Route determination method, communication device, and storage medium

Abstract

A route determination method, a communication device, and a storage medium are provided, which include the steps of first acquiring a first network topology of an audio-video system, in which attribute information of links in the first network topology includes link transmission parameters, the link transmission parameters including a concave parameter, an additive parameter, and a multiplicative parameter, determining links from the first network topology that satisfy a concave parameter constraint, generating a second network topology using the links that satisfy the concave parameter constraint, then generating a third network topology based on key parameters of the links in the second network topology, and determining a plurality of candidate routes based on the third network topology, and determining a target route that satisfies a route selection constraint from the plurality of candidate routes.

Description

[Technical Field]

[0001] (CROSS-REFERENCE TO RELATED APPLICATIONS) This application claims priority from a Chinese patent application bearing application number 202310622100.7, filed on May 29, 2023, the entire contents of which are incorporated herein by reference.

[0002] The present disclosure relates to the field of audio-video communications, and in particular to a routing method, a communication device, and a storage medium. [Background technology]

[0003] With the widespread adoption of mobile internet and the commercialization of 5G (5th-generation mobile communication technology), users are increasingly demanding low-latency, high-reliability audio-video applications. Among these technologies, Real-Time Communication (RTC) leverages long-term technical accumulation in the field of video traffic to rapidly provide the industry with high-concurrency, low-latency, high-definition, smooth, secure, and reliable full-scene, full-interactive, and full-real-time audio-video services, which are applicable to various application scenarios such as online education, cloud conferencing, and social entertainment. Route planning is a core technology of Real-Time Networks (RTNs). Route planning involves collecting and calculating edge data to plan optimal transmission routes between edge nodes. Summary of the Invention [Means for solving the problem]

[0004] In one aspect, embodiments of the present disclosure provide a route determination method, the route determination method comprising: acquiring a first network topology of the audio-video system, wherein attribute information of links in the first network topology includes transmission parameters of the links, and the transmission parameters of the links include a concave parameter, an additive parameter, and a multiplicative parameter; determining links from the first network topology that satisfy the concave parameter constraints, and generating a second network topology with the links that satisfy the concave parameter constraints; generating a third network topology based on key parameters of links in the second network topology, the key parameters being additive parameters and multiplicative parameters that have the highest influence on the target traffic type, and the attribute information of the links in the third network topology including quantification scores determined by the key parameters; determining a plurality of candidate routes based on a third network topology; determining a target route from the plurality of candidate routes that satisfies the route selection constraints.

[0005] In another aspect, an embodiment of the present disclosure provides a route determination device, comprising: an acquisition module for acquiring a first network topology of the audio-video system, wherein attribute information of links in the first network topology includes transmission parameters of the links, and the transmission parameters of the links include a concave parameter, an additive parameter, and a multiplicative parameter; a processing module for determining links from the first network topology that satisfy the concave parameter constraints and generating a second network topology with the links that satisfy the concave parameter constraints; The processing module is further used to generate a third network topology based on key parameters of the links in the second network topology, the key parameters being additive parameters and multiplicative parameters that have the highest influence on the target traffic type, and the attribute information of the links in the third network topology includes a quantification score determined by the key parameters; The processing module is further used for determining a plurality of candidate routes based on the third network topology, and determining a target route from the plurality of candidate routes that satisfies the route selection constraints.

[0006] In yet another aspect, an embodiment of the present disclosure provides a communications device, the communications device including a processor and a memory, the memory storing instructions executable by the processor, the processor configured, when executing the instructions, to cause the communications device to perform a method according to one aspect above.

[0007] In yet another aspect, embodiments of the present disclosure provide a computer-readable storage medium that stores computer instructions that, when executed by a computer, The The method according to the embodiment is carried out.

[0008] In yet another aspect, embodiments of the present disclosure provide a computer program product including computer instructions that, when executed by a computer, The The method according to the embodiment is carried out.

[0009] The accompanying drawings are used to provide a further understanding of the present disclosure and, together with the embodiments of the present disclosure, constitute a part of the specification used to explain the present disclosure and are not intended to limit the present disclosure. [Brief explanation of the drawings]

[0010] [Figure 1]FIG. 1 is a schematic diagram of an audio-video system architecture according to some embodiments. [Figure 2] 1 is a method flowchart of a route determination method according to some embodiments. [Figure 3] FIG. 1 is a schematic diagram of a network topology according to some embodiments. [Figure 4] FIG. 2 is a schematic diagram of another network topology according to some embodiments. [Figure 5] FIG. 1 is a schematic diagram of candidate routes according to some embodiments. [Figure 6] FIG. 1 is a schematic block diagram of a routing device according to some embodiments. [Figure 7] 1 is a schematic structural diagram of a routing device according to some embodiments; DETAILED DESCRIPTION OF THE INVENTION

[0011] The invention according to the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are only some of the embodiments of the present disclosure, and are not all of the embodiments. All other embodiments that a person skilled in the art can obtain based on the embodiments of the present disclosure without any creative work are included in the scope of protection that the present disclosure intends to protect.

