CN109039885B - Data transmission path selection method and device - Google Patents
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Abstract
A data transmission path selection method and device comprises the following steps: establishing a neural network model for selecting a recommended data transmission line; receiving data transmission request information sent by communication equipment, determining a plurality of data transmission lines including an initial routing node and a destination routing node, and determining a preset number of recommended data transmission lines from the plurality of data transmission lines through a neural network model; and sending the preset number of recommended data transmission lines to the communication equipment, and switching the current data transmission line into one recommended data transmission line selected from the preset number of recommended data transmission lines by using the communication equipment. Therefore, the method and the device for selecting the data transmission paths can intelligently screen out a plurality of data transmission paths and recommend the data transmission paths to the communication equipment for selection, and are beneficial to improving the data transmission quality and further improving the data transmission efficiency.
Description
Technical Field
The present invention relates to the field of data communication technologies, and in particular, to a method and an apparatus for selecting a data transmission path.
Background
With the development of networks, more and more users use mobile terminals such as mobile phones or ipads to surf the internet, and the selection of a data transmission path has an extremely important influence on the performance of the network. The existing data transmission path selection method is to select a data transmission path according to traffic distribution, and usually, one data transmission path with the shortest transmission distance is selected as an optimal data transmission path from a plurality of data transmission paths between a network source node and a network destination routing node. However, in practice, it is found that network congestion is often caused by that a large number of users all use the data transmission path with the shortest transmission distance for transmission, so that data transmission quality is affected, data transmission efficiency is low, and time delay is large.
Disclosure of Invention
In view of the above problems, the present invention provides a method and an apparatus for selecting a data transmission path, which can intelligently screen out a plurality of data transmission paths and recommend the data transmission paths to a communication device for selection, thereby facilitating to improve data transmission quality and further improving data transmission efficiency.
In order to achieve the purpose, the invention adopts the following technical scheme:
the first aspect of the present invention discloses a data transmission path selection method, which includes:
establishing a neural network model for selecting a recommended data transmission line;
receiving data transmission request information sent by communication equipment, wherein the data transmission request information comprises an initial routing node for sending data information and a destination routing node for receiving the data information;
determining a plurality of data transmission lines including the start routing node and the destination routing node, and determining a preset number of recommended data transmission lines having good data communication performance from the plurality of data transmission lines through the neural network model;
and transmitting a line plan including the preset number of recommended data transmission lines to the communication device, and switching a current data transmission line to one recommended data transmission line selected from the preset number of recommended data transmission lines using the communication device.
As an alternative implementation, in the first aspect of the present invention, the method further includes:
acquiring line information of the data transmission line switched by the communication equipment, and judging whether the data transmission line switched by the communication equipment is smooth or not by taking the line information as a basis;
and if the data transmission line switched by the communication equipment is judged to be not smooth, determining a plurality of data transmission lines including the starting routing node and the destination routing node, and determining a preset number of recommended data transmission lines from the plurality of data transmission lines through the neural network model.
As an optional implementation manner, in the first aspect of the present invention, the obtaining the line information of the data transmission line after the switching of the communication device, and determining whether the data transmission line after the switching of the communication device is clear based on the line information includes:
acquiring the occupation proportion of the transmission bandwidth of the data transmission line switched by the communication equipment;
judging whether the occupation proportion of the transmission bandwidth exceeds a preset proportion threshold value or not;
and if the occupation proportion of the transmission bandwidth does not exceed the preset proportion threshold value, determining that the data transmission line is not smooth after the communication equipment is switched.
As an optional implementation manner, in the first aspect of the present invention, the acquiring line information of the data transmission line after the switching of the communication device, and determining whether the data transmission line after the switching of the communication device is clear based on the line information includes:
sending a test data packet through the data transmission line switched by the communication equipment, and determining the consumed time for receiving a response data packet responding to the test data packet;
judging whether the consumed time length is greater than a preset time length threshold value or not;
and if the consumed time length is judged to be greater than the preset time length threshold value, determining that the data transmission line is not smooth after the communication equipment is switched.
As an alternative implementation, in the first aspect of the present invention, the establishing a neural network model for selecting a recommended data transmission line includes:
acquiring data information of a communication network where the communication equipment is located, wherein the data information comprises all communication node data of the communication network and a route structure of the communication network;
constructing the neural network model corresponding to the communication network based on the data information; wherein a topology structure of the neural network model corresponds to a route structure of the communication network, and each neuron of the topology structure corresponds to one communication node data of the communication network.
