CN110779524A - Path planning method, device, equipment and storage medium - Google Patents
Path planning method, device, equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a path planning method, a path planning device, a path planning equipment and a storage medium. The method comprises the following steps: determining a source node and a target node in a target network; calculating dynamic recursive values of a plurality of paths from a source node to a target node according to network parameters of the target network, wherein the network parameters at least comprise the bandwidth of the nodes in the target network; and determining the optimal path from the source node to the target node in the plurality of paths according to the dynamic recursion values. The path planning method, the device, the equipment and the storage medium of the embodiment of the invention take bandwidth factors into consideration during path planning, and can avoid network congestion and network data transmission performance reduction.
Description
Technical Field
The present invention relates to the field of internet technologies, and in particular, to a path planning method, apparatus, device, and storage medium.
Background
Path planning refers to a strategy for constructing a path, where a path refers to a sequence of points or curves connecting a start position and an end position.
Path planning has wide application in many fields. The applications in the high and new technology field are as follows: autonomous collision-free action of the robot; obstacle avoidance and sudden prevention flight of the unmanned aerial vehicle; the cruise missile avoids radar search, prevents missile attack, completes a penetration and explosion task and the like. The application in the daily life field is as follows: global Positioning System (GPS) navigation, Geographic Information System (GIS) based road planning, urban road network planning navigation, and the like. The application in the field of decision management is as follows: vehicle issues in logistics and similar resource management resource allocation issues. Routing problems in the field of communications technology, etc. The planning problem of any topologically dotted line network can be basically solved by adopting a path planning method.
At present, Dijkstra (Dijkstra) algorithm is mainly adopted for path planning aiming at routing problem, but the Dijkstra algorithm only depends on the distance of nodes in the network, so that the planned path may cause network congestion and reduce network data transmission performance.
Disclosure of Invention
Embodiments of the present invention provide a path planning method, apparatus, device, and storage medium, which can avoid network congestion and network data transmission performance degradation.
In one aspect, an embodiment of the present invention provides a path planning method, where the method includes:
determining a source node and a target node in a target network;
calculating dynamic recursive values of a plurality of paths from a source node to a target node according to network parameters of the target network, wherein the network parameters at least comprise the bandwidth of the nodes in the target network;
and determining the optimal path from the source node to the target node in the plurality of paths according to the dynamic recursion values.
In one embodiment of the present invention, calculating dynamic recursive values of a plurality of paths from a source node to a target node according to a network parameter of a target network includes:
establishing a two-dimensional array from a source node to a target node, wherein the rows and the columns of the two-dimensional array are both node identification information, and the element values of the two-dimensional array are values calculated according to network parameters of a target network;
and aiming at a target path in a plurality of paths from the source node to the target node, taking the sum of element values of the two-dimensional array corresponding to the target path as a dynamic recursive value of the target path, wherein the target path is a path selected from the plurality of paths from the source node to the target node.
In one embodiment of the present invention, the network parameters further include one or more of the following:
round trip delay of nodes, bandwidth cost of nodes, and distance between nodes.
In one embodiment of the present invention, determining an optimal path from a source node to a target node among a plurality of paths according to a dynamic recurrence value includes:
and in the plurality of paths, taking the path corresponding to the minimum dynamic recursion value in the dynamic recursion values as the optimal path from the source node to the target node.
In an embodiment of the present invention, taking a path corresponding to a minimum dynamic recurrence value in the dynamic recurrence values as an optimal path from a source node to a target node, includes:
determining a path corresponding to the minimum dynamic recursive value from the plurality of paths according to the dynamic recursive value;
calculating the current bandwidth utilization rate of each node between a source node and a target node in a path corresponding to the minimum dynamic recursive value;
and if the bandwidth utilization rate is not greater than the preset bandwidth utilization rate, taking the path corresponding to the minimum dynamic recursion value as the optimal path from the source node to the target node.
In one embodiment of the invention, the target network is a Content Delivery Network (CDN).
In another aspect, an embodiment of the present invention provides a path planning apparatus, where the apparatus includes:
the determining module is used for determining a source node and a target node in a target network;
the calculation module is used for calculating dynamic recursive values of a plurality of paths from a source node to a target node according to network parameters of the target network, wherein the network parameters at least comprise the bandwidth of the nodes in the target network;
and the planning module is used for determining the optimal path from the source node to the target node in the plurality of paths according to the dynamic recursive value.