[0012] In the description of the present disclosure, unless otherwise specified, " / " means "or," for example, A / B may mean A or B. In this specification, "and / or" is only a relational relationship for describing related objects, and means that three relationships may exist, for example, A and / or B may mean A only, B only, or A and B. Also, "at least one" means one or more, and "plurality" means two or more. Expressions such as "first," "second," etc. do not limit the quantity or execution order, and expressions such as "first," "second," etc. do not necessarily limit different things.

[0013] It should be noted that in this disclosure, phrases such as "for example" and "for example" are used to indicate an example, illustration, or explanation. Any embodiment or design described in this disclosure as "for example" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of phrases such as "for example" and "for example" is intended to provide a detailed description of the relevant concept.

[0014] In some techniques, path planning techniques in RTN usually use one composite parameter to represent the characteristics of multiple parameters, construct a function mapping model using multiple parameters as function variables, and use the function value as the basis for path planning. However, this path planning method has significant limitations.

[0015] In practical applications, real-time audio-video communication traffic applications typically rely on RTN systems to achieve high-speed, high-quality data transmission, which may impose requirements on multiple independent parameters, such as network delay, packet loss rate, and bandwidth. Therefore, it is difficult to guarantee that each parameter of the route meets the traffic requirements based on the above route planning method.

[0016] In view of this, an embodiment of the present disclosure provides a route determination method, the method including: acquiring a first network topology of an audio-video system, where attribute information of links in the first network topology includes link transmission parameters, the link transmission parameters including concave parameters, additive parameters, and multiplicative parameters; determining links from the first network topology that satisfy a concave parameter constraint and generating a second network topology using the links that satisfy the concave parameter constraint; generating a third network topology based on key parameters of the links in the second network topology, where the key parameters are additive parameters and multiplicative parameters that have the highest influence on a target traffic type, and the attribute information of the links in the third network topology includes quantification scores determined by the key parameters; determining multiple candidate routes based on the third network topology; and determining a target route from the multiple candidate routes that satisfies a route selection constraint. In this way, route planning can be applied to various traffic scenarios, thereby improving the practicality and accuracy of route planning.

[0017] 1 illustrates an audio-video system architecture according to an embodiment of the present disclosure. As shown in FIG. 1, the audio-video system may include a control node 110 and an edge node 120.

[0018] In some embodiments, the audio-video system may include an audio-video cloud network, which may be used to enable distributed deployment of edge computing infrastructure resources and to manage these resources in a unified manner. A centralized deployment point with a large number of resources is called a central cloud, while a widely distributed deployment point with a small number of resources is called an edge cloud (also called an edge cloud node). Because edge clouds are distributed more widely, they are closer to the terminal devices used by users. Therefore, an edge cloud may be understood as a cloud computing platform close to the terminal devices, and a central cloud may be understood as a cloud platform that manages multiple edge clouds in a unified manner.

[0019] The control node 110 is located in the central cloud and is responsible for controlling and managing the media nodes, and for receiving and processing node information and link quality information reported by the media nodes. In some embodiments, the control node 110 may be responsible for controlling and scheduling the edge nodes 120 in the audio-video system and managing system data. In some embodiments, the control node 110 may include a network recognition module, a simplification module, a quantification module, a calculation module, and a matching module.

[0020] The edge nodes 120 are located in the edge cloud, and a data transmission path may consist of multiple edge nodes 120 and links between the nodes. The edge nodes 120 may consist of multiple small nodes and be widely distributed. The edge nodes 120 can transfer traffic data in the RTN network at high speed and with high quality.

[0021] In some embodiments, the audio-video system may further include a client 130 that accesses the edge node 120. The client 130 may be any of a variety of physical devices or software applications (e.g., a mobile phone application (App), a software development kit (SDK)), or terminal devices (e.g., a mobile phone, a tablet, a desktop computer, a laptop computer, a handheld computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook, and terminal devices such as a mobile phone, a personal digital assistant (PDA), an augmented reality (AR) / virtual reality (VR) device) that support the generation, transmission, and display of data such as audio and video.

[0022] It should be understood that the system architecture shown in FIG. 1 is not intended to limit embodiments of the present disclosure, and that the system architecture shown in FIG. 1 may include more or fewer components than those shown, may combine certain components, or may have different component arrangements.

[0023] The method according to the present disclosure will now be described in detail with reference to the accompanying drawings.

[0024] As shown in FIG. 2, an embodiment of the present disclosure provides a route determination method including the following steps.

[0025] S101, first obtain the network topology of the audio-video system. The attribute information of the link in the first network topology includes transmission parameters of the link, and the transmission parameters of the link include a concave parameter, an additive parameter, and a multiplicative parameter.