A second aspect of the present invention discloses a data transmission path selecting apparatus, including:
the model establishing module is used for establishing a neural network model for selecting the recommended data transmission line;
the receiving module is used for receiving data transmission request information sent by communication equipment, wherein the data transmission request information comprises an initial routing node for sending data information and a destination routing node for receiving the data information by the communication equipment;
a line determination module for determining a plurality of data transmission lines including the start routing node and the destination routing node through the neural network model, and determining a preset number of recommended data transmission lines from the plurality of data transmission lines through the neural network model;
a transmitting module configured to transmit a line plan including the preset number of recommended data transmission lines to the communication device, and switch a current data transmission line to one recommended data transmission line selected from the preset number of recommended data transmission lines using the communication device.
As an optional implementation manner, in the second aspect of the present invention, the data transmission path selecting apparatus further includes:
the line unblocked judging module is used for acquiring the line information of the data transmission line switched by the communication equipment and judging whether the data transmission line switched by the communication equipment is unblocked or not by taking the line information as a basis;
the line determining module is further configured to determine a plurality of data transmission lines including the start routing node and the destination routing node when the line unblocked judging module judges that the data transmission lines switched by the communication device are unblocked, and determine a preset number of recommended data transmission lines from the plurality of data transmission lines through the neural network model.
As an optional implementation manner, in the second aspect of the present invention, the model building module includes:
the first submodule is used for acquiring data information of a communication network where the communication equipment is located, wherein the data information comprises all communication node data of the communication network and a route structure of the communication network;
the second submodule is used for constructing the neural network model corresponding to the communication network based on the data information; wherein a topology structure of the neural network model corresponds to a route structure of the communication network, and each neuron of the topology structure corresponds to one communication node data of the communication network.
In a third aspect, the present invention discloses a computer device, which includes a memory for storing a computer program and a processor for executing the computer program to make the computer device execute part or all of the data transmission path selection method disclosed in the first aspect.
A fourth aspect of the present invention discloses a computer-readable storage medium storing the computer program for use in the computer apparatus of the third aspect.
According to the data transmission path selection method and device provided by the invention, a neural network model for selecting a recommended data transmission line is established; when data transmission request information sent by communication equipment is received, a starting routing node for sending the data information and a destination routing node for receiving the data information, which are included in the data transmission request information, of the communication equipment, a plurality of data transmission lines can be determined according to the data transmission request information, and the plurality of data transmission lines can all realize data transmission from the starting routing node to the destination routing node; further, a preset number of recommended data transmission lines with good data communication performance are determined from the plurality of data transmission lines through a neural network model established previously, and finally, a line scheme including the preset number of recommended data transmission lines is sent to the communication equipment, and after the communication equipment receives the line scheme, the current data transmission line is switched to one recommended data transmission line selected from the preset number of recommended data transmission lines, so that the single data transmission path with the shortest transmission distance is effectively prevented from being adopted for transmission, the data transmission quality is favorably improved, and the data transmission efficiency is further improved.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are required to be used in the embodiments will be briefly described below, and it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope of the present invention.
Fig. 1 is a schematic flowchart of a data transmission path selection method according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a data transmission path selection method according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a data transmission path selection apparatus according to a third embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present invention without making any creative effort, shall fall within the protection scope of the present invention.
Aiming at the problems in the prior art, the invention provides a data transmission path selection method and a data transmission path selection device; firstly, establishing a neural network model for selecting a recommended data transmission line; when data transmission request information sent by communication equipment is received, a starting routing node for sending the data information and a destination routing node for receiving the data information, which are included in the data transmission request information, of the communication equipment, a plurality of data transmission lines can be determined according to the data transmission request information, and the plurality of data transmission lines can all realize data transmission from the starting routing node to the destination routing node; further, a preset number of recommended data transmission lines with good data communication performance are determined from the plurality of data transmission lines through a neural network model established previously, and finally, a line scheme including the preset number of recommended data transmission lines is sent to the communication equipment, and after the communication equipment receives the line scheme, the current data transmission line is switched to one recommended data transmission line selected from the preset number of recommended data transmission lines, so that the single data transmission path with the shortest transmission distance is effectively prevented from being adopted for transmission, the data transmission quality is favorably improved, and the data transmission efficiency is further improved. Also, the techniques may be implemented in associated software or hardware, as described below by way of example.
