at the service convergence point.

In this embodiment, a network simulation model is first established based on the terrestrial service access network architecture. The simulation comprises 5 service access nodes, 3 secondary optical cross nodes, 2 primary optical cross nodes and 1 service convergence node, a network node set is marked as V, wherein the access node set is marked as V ₁ ＝{v ₁ ,v ₂ ,…,v ₅ V in the set of secondary optical cross nodes ₂ ＝{v ₆ ,v ₇ ,v ₈ }; the first-level optical cross node set is marked as V ₃ ＝{v ₉ ,v ₁₀ The service convergence node set is marked as V ₄ ＝{v ₁₁ And the connection between the network nodes is bidirectional, and the link set in the network is marked as

E _jk Representing the actual presence of slaves v in the network _j Node to v _k One directed edge of the number node; in this embodiment, an adjacency matrix manner is used to describe the adjacency relationship of network nodes, and an adjacency matrix a obtained by network operation simulation is:

wherein, A represents the topological connection relation G = (V, E) between nodes in the ground service access network; when network exists, node v _j To node v _k Directed link ofTime e _jk Is equal to the physical distance of the link; when there is no node v _j To node v _k Directed link time of e _jk ＝0。

Furthermore, the process converts the dynamically changing network topology into a relatively static topology sequence, and the adjacency list does not change after the step because the ground network topology structure is relatively fixed; only one topological slice is contained in the sequence of topological slices S = { a }.

Referring to fig. 8, the slices are topologically abstracted according to the abstraction rules and the business model. In this embodiment, a virtual input node and a virtual output node are added to a slice adjacency matrix in a topology slice sequence S, the virtual input node is connected with an access satellite node according to an attribute of a network node, and the virtual output node is connected with a gateway station, so as to obtain an abstract topology adjacency matrix set. Service access node V in service model ₁ For the input of the network, a set of service sink nodes V ₄ Is the output of the network; abstracting all users in the network into a virtual input node s, a node s and a set V ₁ All the elements in the network are connected, and the link bandwidth is set to be 0.1GB according to a preset access bandwidth set; the connection relation of nodes in the topology is reserved, and the link bandwidths between a service access node and a secondary optical junction, between a secondary optical junction and a primary optical junction, between a primary optical junction and a service rendezvous point are respectively 1GB, 10GB and 100GB; will be set V ₄ All elements in the virtual output node are connected with a virtual output node t, and the link bandwidth is set to be infinite; the abstracted network link set is represented by a set E ', and the topology obtained by abstraction is represented by a graph G' = (V ', E'). Traversing the topology slice sequence S, abstracting the obtained topology to generate an abstract topology slice sequence S' = { S ″) ₁ Is then S ₁ Comprises the following steps:

wherein, S ″ ₁ Abstract topology G' representing the 1 st slice ₁ ＝(V` ₁ ,E` ₁ ),i∈[1,n]N is the number of abstract topological slices; when the network exists by the node v ″) _j To node v ″ _k Directed link time of b _jk Represents the bandwidth of the link; when there is no node v ″) _j To node v ″ _k Directed link time of b _jk ＝0。

Still further, traverse the abstract topology slice sequence S' = { S ″) ₁ }; in the present example, the abstract topological slice S' in the sequence S ₁ Calculating the maximum flow C from the virtual input node s to the virtual output node t in the abstract topological slice by using a Boykov-Kolmogorov algorithm ₁ And a maximum flow path GF ₁ (ii) a Traversing the sequence S' to obtain a capacity sequence C = { C) corresponding to the sequence S = { (C) } ₁ And maximum stream path sequence GF = { GF = } ₁ In this example, the service model calculates the network capacity C of the network using a formula _network 。

C _network ＝min(C)＝0.5GB

When the network flow is maximum, the flow occupation condition of each link is GF ₁ ：