[0026] In some embodiments, the concave parameter includes bandwidth, the additive parameter includes cost and / or delay, and the multiplicative parameter includes packet loss rate. In some embodiments, the additive parameters may also include parameters such as jitter, number of node hops, etc.

[0027] In some embodiments, for a path between any two nodes in the first network topology, the value of the concavity parameter of the path is equal to the minimum value of the concavity parameters of all the links that make up the path.

[0028] Taking bandwidth as an example, G=(V,E) is defined as representing the first network topology, where V represents the set of nodes and E represents the set of links of the connecting nodes. P(s,d) is defined as the set of transmission paths in the first network topology, where s∈V represents the source node and d∈V represents the destination node. The bandwidth of path p can be determined based on the following equation (1):

number

[0029] In some embodiments, for a path between any two nodes in the first network topology, the value of the additivity parameter for that path is obtained by performing an addition operation based on the values ​​of the additivity parameters of all links that make up that path.

[0030] For example, the cost of a path p can be determined based on the following equation (2):

number

[0031] For example, the delay of path p can be determined based on the following equation (3):

number

[0032] In some embodiments, for a path between any two nodes in the first network topology, the value of the multiplicative parameter for that path is obtained by performing a multiplication operation based on the values ​​of the multiplicative parameters of all links that make up that path.

[0033] For example, the packet loss rate of a path p can be determined based on the following equation (4):

number

[0034] In some embodiments, a control node of the audio-video system may perceive the data in real time at a preset frequency to obtain a real-time network topology of the audio-video system.

[0035] In some embodiments, the above network awareness may be realized by a periodic task: the control node may analyze the relationships between edge nodes through a network awareness module to obtain probe data such as packet loss rate, delay, jitter, and bandwidth usage of links between each edge node, and send a network probe request to each node in the edge cloud, so that the edge node periodically performs network probes on connected nodes based on the above preset frequency.

[0036] In some embodiments, the control node may also obtain and record specific data for individual nodes (e.g., node IP addresses, node identity documents (IDs), node hardware parameters (e.g., CPU, memory, etc.)).

[0037] In some embodiments, the control node may perform network recognition to acquire data, and then perform anomaly processing of the received data, such as detecting whether the data is returned according to a standard format, detecting whether the data exceeds a predetermined range, etc., to determine whether the data is anomalous and process the data for which an anomaly is detected.

[0038] In some embodiments, when the network topology of the audio-video system changes (e.g., nodes are added or removed, connecting links are added or removed, etc.), the control node may again perform network recognition based on the real-time network topology. For example, the control node may send new network probe requests and data collection requests to each edge node to obtain new data and update the first network topology based on the obtained new data.

[0039] S102: Determine links that satisfy the concave parameter constraint conditions from the first network topology, and generate a second network topology using the links that satisfy the concave parameter constraint conditions.

[0040] In some embodiments, when the concavity parameter includes a bandwidth, the pre-conditions for the concavity parameter are (i.e., the concave parameter constraints above) The concavity parameter may include a bandwidth being less than a predetermined threshold. That is, the control node may obtain a second network topology by deleting links in the first network topology that do not satisfy the predetermined condition based on the concavity parameter, thereby simplifying the network topology. Taking the control node 110 in FIG. 1 as an example, the control node 110 may obtain a second network topology by simplifying the first network topology of the audio-video system through the simplification module.

[0041] The preset threshold is a value in the form of a bandwidth value that is preset or determined in real time based on the actual network topology, a ratio of the real-time bandwidth to the total available bandwidth of the link, etc. If the bandwidth of the link is equal to or greater than the preset threshold, this indicates that the link is approaching saturation and cannot allocate any more traffic, so the control node may remove the link from the first network topology.

[0042] In some embodiments, the control node may generate the second network topology based on a simplification operation directed to the first network topology according to a simplified model.

[0043] For example, the simplified model may be preset with the concave parameter constraint (e.g., bandwidth is less than a preset threshold). The control node may input the first network topology and the bandwidths of the links between all nodes in the first network topology into the simplified model. The simplified model may then be configured to calculate the concave parameter constraint from the first network topology. does not satisfy By dynamically deleting links, the second network topology above can be obtained.

[0044] As an example, as shown in FIG. 3, the nodes in the first network topology obtained by the control node performing network recognition include node A, node B, node C, node D, node E, and node F. The preset condition of the concavity parameter includes that the bandwidth is less than 90% of the total available bandwidth of the link. If the real-time bandwidth of the link from node B to node E is 2.7 Gbps and reaches 90% of the total available bandwidth of the link, which is 3 Gbps, as shown in FIG. 3, the control node No. 1 Network Topology Jika The link can then be temporarily removed from the network topology to obtain a second network topology.

[0045] In some embodiments, the control node may update the second network topology in real time based on data obtained by network awareness, and if data obtained by subsequent network awareness indicates that the bandwidth value of the removed link comes to satisfy the concavity parameter constraint, the control node may update the second network topology based on data obtained by the new network awareness to dynamically restore the link in the updated second network topology.