Example 1
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating a data transmission path selection method according to an embodiment of the present invention. As shown in fig. 1, the data transmission path selecting method may include the following steps:
s101, establishing a neural network model for selecting a recommended data transmission line.
In this embodiment, the neural network model may be a fluid neural network model. The fluid neural network is a neural network model with fluid characteristics, and assuming that each neuron of the fluid neural network is a container containing fluid, the dynamic characteristics of the ith container (neuron) in the fluid neural network comprising n containers (neurons) are shown as follows:
wherein, ω isijFor describing the current capacity of the cocurrent connection of vessels (neurons) I and j, IiRepresenting the input of a container (neuron), siFor describing the height of the liquid surface, uiFor describing the volume of the ith container (neuron). In a fluidic neural network, the probability of a single fluid molecule flowing through a channel is related to the flow rate of that channel.
S102, receiving data transmission request information sent by the communication equipment, wherein the data transmission request information comprises a starting routing node for sending the data information and a destination routing node for receiving the data information by the communication equipment.
In this embodiment, the communication device may be a smart phone (such as an Android phone, an iOS phone, and the like), a tablet computer, a palm computer, a smart watch, a Mobile Internet Device (MID), a PC, and the like, which is not limited in this embodiment.
The main body of the data transmission path selection method provided in this embodiment may be a communication server, a carrier base station server, a data transmission path selection device, and the like, which is not limited in this embodiment.
S103, determining a plurality of data transmission lines including the starting routing node and the destination routing node, and determining a preset number of recommended data transmission lines with good data communication performance from the plurality of data transmission lines through a neural network model.
In this embodiment, the preset number may be 1, 2, 3, etc., and this embodiment is not limited thereto.
In this embodiment, the initial routing node is a network node used when the communication device sends the original data, and is also referred to as a source node; accordingly, the destination routing node is a network node used by the receiving end to receive data, and is also called a destination node.
And S104, sending the line scheme comprising the preset number of recommended data transmission lines to the communication equipment, and switching the current data transmission line into one recommended data transmission line selected from the preset number of recommended data transmission lines by using the communication equipment.
As an alternative implementation, after the communication device receives the line plan, the communication device may output the line plan, and switch the current data transmission line to the data transmission line corresponding to the selection instruction according to the received selection instruction.
As another alternative, after the communication device receives the line plan, the current data transmission line may be automatically switched to the data transmission line matching the current data transmission line.
In the data transmission path selection method described in fig. 1, a neural network model for selecting a recommended data transmission line is first established; when data transmission request information sent by communication equipment is received, a starting routing node for sending the data information and a destination routing node for receiving the data information, which are included in the data transmission request information, of the communication equipment, a plurality of data transmission lines can be determined according to the data transmission request information, and the plurality of data transmission lines can all realize data transmission from the starting routing node to the destination routing node; further, a preset number of recommended data transmission lines with good data communication performance are determined from the plurality of data transmission lines through a neural network model established previously, and finally, a line plan including the preset number of recommended data transmission lines is sent to the communication device, and after the communication device receives the line plan, the current data transmission line is switched to one of the preset number of recommended data transmission lines. Therefore, by implementing the data transmission path selection method described in fig. 1, a plurality of data transmission paths can be intelligently screened out and recommended to the communication device for selection, so that the single data transmission path with the shortest transmission distance is effectively avoided from being adopted for transmission, the data transmission quality is favorably improved, and the data transmission efficiency is further improved.
Example 2
Referring to fig. 2, fig. 2 is a schematic flowchart illustrating a data transmission path selection method according to an embodiment of the present invention. As shown in fig. 2, the data transmission path selecting method may include the following steps:
s201, establishing a neural network model for selecting a recommended data transmission line.
S202, receiving data transmission request information sent by the communication equipment, wherein the data transmission request information comprises a starting routing node for sending the data information and a destination routing node for receiving the data information by the communication equipment.
S203, determining a plurality of data transmission lines including the starting routing node and the destination routing node, and determining a preset number of recommended data transmission lines with good data communication performance from the plurality of data transmission lines through a neural network model.
And S204, sending the line scheme comprising the preset number of recommended data transmission lines to the communication equipment, and switching the current data transmission line into one recommended data transmission line selected from the preset number of recommended data transmission lines by using the communication equipment.
And S205, acquiring the occupation ratio of the transmission bandwidth of the data transmission line after the communication equipment is switched.