In an embodiment of the present invention, the calculation module is specifically configured to:
establishing a two-dimensional array from a source node to a target node, wherein the rows and the columns of the two-dimensional array are both node identification information, and the element values of the two-dimensional array are values calculated according to network parameters of a target network;
and aiming at a target path in a plurality of paths from the source node to the target node, taking the sum of element values of the two-dimensional array corresponding to the target path as a dynamic recursive value of the target path, wherein the target path is a path selected from the plurality of paths from the source node to the target node.
In one embodiment of the present invention, the network parameters further include one or more of the following:
round trip delay of nodes, bandwidth cost of nodes, and distance between nodes.
In an embodiment of the present invention, the planning module is specifically configured to:
and in the plurality of paths, taking the path corresponding to the minimum dynamic recursion value in the dynamic recursion values as the optimal path from the source node to the target node.
In an embodiment of the present invention, the planning module is specifically configured to:
determining a path corresponding to the minimum dynamic recursive value from the plurality of paths according to the dynamic recursive value;
calculating the current bandwidth utilization rate of each node between a source node and a target node in a path corresponding to the minimum dynamic recursive value;
and if the bandwidth utilization rate is not greater than the preset bandwidth utilization rate, taking the path corresponding to the minimum dynamic recursion value as the optimal path from the source node to the target node.
In one embodiment of the invention, the target network is a content delivery network CDN.
In another aspect, an embodiment of the present invention provides a path planning apparatus, where the apparatus includes: a memory and a processor;
the memory is used for storing executable program codes;
the processor is used for reading the executable program codes stored in the memory to execute the path planning method provided by the embodiment of the invention.
In yet another aspect, an embodiment of the present invention provides a computer-readable storage medium having computer program instructions stored thereon; the computer program instructions, when executed by the processor, implement the path planning method provided by the embodiments of the present invention.
The path planning method, the device, the equipment and the storage medium of the embodiment of the invention take bandwidth factors into consideration during path planning, and can avoid network congestion and network data transmission performance reduction.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart illustrating a path planning method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a target network provided by an embodiment of the invention;
fig. 3 is a schematic structural diagram of a path planning apparatus according to an embodiment of the present invention;
fig. 4 is a block diagram illustrating an exemplary hardware architecture of a computing device capable of implementing a path planning method and apparatus according to embodiments of the present invention.
Detailed Description
Features and exemplary embodiments of various aspects of the present invention will be described in detail below, and in order to make objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the present invention.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
At present, a Dijkstra algorithm is mainly adopted for path planning aiming at a routing problem, but the Dijkstra algorithm is only based on the distance of nodes in a network, so that the planned path may cause network congestion and the network data transmission performance is reduced. Based on this, embodiments of the present invention provide a path planning method, apparatus, device, and storage medium, so as to avoid network congestion and network data transmission performance degradation. First, a path planning method provided by the embodiment of the present invention is described below.
As shown in fig. 1, fig. 1 is a schematic flow chart of a path planning method provided by an embodiment of the present invention. The path planning may include:
s101: a source node and a target node in a target network are determined.
S102: and calculating dynamic recursive values of a plurality of paths from the source node to the target node according to the network parameters of the target network.
Wherein the network parameters comprise at least the bandwidth of the nodes in the target network.
S103: and determining the optimal path from the source node to the target node in the plurality of paths according to the dynamic recursion values.
Illustratively, assume that the target network is as shown in FIG. 2. Fig. 2 is a schematic diagram of a target network provided by an embodiment of the present invention. The target network includes 7 nodes, node 1 to node 7 respectively. The node 6 stores data of the source station 1, and the node 7 stores data of the source station 2. The nodes 6 and 7 have only a function of providing data.
In an embodiment of the present invention, the source node may be a node that receives a user access request, and the target node may be a node that stores user access data. Therefore, when determining a source node in the target network, the node receiving the user access request can be used as the source node; when determining a target node in the target network, the node storing the user access data may be used as the target node.
Assuming that a user wants to access data of the source station 2, the node 7 storing the data of the source station 2 is used as a target node; and if the node receiving the user request is the node 1, taking the node 1 as a source node.