[0046] S103, generating a third network topology based on the key parameters of the links in the second network topology. The key parameter is a parameter that has the greatest influence on the target traffic type among the additive parameters and the multiplicative parameters. The attribute information of the link in the third network topology includes a quantification score determined by the key parameter.

[0047] In some embodiments, the control node may determine key parameters of a target traffic type based on the traffic requirements corresponding to the target traffic type to which the target traffic belongs.

[0048] As examples, target traffic may include cloud PC, interactive whiteboard, video conferencing, video IoT, interactive live broadcast, extended reality (XR), and other possible traffic.

[0049] In one example, if the target traffic is traffic for a cloud PC, an interactive whiteboard, or the like, which has very low tolerance for delay and tolerates only a small amount of packet loss, the control node may determine that the target traffic type is traffic with a delay priority requirement (i.e., a key parameter of the target traffic type is delay). In another example, if the target traffic is transmission of a compressed data file, or other traffic in which packet loss rate requirements take priority over delay requirements or other requirements, the control node may determine that the target traffic type is traffic with a packet loss rate priority requirement (i.e., a key parameter of the target traffic type is packet loss rate). Furthermore, the target traffic type in the embodiments of the present disclosure may include other possible traffic types, which will not be listed here.

[0050] In some embodiments, the control node can obtain a quantified score of the link based on the key parameter of the link, use the structure of the second network topology as the structure of a third network topology, and generate a third network topology using the quantified score of the link as attribute information of the link in the third network topology.

[0051] The quantification score of a link is intended to characterize the reliability of that link for transmitting traffic data of that traffic type.

[0052] As an example, the quantification score may be negatively correlated with reliability, i.e., the smaller the quantification score of a link, the more reliable the link is for transmitting traffic data of a traffic type, and conversely, the larger the quantification score of a link, the less reliable the link is for transmitting traffic data of a traffic type.

[0053] As another example, the quantification score may have a positive correlation with the reliability. Note that the relationship between the quantification score and the reliability mainly depends on the algorithm for determining the quantification score. Below, a detailed explanation will be given, focusing on the negative correlation between the quantification score and the reliability.

[0054] In some embodiments, the control node can obtain the third network topology based on the key parameters of the target traffic type and the quantification model. The quantification model can map the key parameters of the link to a value representing the quantification score of the link according to a predetermined mathematical conversion relationship. Taking the control node 110 of FIG. 1 as an example, the quantification model of the control node 110 Module In this case, the quantification model can be preset, and the control node 110 can determine the third network topology through the quantification module.

[0055] For example, the control node can input the key parameters of the second network topology and the links between all the nodes of the second network topology into the quantification model to obtain the above third network topology.

[0056] Figure 4 shows a third network topology with delay, packet loss rate, and cost as key parameters. As shown in Figure 4, the third network topology includes node A, node B, node C, ..., and node F. Taking the third network topology with delay as a key parameter as an example, the quantification score of link AB between node A and node B is set to 6, the quantification score of link AC is set to 3, the quantification score of link BD is set to 5, the quantification score of link BC is set to 2, the quantification score of link CE is set to 4, the quantification score of link CD is set to 3, the quantification score of link DE is set to 2, the quantification score of link DF is set to 3, and the quantification score of link EF is set to 6.

[0057] In one implementation, the control node can pre-determine quantified network topologies corresponding to multiple possible key parameters, and can further select a quantified network topology corresponding to a target traffic type (i.e., the third network topology described above) based on the traffic type to which the target traffic belongs.

[0058] In another implementation, the control node can first determine a target traffic type and then determine the third network topology based on the traffic requirements corresponding to the target traffic type and the second network topology of the audio-video system.

[0059] The above invention uses a key parameter-based route planning method to classify parameters in an audio-video system, and first simplify the first network topology using concavity parameters to obtain a second network topology. Furthermore, a third network topology is determined based on the key parameters that have the highest impact on the differences between different traffic types and the target traffic, and candidate routes are then determined from the third network topology. In this way, the third network topology corresponding to different traffic types can be calculated based on different key parameters, eliminating the need for parameter synthesis, i.e., the need to determine a function mapping model for the synthesis parameters. This reduces computational complexity and improves the feasibility of route planning.

[0060] S104, determining a plurality of candidate routes based on the third network topology.

[0061] In some embodiments, the control node may determine a plurality of paths between the first node and the second node based on a third network topology, and determine a path score for each of the plurality of paths. The path score for a path is obtained based on the quantified scores of all links that make up the path. The first node and the second node are any two nodes in the third network topology.

[0062] Similar to the quantification score of a link, the route score of a route is intended to characterize the reliability of the route for transmitting traffic data of a traffic type. The route score may also be negatively correlated with the reliability. Alternatively, the route score may be positively correlated with the reliability. It should be understood that the relationship between the route score and the reliability mainly depends on the route score determination algorithm. The following will focus on the negative correlation between the route score and the reliability in more detail.