As can be seen from the foregoing, according to the network capacity determining method, device, electronic device and storage medium provided by the present application, a communication network simulation model is established according to a satellite communication network architecture to determine a satellite communication network topology connection relationship; wherein, the topology connection relationship of the satellite communication network comprises: a adjacency matrix sequence, the adjacency matrix sequence comprising: a plurality of adjacency matrices; traversing the adjacent matrix sequence according to a preset sequence, and segmenting all the adjacent matrices to determine a topological slice sequence; traversing the topology slice sequence according to an abstract rule and a service model, and abstracting the topology slice sequence to determine an abstract topology slice sequence; and determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence, and determining the network capacity according to the capacity sequence and the maximum flow path sequence. Dividing the high-dynamic satellite network operation process into 'topological slices' to be analyzed by using a slice dividing method; converting a multi-input multi-output complex satellite network slice into an abstract slice by using a topology abstraction technology, so that the abstract slice becomes a simple abstract topology with single input and single output; the network capacity of the abstract slice is calculated and evaluated by using a network flow algorithm, so that the problems of difficult simulation setting, long simulation time, dependence on a service model and the like in the conventional network capacity simulation test method are solved. The method can reduce the simulation complexity of the network capacity, reduce the consumption of computing resources and provide flexible adaptation capability to different service models.

It should be noted that the method of the embodiment of the present application may be executed by a single device, such as a computer or a server. The method of the embodiment can also be applied to a distributed scene and completed by the mutual cooperation of a plurality of devices. In such a distributed scenario, one of the multiple devices may only perform one or more steps of the method of the embodiment, and the multiple devices interact with each other to complete the method.

It should be noted that the description describes some embodiments of the present application. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the described embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

Based on the same inventive concept, corresponding to the method of any embodiment, the application also provides a network capacity determining device.

Referring to fig. 9, the network capacity determination apparatus includes: the device comprises a first determining module, a cutting module, an abstract module and a second determining module; wherein, the first and the second end of the pipe are connected with each other,

a second determination module configured to determine a capacity sequence and a maximum flow path sequence from the abstract topology slice sequence and determine a network capacity from the capacity sequence and the maximum flow path sequence.

operating the communication network simulation model by taking a satellite orbit period as simulation duration to determine the topological connection relation of the satellite communication network; wherein the satellite communication network topology connection relationship comprises: a sequence of adjacency matrices; the adjacency matrix sequence comprises: a plurality of adjacency matrices;

wherein any one adjacency matrix is represented as

Wherein A is _i Representing an adjacency matrix of a satellite and a ground station in the satellite network at the moment i, m is the number of nodes in a network set V, T represents a simulation period, e _jk Representing a node v _j To node v _k The physical distance of the directed link.

In one possible implementation, the slicing module is further configured to:

determining whether the feed link of the next adjacent matrix is changed in on-off state;

the abstraction module is further configured to:

for each topological slice and the corresponding adjacency matrix,

In one possible implementation, the second determining module is further configured to:

C _network ＝min(C)

Wherein, C _network Representing network capacity.

In one possible implementation manner, the apparatus further includes: an application module;

the application module is configured to:

In one possible implementation manner, the first determining module may include: the device comprises a network parameter setting unit, a software simulation unit and a connection sequence generation unit;

the system comprises a network parameter setting unit, a simulation unit and a simulation unit, wherein the network parameter setting unit is used for determining the node setting in a satellite communication network to be evaluated within simulation time and the connection relation among all nodes;

the software simulation unit is used for calculating the topology change condition of the satellite communication network to be evaluated in the simulation duration in a software application mode based on physical computer hardware;

and the connection sequence generation unit is used for outputting the simulation result of the software simulation unit into a series of network connection relation sequences according to the normalized format.

In one possible implementation, the slicing module may include: a sequence analysis unit and a slice sequence generation unit;

the sequence analysis unit is used for dividing the network connection relation sequence according to the slice triggering rule;

and the slicing sequence generating unit is used for outputting the result of the sequence analyzing unit into a series of network slicing sequences according to the normalized format.

In one possible implementation manner, the abstraction module may include: the device comprises a virtualization unit and an abstract topological sequence generation unit;

the virtualization unit is used for setting a virtual input node and an input link, setting a virtual output node and an output link, and constructing an abstract topology;

and the abstract topology sequence generation unit is used for outputting the result of the virtualization unit into a series of abstract topology sequences according to the normalized format.