S206, judging whether the occupation proportion of the transmission bandwidth exceeds a preset proportion threshold value, and if so, executing the step S203 to the step S206; if not, the flow ends.
In this embodiment, the preset ratio threshold may be 30%, 60%, 80%, etc., and this embodiment is not limited thereto.
In this embodiment, the above-mentioned steps S205 to S206 are executed to obtain the line information of the data transmission line after the switching of the communication device, and determine whether the data transmission line after the switching of the communication device is smooth based on the line information.
As an optional implementation manner, when it is determined that the occupation ratio of the initial transmission bandwidth does not exceed the preset ratio threshold, after the preset time period, the line information of the data transmission line after the switching of the communication device is obtained, and it is determined whether the data transmission line after the switching of the communication device is unblocked according to the line information, and if not, step S203 to step S206 are executed.
As an optional implementation manner, the method for determining whether the data transmission line switched by the communication device is unblocked according to the line information obtained from the data transmission line switched by the communication device may further include the following steps:
sending a test data packet through a data transmission line after the switching of the communication equipment, and determining the consumed time for receiving a response data packet responding to the test data packet;
judging whether the consumed time length is greater than a preset time length threshold value or not;
and if the consumed time length is judged to be greater than the preset time length threshold value, determining that the data transmission line is not smooth after the communication equipment is switched.
In the above embodiment, the preset time threshold may be 34ms, 46ms, etc., and this embodiment is not limited thereto.
As an alternative embodiment, establishing a neural network model for selecting a recommended data transmission line may include the steps of:
acquiring data information of a communication network where communication equipment is located, wherein the data information comprises all communication node data of the communication network and a route structure of the communication network;
constructing a neural network model corresponding to the communication network based on the data information; the topological structure of the neural network model corresponds to a route structure of the communication network, and each neuron of the topological structure corresponds to one communication node data of the communication network.
In this embodiment, the communication node data includes a plurality of communication nodes, a capacity of each communication node, a connection weight relationship between each communication node and its neighboring node, and the like.
In this embodiment, the neural network model may be a fluid neural network model. The fluid neural network is a neural network model with fluid characteristics, and assuming that each neuron of the fluid neural network is a container containing fluid, the dynamic characteristics of the ith container (neuron) in the fluid neural network comprising n containers (neurons) are shown as follows:
wherein, ω isijFor describing the current capacity of the cocurrent connection of vessels (neurons) I and j, IiRepresenting the input of a container (neuron), siFor describing the height of the liquid level in the vessel (neuron), uiFor describing the volume of the ith container (neuron). In a fluidic neural network, the probability of a single fluid molecule flowing through a channel is related to the flow rate of that channel.
In this embodiment, a decision condition is added to the neural network model to optimize the problem that the route selected by the single decision condition is single, where the decision condition may be packet loss rate, time delay, jitter, bandwidth, and the like, and this embodiment is not limited thereto. Further, with different decision conditions, a plurality of recommended data transmission lines having good data communication performance can be determined.
In this embodiment, when the determination condition is a bandwidth, the communication node data further includes a bandwidth occupation ratio of each communication node, and a process of determining a recommended data transmission line with good data communication performance by using a neural network model is as follows:
let s1，s2，…，snIs the height of the liquid surface in the vessel (neuron), u1，u2，…，unThe relationship is expressed as the following equation:
si＝g(ui)；
assume an initial state of s1(0)＝s2(0)＝…＝sn(0)＝s0，u1(0)＝u2(0)＝…＝un(0)＝u0And adding the input and the output with the same flow rate to the initial routing node and the destination routing node.
The neural network model is then iterated side by side until the expression of the neurons is unchanged, at which time the expression for each neuron is as follows:
wherein, when IiWhen the number is I, I is the initial routing node; when I isiWhen the destination routing node is-I, I is a destination routing node; when I isiWhen 0, i is the other node.
Starting to search the path with the maximum traffic (i.e. the minimum bandwidth occupation ratio) from the initial routing node s to the next node i1Then i is further provided with1Searching the path with the maximum flow to i2Repeating the above operations until the destination node d is searched, and searching the route s → i of the route1→i2→…→ik→ d is a recommended data transmission line with good data communication performance determined by the neural network model from a plurality of data transmission lines.
Therefore, by implementing the data transmission path selection method described in fig. 2, a plurality of data transmission paths can be intelligently screened out and recommended to the communication device for selection, so that the single data transmission path with the shortest transmission distance is effectively avoided from being adopted for transmission, the data transmission quality is favorably improved, and the data transmission efficiency is further improved.