[0063] Furthermore, the control node can determine the top N paths with the smallest path scores among the multiple paths as multiple candidate paths between the second node and the first node, where N is a positive integer greater than 1. Taking the control node 110 in Figure 1 as an example, the above multiple candidate paths can be determined by a calculation module.

[0064] In some embodiments, the plurality of paths between the first node and the second node includes a first path that is the shortest path from the first node to the second node, and a second path that is the shortest path from the first node to a third node. (also called divergence nodes) fart The history path from the third node to the second node shortest The third node is any node on the first path other than the first node and the second node.

[0065] In the third network topology, the shortest path from the first node to the second node can be understood to be the path from the first node to the second node that has the smallest path score in the third network topology.

[0066] As an example, the process by which the control node determines multiple candidate routes may be realized, for example, by the following steps. S1, the control node determines the first node (source node) and the second node (destination node) in the third network topology. As an example, the control node can define G = (V, E) to represent the first network topology, where V represents the set of nodes and E represents the set of links of the connecting nodes. The control node denote the first node as s (s∈V) and the second node as d (d∈V). The i-th candidate path from node s to node d is denoted as p i (s, d), and the set of multiple paths is P n (s,d)={p1(s,d),p2(s,d),…,p n (s,d)}.

[0067] In S2, the control node calculates the shortest path from the first node s to the second node d, i.e., the path with the smallest path score in the third network topology. The control node can denote this shortest path as p1(s,d).

[0068] S3: The control node determines all other nodes on p1(s,d) except the second node as divergent nodes, and creates a divergent node set D = {d1,d2,...,d x The discrepancy node set has a total of x discrepancy nodes.

[0069] S4, the control node is the deviation node d i (i=1,2,...,x) according to the discrepancy node d i The shortest path from node 1 to node 2, i.e., the path with the smallest quantification score, can be determined and used as a candidate path.

[0070] S5, the control node is the node d separated from the first node in p1(s,d). i The path to the discrepancy node d determined in S4 i Based on the shortest path from the first node to the second node, the path between the first node and the second node is determined and recorded in a second path set C(s, d).

[0071] S6, D = {d1, d2, …, d x After traversing all the deviation nodes in}, the control node determines the path with the smallest path score in C(s,d), which can be denoted as p2(s,d). p 2 (s,d) From set C(s,d) to set P n p2(s,d) is the second shortest path between the first node and the second node and can be a candidate path.

[0072] S7: The control node updates the deviation node set based on the determination method shown in S3 to S6; Candidate Route Set P n (s,d) (i.e., a set of multiple routes above) New candidate routes can be determined until the number of routes in reaches N.

[0073] For example, as shown in Fig. 5, in the third network topology in which delay is a key parameter, a candidate route from source node A to destination node F is determined, and N is set to 4. Furthermore, based on this third network topology, the control node can determine the route score of the route candidate A → C → D → F as 9, the route score of the route candidate A → C → E → D → F as 12, the route score of the route candidate A → C → E → F as 13, and the route score of the route candidate A → C → B → D → F as 13.

[0074] In some embodiments, the control node can calculate candidate paths between any two nodes in the third network topology, and further determine multiple candidate paths between the source node and the destination node from all candidate paths in the third network topology based on the source node and destination node of the target traffic.

[0075] S105: A target route that satisfies the route selection constraints is determined from the plurality of candidate routes.

[0076] In some embodiments, the control node may obtain transmission parameters of all links that make up the candidate route and determine transmission parameters of the candidate route based on the transmission parameters of all links that make up the candidate route.

[0077] In one example, for the concavity parameter, the value of the concavity parameter of the candidate route is equal to the minimum value of the concavity parameter values ​​of all the links that make up the candidate route. For example, the bandwidth value of the candidate route can be determined based on the above equation (1).

[0078] In another example, for the additive parameters, the additive parameter of a candidate route is obtained by performing an addition operation based on the additive parameter values ​​of all links constituting the candidate route. For example, the cost of the candidate route can be determined based on the above formula (2), and the delay of the candidate route can be determined based on the above formula (3).

[0079] In yet another example, for the multiplicative parameter, the value of the multiplicative parameter of the candidate route is obtained by performing a multiplication operation based on the values ​​of the multiplicative parameters of all links constituting the route. For example, the packet loss rate of the candidate route can be determined based on the above equation (4).

[0080] In some embodiments, the control node may also express the transmission parameters of the candidate paths as parametric equations.

[0081] As an example, let's take the third network topology where delay is a key parameter, and the route information is "A → C → D → F". The delay of link A → C is 30 ms, the packet loss rate is 1%, the jitter is 10 ms, and the cost is 1. The delay of link C → D is 40 ms, the packet loss rate is 1%, the jitter is 10 ms, and the cost is 2. The delay of link D → F is 30 ms, the packet loss rate is 1%, the jitter is 10 ms, and the cost is 3. Then, the delay of route A → C → D → F is 100 ms, the packet loss rate is 3%, and the jitter is 30 ms, and the cost is 6. Therefore, the parameter formula of the candidate route can be expressed as "type=1,path='ACD-F',score=9,delay=100,jitter=30,lost=3,hop=4,cost=6", where type=1 indicates the traffic type, i.e., the traffic requirement is delay priority.