There are 10 paths from node 1 to node 7. The 10 paths from node 1 to node 7 are:
path a: node 1- > node 7.
And a path B: node 1- > node 4- > node 7.
And a path C: node 1- > node 2- > node 5- > node 7.
Route D: node 1- > node 4- > node 5- > node 7.
Path E: node 1- > node 2- > node 3- > node 5- > node 7.
Path F: node 1- > node 2- > node 4- > node 5- > node 7.
A path G: node 1- > node 2- > node 3- > node 4- > node 5- > node 7.
Path H: node 1- > node 2- > node 3- > node 5- > node 4- > node 7.
Path I: node 1- > node 2- > node 4- > node 3- > node 5- > node 7.
Path J: node 1- > node 2- > node 5- > node 3- > node 4- > node 7.
The dynamic recurrence value of each of the 10 paths is calculated based on network parameters including at least the bandwidth of the target network node. And then determining the optimal path from the node 1 to the node 7 from the 10 paths according to the dynamic recursive value of each path.
In an embodiment of the present invention, when the dynamic recursive value of the path is calculated according to the bandwidth of the node, the calculation may be performed according to the total bandwidth of the node, and may also be performed according to the remaining bandwidth of the node.
For example, for path B: node 1- > node 4- > node 7, the remaining bandwidth of node 4 is 10 megabits (M), and the remaining bandwidth of node 7 is 25M. Since the residual bandwidth of node 4 is smaller than that of node 7, and data transmission is limited by the node corresponding to the minimum residual bandwidth in the path, 10M can be directly used as the dynamic recursive value of path B.
In an embodiment of the present invention, when determining a source node and a target node in a target network, any node in the target network may be used as the source node, and nodes other than the source node may be used as the target nodes. And planning the path based on the whole situation of the target network.
In an embodiment of the present invention, calculating the dynamic recursive values of the plurality of paths from the source node to the target node according to the network parameter of the target network may include: and establishing a two-dimensional array from the source node to the target node, wherein the rows and the columns of the two-dimensional array are both node identification information, and the element values of the two-dimensional array are values obtained by calculation according to the network parameters of the target network. And aiming at a target path in a plurality of paths from the source node to the target node, taking the sum of element values of the two-dimensional array corresponding to the target path as a dynamic recursive value of the target path, wherein the target path is a path selected from the plurality of paths from the source node to the target node.
Illustratively, the target network shown in fig. 2 is also used as an example for explanation.
The two-dimensional array created based on the target network shown in fig. 2 is shown in table 1.
TABLE 1
The element value ij is obtained according to the network parameter of the target network shown in fig. 2, where i and j are both node numbers.
The description of the dynamic recursive value calculation is given by taking the calculation of the path F from the node 1 to the node 7 as an example.
The dynamic recursive value of the path from the source node to the target node X over Y hops is represented by DP (X, Y).
DP (7, 1) represents the dynamic recurrence value of said one path, i.e. the dynamic recurrence value of said path a; DP (7, 2) represents the dynamic recurrence value of said one path, i.e. the dynamic recurrence value of said path B; DP (7, 3) represents the dynamic recursion values of the two paths, i.e. the dynamic recursion values of the path C and the path D; DP (7, 4) represents the dynamic recursion values of said two paths, i.e. the dynamic recursion values of said path E and path F; DP (7, 5) represents the dynamic recursion values of the four paths, i.e., the dynamic recursion values of path G, path H, path I, and path J.
For the dynamic recursive value DP (7, 5) of the path G,
DP (7, 5) ═ DP (5, 4) + element value 57 ═ DP (4, 3) + element value 45+ element value 57 ═ DP (3, 2) + element value 34+ element value 45+ element value 57 ═ DP (2, 1) + element value 23+ element value 34+ element value 45+ element value 57 ═ DP (1, 0) + element value 12+ element value 23+ element value 34+ element value 45+ element value 57.
Since DP (1, 0) represents the dynamic recursive value of the path through 0 hops from the source node to the destination node 1, DP (1, 0) is 0. As can be seen from the dynamic recursive value DP (7, 5) derivation process for path G, the dynamic recursive value DP (7, 5) for path G is equal to the sum of the element value 12, element value 23, element value 34, element value 45, and element value 57 corresponding to path G.