In one possible implementation manner, the second determining module may include: a capacity calculation unit and a capacity statistic unit;

the system comprises a capacity calculation unit, a traffic matrix calculation unit and a traffic matrix calculation unit, wherein the capacity calculation unit is used for calculating the network capacity in an abstract topological sequence according to a required capacity calculation mode and recording the capacity value and the traffic matrix of each element in the sequence;

and the capacity counting unit is used for counting the capacity value corresponding to the abstract topology sequence according to the required capacity counting mode and determining the capacity value as the network capacity.

In one possible implementation, the capacity calculation includes any of the following: the method comprises a Push-relabel-based maximum flow algorithm, a Ford-Fulkerson algorithm and a Boykov-Kolmogorov algorithm.

In a possible implementation manner, optionally, the capacity statistics manner includes any one of the following: maximum, minimum, median, mean, variance.

In one possible implementation, the application module may include: the device comprises a communication unit, a storage unit, a timing unit and a cache unit;

the communication unit is used for communication between the control center and the network nodes, converting the evaluation result of the network capacity into a routing table item required by the network nodes, and sending the routing table item to each network node by the control center to complete the configuration of the node routing table item;

the storage unit is used for locally storing the routing table entry in the network node, and when the satellite node receives the routing table entry sent by the control center through the communication unit, the storage unit is used for finishing the storage of the table entry;

the timing unit is used for calling the routing table items in the storage unit at the appointed time, and the nodes use the corresponding routing table items in the storage unit to perform table look-up and forwarding on the data stream;

and the cache unit is used for caching the data in the switching process of the routing table. In the process of switching the routing table, the data packets received by each node enter the node cache, and after the switching of the routing table is completed, the data packets are sent to the next hop node along the new routing table.

For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, the functionality of the various modules may be implemented in the same one or more software and/or hardware implementations as the present application.

The apparatus in the embodiment is configured to implement the corresponding network capacity determining method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.

Based on the same inventive concept, corresponding to the method of any embodiment, the application further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the network capacity determination method of any embodiment is implemented. Fig. 10 is a schematic diagram illustrating a more specific hardware structure of an electronic device according to this embodiment, where the electronic device may include: a processor 1010, a memory 1020, an input/output interface 1030, a communication interface 1040, and a bus 1050. Wherein the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 are communicatively coupled to each other within the device via a bus 1050.

The processor 1010 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits, and is configured to execute related programs to implement the technical solutions provided in the embodiments of the present disclosure.

The Memory 1020 may be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static Memory device, a dynamic Memory device, or the like. The memory 1020 may store an operating system and other application programs, and when the technical solution provided by the embodiments of the present specification is implemented by software or firmware, the relevant program codes are stored in the memory 1020 and called to be executed by the processor 1010.

The input/output interface 1030 is used for connecting an input/output module to input and output information. The input/output module may be configured as a component in a device (not shown) or may be external to the device to provide a corresponding function. The input devices may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output devices may include a display, a speaker, a vibrator, an indicator light, etc.

The communication interface 1040 is used for connecting a communication module (not shown in the drawings) to implement communication interaction between the present apparatus and other apparatuses. The communication module can realize communication in a wired mode (such as USB, network cable and the like) and also can realize communication in a wireless mode (such as mobile network, WIFI, bluetooth and the like).

The bus 1050 includes a path to transfer information between various components of the device, such as the processor 1010, memory 1020, input/output interface 1030, and communication interface 1040.

It should be noted that although the device only shows the processor 1010, the memory 1020, the input/output interface 1030, the communication interface 1040 and the bus 1050, in a specific implementation, the device may also include other components necessary for normal operation. Moreover, those skilled in the art will appreciate that the apparatus may also include only those components necessary to implement the embodiments of the present description, and not necessarily all of the components shown in the figures.