[0082] This allows the control node to determine, as the target route, a route that satisfies the route selection constraints from among the multiple candidate routes based on the transmission parameters of each of the multiple candidate routes.

[0083] The route selection constraints are used to constrain the transmission parameters of the target route. The route selection constraints are determined based on the parameter requirements of the target traffic. If the target traffic imposes constraints on multiple transmission parameters, the route selection constraints are used to constrain multiple transmission parameters of the target route. Naturally, if the target traffic imposes constraints on only one transmission parameter, the route selection constraints are used to constrain one transmission parameter of the target route.

[0084] In some embodiments, the path selection constraints may include multiplicative and / or additive parameters of the path's transmission parameters, such as delay, packet loss rate, jitter, and number of node hops. The path selection constraints may also include concave parameters of the path's transmission parameters. In some embodiments, the path selection constraints may include traffic information of the target traffic (e.g., information such as the traffic type, source node, and destination node of the target traffic).

[0085] In some embodiments, the control node can express the routing constraints of the target traffic as a multiple constraint logical formula. The method of expressing the transmission parameters in the routing constraints expressed in the multiple constraint logical formula must be consistent with the above parameter formula (e.g., including source node (src), destination node (dest), delay, packet loss rate (lost), jitter, node hop count (hop), etc.). In addition, the control node can combine detailed constraints of each parameter in the routing constraints with operators to form a multiple constraint logical formula.

[0086] If the route selection constraints include that the source node is A, the destination node is F, the traffic type is a cloud computer, and the transmission delay of the entire link is less than 350 ms or the jitter is less than 50 ms, the packet loss rate is less than 5%, and the number of node hops is less than 5 hops, the control node can determine "src='A' and dest='F' and type='1' and delay<350 or jitter<50 and lost<5 and hop<5" as the multiple constraint logical formula.

[0087] Furthermore, the control node can determine the target path by matching the multiple constraint logical formula representing the path selection constraints with the parameter formula of each of the above candidate paths. Taking the control node 110 in Figure 1 as an example, the control node 110 can match the traffic path selection constraints with the transmission parameters of the candidate paths through a matching module.

[0088] For example, suppose the parameter expressions of multiple candidate routes are "type=1,path='ACD-F',delay=100,jitter=30,lost=3,hop=4,cost=6", "type=1,path='ACED-F',delay=200,jitter=30,lost=6,hop=5,cost=10", "type=1,path='ACE-F',delay=300,jitter=40,lost=4,hop=4,cost=15", and "type=1,path='ACBD-F',delay=400,jitter=40 , lost=4,hop=5,cost=13", based on the above multiple constraint logical formula, the parameter formulas that match the multiple constraint logical formula can be determined to include "type=1,path='ACD-F',delay=100,jitter=30,lost=3,hop=4,cost=6" and "type=1,path='ACE-F',delay=300,jitter=40,lost=4,hop=4,cost=15", and the route corresponding to the matching parameter formula can be determined as the target route.

[0089] Based on the above embodiment, this method first simplifies the network topology based on the concavity parameters, and then determines a third network topology based on key parameters of different traffic types to facilitate the determination of candidate routes. Furthermore, the method can more accurately reflect the multiple parameters of each candidate route and determine a route from the candidate routes that meets the requirements of multiple traffic parameters based on the parameters of the candidate routes. This allows for more accurate route planning. Furthermore, the route planning can be applied to various traffic scenarios, improving the practicality of the route planning.

[0090] The present disclosure has been described above primarily from the perspective of interactions between nodes. It should be understood that each node, e.g., an apparatus or device, includes hardware configurations and / or software modules corresponding to the functions described above. As will be readily understood by those skilled in the art, with reference to the steps of the algorithms of the examples disclosed herein, the present disclosure can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is implemented in hardware or by computer software driving hardware depends on the specific application and design constraints of the invention. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementations should not be interpreted as departing from the scope of the present invention.

[0091] 6 is a schematic block diagram of a path determination device applied to a first node according to some embodiments. As shown in FIG. 6, the path determination device 60 includes an acquisition module 601 and a processing module 602.

[0092] In some embodiments, the acquisition module 601 is for acquiring a first network topology of an audio-video system, and the attribute information of links in the first network topology includes link transmission parameters, the link transmission parameters including a concave parameter, an additive parameter, and a multiplicative parameter. The processing module 602 determines links from the first network topology that satisfy the concave parameter constraint and generates a second network topology using the links that satisfy the concave parameter constraint. The processing module 602 is further used to generate a third network topology based on key parameters of the links in the second network topology. The key parameters are the additive parameters and the multiplicative parameters that have the greatest influence on the target traffic type. The attribute information of the links in the third network topology includes a quantification score determined by the key parameters. The processing module 602 is further used to determine multiple candidate routes based on the third network topology and determine a target route that satisfies the route selection constraint from the multiple candidate routes.