Accordingly, dynamic recursive values for other paths may be computed.
In one embodiment of the present invention, the network parameters further include one or more of the following: round trip delay of nodes, bandwidth cost of nodes, and distance between nodes. Based on this, the element value ij may be equal to a _ rtt + b _ price + c _ bandwidth + d _ distance.
Wherein rtt is the round-trip delay from the node i to the node j; price is the bandwidth cost of node j; bandwidth is the bandwidth of node j; distance is the distance from node i to node j. The round trip delay from node i to node j is: the total time duration from the time when the node i sends the data to the time when the node i receives the acknowledgement of the node j, wherein the node j immediately sends the acknowledgement after receiving the data. Assuming node j uses a network provided by a telecommunications service provider where the price is 1 giga 1 ten thousand dollars, the bandwidth cost of node j is 10 dollars per million. The a, b, c and d are respectively: and weighted values corresponding to rtt, price, bandwidth and distance.
In one embodiment of the present invention, the bandwidth may be a remaining bandwidth (unused bandwidth) of the node j or may be a used bandwidth of the node j.
In an embodiment of the present invention, a, b, c, and d may be preset or obtained by training through a training algorithm (e.g., a neural network).
In an embodiment of the present invention, the element values ij may be normalized, and the dynamic recursive values of the path may be normalized.
It will be appreciated that the round trip delay rtt and the bandwidth are dynamically varied and the value of the path from the source node to the destination node is calculated recursively. Therefore, the value of the path from the source node to the target node is made a dynamic recursive value.
In an embodiment of the present invention, determining an optimal path from a source node to a target node in a plurality of paths according to a dynamic recurrence value may include: and in the plurality of paths, taking the path corresponding to the minimum dynamic recursion value in the dynamic recursion values as the optimal path from the source node to the target node.
For example, assuming that the dynamic recurrence value corresponding to the path E among the above 10 paths is the minimum, the path E is taken as the optimal path from the node 1 to the node E.
In an embodiment of the present invention, taking a path corresponding to a minimum dynamic recurrence value in the dynamic recurrence values as an optimal path from the source node to the target node, may include: determining a path corresponding to the minimum dynamic recursive value from the plurality of paths according to the dynamic recursive value; calculating the current bandwidth utilization rate of each node between a source node and a target node in a path corresponding to the minimum dynamic recursive value; and if the calculated bandwidth utilization rate is not greater than the preset bandwidth utilization rate, taking the path corresponding to the minimum dynamic recursion value as the optimal path from the source node to the target node. It can be understood that the larger the bandwidth utilization rate is, the less bandwidth resources are left for representing the node, the more unfavorable the data transmission is, and the more easily the blocking is.
For example, assuming that the dynamic recursion value corresponding to the path E of the 10 paths is determined to be the minimum according to the dynamic recursion value, the current bandwidth utilization rate of each node of the nodes 2, 3, and 5 among the nodes 1 to 7 in the path E is calculated.
And if the bandwidth utilization rates of the three nodes of the node 2, the node 3 and the node 5 are all smaller than the preset bandwidth utilization rate, taking the path E as the optimal path from the node 1 to the node 7.
If the bandwidth utilization rate of any one node among the three nodes 2, 3 and 5 is not less than the preset bandwidth utilization rate, determining a path corresponding to the minimum dynamic recursion value from the remaining 9 paths except the path E, and then calculating the current bandwidth utilization rate of each node between the node 1 and the node 7 in the determined path.
And if the current bandwidth utilization rate of each node between the node 1 and the node 7 in the determined path is less than the preset bandwidth utilization rate, taking the determined path as the optimal path from the node 1 to the node 7.
If the bandwidth utilization rate of any node in the nodes between the node 1 and the node 7 in the determined path is not less than the preset bandwidth utilization rate, the path corresponding to the minimum dynamic recursion value is continuously determined from the rest paths, and the optimal path is determined according to the process.
In an embodiment of the present invention, the target network may be a content delivery network CDN. The CDN network avoids bottlenecks and links on the Internet which may affect the data transmission speed and stability as far as possible, so that the content transmission is faster and more stable. By placing node servers at various positions of the network to form a layer of intelligent virtual network on the basis of the existing internet, the CDN system can redirect the request of a user to a service node closest to the user in real time according to network flow, connection of each node, load condition, distance to the user, response time and other comprehensive information. The method aims to enable the user to obtain the required content nearby, solve the problem of congestion of the Internet network and improve the response speed of the user for accessing the website.