The electronic device of the embodiment is used to implement the corresponding network capacity determining method in any of the foregoing embodiments, and has the beneficial effects of the corresponding method embodiment, which are not described herein again.

Based on the same inventive concept, corresponding to the method of any of the embodiments, the present application also provides a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the method of determining network capacity according to any of the embodiments.

Computer-readable media of the present embodiments, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device.

The computer instructions stored in the storage medium of the embodiment are used to enable the computer to execute the network capacity determining method according to any of the above embodiments, and have the beneficial effects of the corresponding method embodiment, and are not described herein again.

Those of ordinary skill in the art will understand that: the discussion of any embodiment above is meant to be exemplary only, and is not intended to intimate that the scope of the disclosure, including the claims, is limited to these examples; within the context of the present application, features from the above embodiments or from different embodiments may also be combined, steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of brevity.

In addition, well-known power/ground connections to Integrated Circuit (IC) chips and other components may or may not be shown in the provided figures for simplicity of illustration and discussion, and so as not to obscure the embodiments of the application. Furthermore, devices may be shown in block diagram form in order to avoid obscuring embodiments of the application, and this also takes into account the fact that specifics with respect to implementation of such block diagram devices are highly dependent upon the platform within which the embodiments of the application are to be implemented (i.e., specifics should be well within purview of one skilled in the art). Where specific details (e.g., circuits) are set forth in order to describe example embodiments of the application, it should be apparent to one skilled in the art that the embodiments of the application can be practiced without, or with variation of, these specific details. Accordingly, the description is to be regarded as illustrative instead of restrictive.

While the present application has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those of ordinary skill in the art in light of the foregoing description. For example, other memory architectures, such as Dynamic RAM (DRAM), may use the discussed embodiments.

The present embodiments are intended to embrace all such alternatives, modifications and variances which fall within the broad scope of the appended claims. Therefore, any omissions, modifications, substitutions, improvements, and the like that may be made without departing from the spirit and principles of the embodiments of the present application are intended to be included within the scope of the present application.

Claims

1. A method for determining network capacity, comprising:

establishing a communication network simulation model according to a satellite communication network architecture to determine a satellite communication network topology connection relation; wherein, the topology connection relationship of the satellite communication network comprises: an adjacency matrix sequence, the adjacency matrix sequence comprising: a plurality of adjacency matrices;

2. The method of claim 1, wherein the establishing a communication network simulation model according to a satellite communication network architecture to determine a satellite communication network topology connection relationship comprises:

wherein any one adjacency matrix is represented as

3. The method of claim 1, wherein traversing the sequence of adjacency matrices according to a preset order and slicing all of the adjacency matrices to determine a sequence of topological slices comprises:

4. The method of claim 1, wherein the sequence of topological slices comprises: a plurality of topological slices; the adjacency matrix includes: accessing a satellite node and a gateway station node;

for each topological slice and the corresponding adjacency matrix,

5. The method of claim 4, wherein determining a capacity sequence and a maximum flow path sequence from the sequence of abstract topology slices and determining a network capacity from the capacity sequence and the maximum flow path sequence comprises:

determining a maximum flow and a maximum flow path from the virtual input node to the virtual output node in each abstract topology slice by using a Boykov-Kolmogorov algorithm, determining the capacity sequence C according to the maximum flow of each abstract topology slice, and determining the maximum flow path sequence GF according to the maximum flow path of each abstract topology slice;

C _network ＝min(C)

Wherein, C _network Representing the network capacity.

6. The method of claim 1, wherein after determining a capacity sequence and a maximum flow path sequence according to the abstract topology slice sequence and determining a network capacity according to the capacity sequence and the maximum flow path sequence, further comprising:

7. A network capacity determination apparatus, comprising:

an abstraction module configured to traverse the topological slice sequence according to an abstraction rule and a business model, and abstract the topological slice sequence to determine an abstract topological slice sequence;

8. The apparatus of claim 7, wherein the first determining module is further configured to:

wherein any one adjacency matrix is represented as

9. An electronic device 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 to 6 when executing the program.

10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to implement the method of any one of claims 1 to 6.