[0093] In some embodiments, the concave parameter comprises bandwidth, the additive parameter comprises cost and / or delay, and the multiplicative parameter comprises packet loss rate.

[0094] In some embodiments, when the concavity parameter includes a bandwidth, the concavity parameter constraints The conditions include the bandwidth being below a preset threshold.

[0095] In some embodiments, the processing module 602 is used to obtain quantified scores of the links based on the key parameters of the links, use the structure of the second network topology as the structure of a third network topology, and generate a third network topology with the quantified scores of the links as attribute information of the links in the third network topology.

[0096] In some embodiments, the processing module 602 is used to determine a plurality of paths between the first node and the second node based on the third network topology, and determine a path score for each of the plurality of paths. The path score of a path is obtained based on the quantified scores of all links constituting the path. The first node and the second node are any two nodes in the third network topology. From the plurality of paths, top N paths with the smallest path scores are determined as a plurality of candidate paths between the second node and the first node, where N is a positive integer greater than 1.

[0097] In some embodiments, the multiple paths between the first node and the second node include a first path that is the shortest path from the first node to the second node, and a third path that is any node in the first path other than the first node and the second node. The history path from the third node to the second node shortest and a second path consisting of the first path and the second path.

[0098] In some embodiments, the acquisition module 601 includes: Multiple Candidate Route Each of and determining transmission parameters of the candidate route based on the transmission parameters of all the links that constitute the candidate route. The processing module 602 is used to determine a target route that satisfies the route selection constraints from the plurality of candidate routes based on the transmission parameters of each of the plurality of candidate routes.

[0099] In some embodiments, for a concave parameter, the value of the concave parameter of a candidate route is equal to the minimum value of the concave parameter values ​​of all links that make up the candidate route; for an additive parameter, the value of the additive parameter of a candidate route is obtained by performing an addition operation based on the additive parameter values ​​of all links that make up the candidate route; and for a multiplicative parameter, the value of the multiplicative parameter of a candidate route is obtained by performing a multiplication operation based on the multiplicative parameter values ​​of all links that make up the candidate route.

[0100] 6 may be called units, for example, the acquisition module may be called an acquisition unit. In the embodiment shown in FIG. 6, the names of the modules do not have to be the names shown in the figure, for example, the acquisition module may be called a communication module.

[0101] Each unit in FIG. 6 may be implemented in the form of a software functional module and stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the invention according to the embodiments of the present disclosure may essentially be embodied in the form of a software product, in other words, a portion that contributes to the prior art, or all or a portion of the invention, stored in a storage medium containing several instructions for causing a computer device (such as a personal computer, a server, or a network device) or a processor to execute all or a portion of the steps of the methods of various embodiments of the present disclosure. Storage media for storing computer software products include various media capable of storing program code, such as a USB memory, a removable hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0102] The embodiments of the present disclosure further provide a schematic structural diagram of a routing device when the functions of the above integrated modules are implemented in the form of hardware. As shown in Figure 7, the routing device 70 includes a processor 702, a communication interface 703, and a bus 704. In some embodiments, Route Determination The device 70 may further include a memory 701 .

[0103] The processor 702 may implement or execute various exemplary logic blocks, modules, and circuits described in connection with this disclosure. The processor 702 may be a central processor, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. The processor 702 may implement or execute various exemplary logic blocks, modules, and circuits described in connection with this disclosure. The processor 702 may also be a combination that implements computing functions, including, for example, a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0104] The communication interface 703 is for connecting to other devices via a communication network, which may be an Ethernet, a wireless access network, a wireless local area network (WLAN), etc.

[0105] Memory 701 may be, but is not limited to, read-only memory (ROM) or other type of static storage capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage capable of storing information and instructions, electrically erasable programmable read-only memory (EEPROM), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer.

[0106] In one implementation, the memory 701 may exist independently of the processor 702, or the memory 701 may be connected to the processor 702 via a bus 704 to store instructions or program code. The processor 702 accesses and executes instructions and program code stored in the memory 701 to perform the operations according to the embodiments of the present disclosure. route A decision method can be implemented.

[0107] In another embodiment, memory 701 may be integrated with processor 702 .

[0108] The bus 704 may be an extended industry standard architecture (EISA) bus, etc. The bus 704 is divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 7, but this does not mean only one bus or only one type of bus.

[0109] From the description of the above embodiments, it will be apparent to those skilled in the art that the division of the above functional modules is merely exemplary for the sake of convenience and simplicity of explanation; in actual applications, the above functions may be allocated to different functional modules as needed, that is, the internal structure of the device or apparatus may be divided into different functional modules to achieve all or part of the above functions.