Example 3
Referring to fig. 3, fig. 3 is a schematic structural diagram of a data transmission path selection device according to an embodiment of the present invention. As shown in fig. 3, the data transmission path selecting apparatus includes:
a model building module 301, configured to build a neural network model for selecting a recommended data transmission line.
A receiving module 302, configured to receive data transmission request information sent by a communication device, where the data transmission request information includes a start routing node for the communication device to send data information and a destination routing node for receiving data information.
A line determining module 303, configured to determine, through the neural network model, a plurality of data transmission lines including the start routing node and the destination routing node, and determine, through the neural network model, a preset number of recommended data transmission lines from the plurality of data transmission lines.
A sending module 304, configured to send a line plan including a preset number of recommended data transmission lines to the communication device, and switch, using the communication device, a current data transmission line to one recommended data transmission line selected from the preset number of recommended data transmission lines.
As an optional implementation manner, the data transmission path selecting apparatus further includes:
the line smoothness judging module 305 is configured to obtain line information of the data transmission line after the switching of the communication device, and judge whether the data transmission line after the switching of the communication device is smooth according to the line information.
In this embodiment, after the sending module 304 sends the line plan including the preset number of recommended data transmission lines to the communication device, the trigger line smoothness determining module 305 may further obtain the line information of the data transmission line after the switching of the communication device.
The line determining module 303 is further configured to determine a plurality of data transmission lines including the start routing node and the destination routing node when the on-line smoothness determining module 305 determines that the data transmission lines switched by the communication device are not smooth, and determine a preset number of recommended data transmission lines from the plurality of data transmission lines through a neural network model.
As an alternative implementation, the model building module 301 includes:
the first sub-module 3011 is configured to obtain data information of a communication network where the communication device is located, where the data information includes data of all communication nodes of the communication network and a route structure of the communication network.
The second sub-module 3012, configured to construct a neural network model corresponding to the communication network based on the data information; the topological structure of the neural network model corresponds to a route structure of the communication network, and each neuron of the topological structure corresponds to one communication node data of the communication network.
Therefore, by implementing the data transmission path selection device described in fig. 3, a plurality of data transmission paths can be intelligently screened out and recommended to the communication device for selection, so that the single data transmission path with the shortest transmission distance is effectively avoided from being adopted for transmission, the data transmission quality is favorably improved, and the data transmission efficiency is further improved.
In addition, the invention also provides computer equipment. The computer device comprises a memory and a processor, wherein the memory can be used for storing a computer program, and the processor can make the computer device execute the functions of the method or each module in the data transmission path selection device by operating the computer program.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function (such as a sound playing function, an image playing function, etc.), and the like; the storage data area may store data (such as audio data, a phonebook, etc.) created according to the use of the mobile terminal, and the like. Further, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
The embodiment also provides a computer storage medium for storing a computer program used in the computer device.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, each functional module or unit in each embodiment of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention or a part of the technical solution that contributes to the prior art in essence can be embodied in the form of a software product, which is stored in a storage medium and includes a plurality of instructions for executing all or part of the steps of the method according to the embodiments of the present invention by using a computer device (which may be a smart phone, a personal computer, a server, or a network device). And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (7)
1. A method for selecting a data transmission path, comprising:
establishing a neural network model for selecting a recommended data transmission line;
receiving data transmission request information sent by communication equipment, wherein the data transmission request information comprises an initial routing node for sending data information and a destination routing node for receiving the data information;
determining a plurality of data transmission lines including the start routing node and the destination routing node, and determining a preset number of recommended data transmission lines having good data communication performance from the plurality of data transmission lines through the neural network model;
transmitting a line plan including the preset number of recommended data transmission lines to the communication device, and switching a current data transmission line to one recommended data transmission line selected from the preset number of recommended data transmission lines using the communication device;
acquiring the occupation proportion of the transmission bandwidth of the data transmission line switched by the communication equipment;
judging whether the occupation proportion of the transmission bandwidth exceeds a preset proportion threshold value or not;
if the occupation ratio of the transmission bandwidth does not exceed the preset ratio threshold value, acquiring the line information of the data transmission line switched by the communication equipment after a preset time period, and judging whether the data transmission line switched by the communication equipment is smooth or not by taking the line information as a basis;
if the data transmission line switched by the communication equipment is judged to be not smooth, determining a plurality of data transmission lines including the starting routing node and the destination routing node, and determining a preset number of recommended data transmission lines with good data communication performance from the plurality of data transmission lines through the neural network model;
transmitting a line plan including the preset number of recommended data transmission lines to the communication device, and switching a current data transmission line to one recommended data transmission line selected from the preset number of recommended data transmission lines using the communication device; wherein,
the neural network model is a fluid neural network model, which comprisesnIndividual neuron ofiThe dynamic characteristics of individual neurons are expressed by the formula:
ω ij for representing connecting neuronsiAnd neuronsjThe flow-through capacity of the channel of (a);
I i an input for representing a neuron;
s i forIndicating the height of the liquid level;
u i is used for showing the firstiVolume of individual container neurons.