It should be noted that, the embodiment of the present invention is described by taking the target network and the path from the planning node 1 to the planning node 7 shown in fig. 2 as examples, which are only a specific example of the present invention and do not limit the present invention.
The path planning method of the embodiment of the invention considers the bandwidth factor during path planning, and can avoid network congestion and network data transmission performance reduction.
Corresponding to the above method embodiment, the embodiment of the present invention further provides a path planning apparatus. As shown in fig. 3, fig. 3 is a schematic structural diagram of a path planning apparatus provided in an embodiment of the present invention. The path planning may include:
a determining module 301, configured to determine a source node and a target node in a target network.
A calculating module 302, configured to calculate dynamic recursive values of multiple paths from the source node to the target node according to the network parameter of the target network.
Wherein the network parameters at least comprise the bandwidth of the nodes in the target network;
and the planning module 303 is configured to determine an optimal path from the source node to the target node in the plurality of paths according to the dynamic recursive value.
In an embodiment of the present invention, the calculation module 302 may specifically be configured to:
establishing a two-dimensional array from a source node to a target node, wherein the rows and the columns of the two-dimensional array are both node identification information, and the element values of the two-dimensional array are values calculated according to network parameters of a target network;
and aiming at a target path in a plurality of paths from the source node to the target node, taking the sum of element values of the two-dimensional array corresponding to the target path as a dynamic recursive value of the target path, wherein the target path is a path selected from the plurality of paths from the source node to the target node.
In one embodiment of the present invention, the network parameters further include one or more of the following:
round trip delay of nodes, bandwidth cost of nodes, and distance between nodes.
In an embodiment of the present invention, the planning module 303 may be specifically configured to:
and in the plurality of paths, taking the path corresponding to the minimum dynamic recursion value in the dynamic recursion values as the optimal path from the source node to the target node.
In an embodiment of the present invention, the planning module 303 may be specifically configured to:
determining a path corresponding to the minimum dynamic recursive value from the plurality of paths according to the dynamic recursive value;
calculating the current bandwidth utilization rate of each node between a source node and a target node in a path corresponding to the minimum dynamic recursive value;
and if the calculated bandwidth utilization rate is not greater than the preset bandwidth utilization rate, taking the path corresponding to the minimum dynamic recursion value as the optimal path from the source node to the target node.
In one embodiment of the invention, the target network is a CDN.
The details of each part of the path planning apparatus shown in fig. 3 in the embodiment of the present invention are similar to the path planning method shown in fig. 1 in the embodiment of the present invention, and the embodiment of the present invention is not described herein again.
The path planning device of the embodiment of the invention considers the bandwidth factor during path planning, and can avoid network congestion and network data transmission performance reduction.
Fig. 4 is a block diagram illustrating an exemplary hardware architecture of a computing device capable of implementing a path planning method and apparatus according to embodiments of the present invention. As shown in fig. 4, computing device 400 includes an input device 401, an input interface 402, a central processor 403, a memory 404, an output interface 405, and an output device 406. The input interface 402, the central processing unit 403, the memory 404, and the output interface 405 are connected to each other through a bus 410, and the input device 401 and the output device 406 are connected to the bus 410 through the input interface 402 and the output interface 405, respectively, and further connected to other components of the computing device 400.
Specifically, the input device 401 receives input information from the outside and transmits the input information to the central processor 403 through the input interface 402; the central processor 403 processes the input information based on computer-executable instructions stored in the memory 404 to generate output information, stores the output information temporarily or permanently in the memory 404, and then transmits the output information to the output device 406 through the output interface 405; output device 406 outputs the output information outside of computing device 400 for use by a user.
That is, the computing device shown in fig. 4 may also be implemented as a path planning device, which may include: a memory storing computer-executable instructions; and a processor which, when executing computer executable instructions, may implement the path planning methods and apparatus described in connection with fig. 1-3.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium has computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement the path planning method provided by embodiments of the present invention.
It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions or change the order between the steps after comprehending the spirit of the present invention.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments mentioned in this patent describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
As described above, only the specific embodiments of the present invention are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present invention, and these modifications or substitutions should be covered within the scope of the present invention.
Claims (14)
1. A method of path planning, the method comprising:
determining a source node and a target node in a target network;
calculating dynamic recursive values of a plurality of paths from the source node to the target node according to network parameters of the target network, wherein the network parameters at least comprise bandwidths of nodes in the target network;
and determining the optimal path from the source node to the target node in the plurality of paths according to the dynamic recursive value.
2. The method of claim 1, wherein the calculating dynamic recursive values of a plurality of paths from the source node to the target node according to the network parameters of the target network comprises:
establishing a two-dimensional array from the source node to the target node, wherein the rows and the columns of the two-dimensional array are both node identification information, and the element values of the two-dimensional array are values obtained by calculation according to network parameters of the target network;
and regarding a target path in a plurality of paths from the source node to the target node, taking the sum of element values of the two-dimensional array corresponding to the target path as a dynamic recursive value of the target path, wherein the target path is a path selected from the plurality of paths from the source node to the target node.
3. The method of claim 1, wherein the network parameters further comprise one or more of the following:
round trip delay of the nodes, bandwidth cost of the nodes, and distance between the nodes.
4. The method of claim 1, wherein determining the optimal path from the source node to the target node among the plurality of paths according to the dynamic recurrence value comprises:
and in the plurality of paths, taking the path corresponding to the minimum dynamic recursive value in the dynamic recursive values as the optimal path from the source node to the target node.
5. The method according to claim 4, wherein the taking the path corresponding to the minimum dynamic recurrence value of the dynamic recurrence values as the optimal path from the source node to the target node comprises:
determining a path corresponding to the minimum dynamic recursive value in the plurality of paths according to the dynamic recursive value;
calculating the current bandwidth utilization rate of each node between the source node and the target node in the path corresponding to the minimum dynamic recursive value;
and if the bandwidth utilization rate is not greater than the preset bandwidth utilization rate, taking the path corresponding to the minimum dynamic recursive value as the optimal path from the source node to the target node.
6. The method of claim 1, wherein the target network is a Content Delivery Network (CDN).
7. A path planning apparatus, the apparatus comprising:
the determining module is used for determining a source node and a target node in a target network;
the calculation module is used for calculating dynamic recursive values of a plurality of paths from the source node to the target node according to network parameters of the target network, wherein the network parameters at least comprise the bandwidth of the nodes in the target network;
and the planning module is used for determining the optimal path from the source node to the target node in the plurality of paths according to the dynamic recursive value.
8. The apparatus of claim 7, wherein the computing module is specifically configured to:
establishing a two-dimensional array from the source node to the target node, wherein the rows and the columns of the two-dimensional array are both node identification information, and the element values of the two-dimensional array are values obtained by calculation according to network parameters of the target network;
and regarding a target path in a plurality of paths from the source node to the target node, taking the sum of element values of the two-dimensional array corresponding to the target path as a dynamic recursive value of the target path, wherein the target path is a path selected from the plurality of paths from the source node to the target node.
9. The apparatus of claim 7, wherein the network parameters further comprise one or more of the following:
round trip delay of the nodes, bandwidth cost of the nodes, and distance between the nodes.
10. The apparatus of claim 7, wherein the planning module is specifically configured to:
and in the plurality of paths, taking the path corresponding to the minimum dynamic recursive value in the dynamic recursive values as the optimal path from the source node to the target node.
11. The apparatus of claim 10, wherein the planning module is specifically configured to:
determining a path corresponding to the minimum dynamic recursive value in the plurality of paths according to the dynamic recursive value;
calculating the current bandwidth utilization rate of each node between the source node and the target node in the path corresponding to the minimum dynamic recursive value;
and if the bandwidth utilization rate is not greater than the preset bandwidth utilization rate, taking the path corresponding to the minimum dynamic recursive value as the optimal path from the source node to the target node.
12. The apparatus of claim 7, wherein the target network is a Content Delivery Network (CDN).
13. A path planning apparatus, characterized in that the apparatus comprises: a memory and a processor;
the memory is used for storing executable program codes;
the processor is configured to read executable program code stored in the memory to perform the path planning method of any of claims 1-6.
14. A computer readable storage medium having computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement a path planning method according to any one of claims 1-6.
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