2. The method of claim 1, wherein the obtaining the line information of the data transmission line after the switching of the communication device, and determining whether the data transmission line after the switching of the communication device is clear based on the line information comprises:
sending a test data packet through the data transmission line switched by the communication equipment, and determining the consumed time for receiving a response data packet responding to the test data packet;
judging whether the consumed time length is greater than a preset time length threshold value or not;
and if the consumed time length is judged to be greater than the preset time length threshold value, determining that the data transmission line is not smooth after the communication equipment is switched.
3. The data transmission path selection method according to claim 1, wherein the establishing a neural network model for selecting a recommended data transmission line includes:
acquiring data information of a communication network where the communication equipment is located, wherein the data information comprises all communication node data of the communication network and a route structure of the communication network;
constructing the neural network model corresponding to the communication network based on the data information; wherein a topology structure of the neural network model corresponds to a route structure of the communication network, and each neuron of the topology structure corresponds to one communication node data of the communication network.
4. A data transmission path selection apparatus, comprising:
the model establishing module is used for establishing a neural network model for selecting the recommended data transmission line;
the receiving module is used for receiving data transmission request information sent by communication equipment, wherein the data transmission request information comprises an initial routing node for sending data information and a destination routing node for receiving the data information by the communication equipment;
a line determination module for determining a plurality of data transmission lines including the start routing node and the destination routing node, and determining a preset number of recommended data transmission lines having good data communication performance from the plurality of data transmission lines through the neural network model;
a transmission module configured to transmit a line plan including the preset number of recommended data transmission lines to the communication device, and switch a current data transmission line to one recommended data transmission line selected from the preset number of recommended data transmission lines using the communication device;
the line unblocked judging module is used for acquiring the occupation proportion of the transmission bandwidth of the data transmission line after the communication equipment is switched; judging whether the occupation proportion of the transmission bandwidth exceeds a preset proportion threshold value or not; if the occupation ratio of the transmission bandwidth does not exceed the preset ratio threshold value, acquiring the line information of the data transmission line switched by the communication equipment after a preset time period, and judging whether the data transmission line switched by the communication equipment is smooth or not by taking the line information as a basis;
the line determining module is further configured to determine a plurality of data transmission lines including the initial routing node and the destination routing node when the line unblocked judging module judges that the data transmission lines switched by the communication device are unblocked, and determine a preset number of recommended data transmission lines from the plurality of data transmission lines through the neural network model;
the sending module is further configured to send a line plan including the preset number of recommended data transmission lines to the communication device, and switch a current data transmission line to one recommended data transmission line selected from the preset number of recommended data transmission lines using the communication device; wherein,
the neural network model is a fluid neural network model, which comprisesnIndividual neuron ofiThe dynamic characteristics of individual neurons are expressed by the formula:
ω ij for representing connecting neuronsiAnd neuronsjThe flow-through capacity of the channel of (a);
I i an input for representing a neuron;
s i for indicating the height of the liquid level;
u i is used for showing the firstiVolume of individual container neurons.
5. The data transmission path selection device according to claim 4, wherein the model building module includes:
the first submodule is used for acquiring data information of a communication network where the communication equipment is located, wherein the data information comprises all communication node data of the communication network and a route structure of the communication network;
the second submodule is used for constructing the neural network model corresponding to the communication network by taking the data information as a basis; wherein a topology structure of the neural network model corresponds to a route structure of the communication network, and each neuron of the topology structure corresponds to one communication node data of the communication network.
6. A computer device comprising a memory for storing a computer program and a processor for executing the computer program to cause the computer device to perform the data transmission path selection method according to any one of claims 1 to 3.
7. A computer-readable storage medium, characterized in that it stores the computer program used in the computer device of claim 6.
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