[0110] An embodiment of the present disclosure further provides a computer-readable storage medium, comprising computer instructions for causing all or part of the flow of the above method embodiment to be executed by associated hardware. or programThe program may be stored in the computer-readable storage medium described above. When executed, the program may include the flow of each of the method embodiments described above. The computer-readable storage medium may be the memory of any of the aforementioned embodiments. The computer-readable storage medium may be an external storage device of the device or apparatus, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., provided in the device or apparatus. Furthermore, the computer-readable storage medium may include both an internal storage unit and an external storage device of the device or apparatus. The computer-readable storage medium stores the computer program as well as other programs and data required by the device or apparatus. The computer-readable storage medium may be used to temporarily store data that has been output or is to be output. The computer-readable storage medium includes a non-transitory computer-readable storage medium.

[0111] When executed by a computer, the embodiments of the present disclosure may be implemented in a manner similar to that described above. route There is further provided a computer program product comprising a computer program for causing a computer to perform any of the determination methods.

[0112] Although the present disclosure has been described herein with reference to various embodiments, those skilled in the art will understand and implement other variations of the disclosed embodiments in the practice of the present disclosure as defined in the claims, by studying the accompanying drawings, the contents of the disclosure, and the claims. In the claims, the word "comprising" does not exclude other elements or steps, and the words "a" or "one" do not exclude a plurality. A single processor or other unit may implement several functions recited in the claims. The fact that certain means are recited in mutually different dependent claims does not mean that these means cannot be combined to achieve satisfactory results.

[0113] Although the present disclosure has been described with detailed features and examples thereof, it is apparent that various modifications and combinations are possible without departing from the spirit and scope of the present disclosure. Therefore, the present specification and accompanying drawings are merely exemplary descriptions of the present disclosure as defined by the appended claims, and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the present disclosure. Obviously, those skilled in the art can make various modifications and variations based on the present disclosure without departing from the spirit and scope of the present disclosure. Thus, if these modifications and variations of the present disclosure fall within the scope of the claims of the present disclosure and the technology equivalent thereto, the present disclosure also intends to include these modifications and variations.

[0114] The above are merely specific embodiments of the present disclosure, but the scope of protection of the present disclosure is not limited thereto, and any modifications or replacements within the technical scope disclosed by the present disclosure shall be included within the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure shall be governed by the claims.

Claims

1. A route determination method, comprising: acquiring a first network topology of the audio-video system, wherein attribute information of links in the first network topology includes transmission parameters of the links, the transmission parameters of the links including a concave parameter, an additive parameter, and a multiplicative parameter; determining links from the first network topology that satisfy the concave parameter constraints, and generating a second network topology with the links that satisfy the concave parameter constraints; generating a third network topology based on key parameters of links in the second network topology, the key parameters being the additive parameters and the multiplicative parameters that have the greatest influence on a target traffic type, and attribute information of links in the third network topology including quantification scores determined by the key parameters; determining a plurality of candidate routes based on the third network topology; determining a target route from the plurality of candidate routes that satisfies a route selection constraint; method.

2. the concave parameter comprises bandwidth, the additive parameter comprises cost and / or delay, and the multiplicative parameter comprises packet loss rate; The method of claim 1.

3. If the concavity parameter includes a bandwidth, the preset condition for the concavity parameter includes the bandwidth being less than a preset threshold. The method of claim 1.

4. generating a third network topology based on key parameters of links in the second network topology, obtaining a quantified score for the link based on key parameters of the link; generating the third network topology by using the structure of the second network topology as the structure of the third network topology and using the quantified scores of the links as attribute information of the links in the third network topology, The method of claim 1.

5. determining a plurality of candidate routes based on the third network topology, determining a plurality of paths between a first node and a second node based on the third network topology, and determining a path score for each of the plurality of paths, wherein the path scores for the plurality of paths are obtained based on quantified scores of all links constituting the plurality of paths, and the first node and the second node are any two nodes in the third network topology; determining, from the plurality of routes, top N routes with the smallest route scores as a plurality of candidate routes between the second node and the first node, where N is a positive integer greater than 1; The method of claim 1.

6. the plurality of paths between the first node and the second node include a first path that is the shortest path from the first node to the second node, and a second path that is composed of a shortest path from the first node to a third node and a second shortest path from the third node to the second node, and the third node is any node on the first path other than the first node and the second node; The method of claim 5.

7. The step of determining a target route that satisfies a route selection constraint from the plurality of candidate routes includes: acquiring transmission parameters of all links constituting the candidate route, and determining transmission parameters of the candidate route based on the transmission parameters of all links constituting the candidate route; determining a target route that satisfies a route selection constraint from the plurality of candidate routes based on transmission parameters of each of the plurality of candidate routes; The method of claim 1.

8. Regarding the concavity parameter, the value of the concavity parameter of the candidate route is equal to the minimum value of the concavity parameter values ​​of all the links constituting the candidate route; Regarding an additive parameter, the value of the additive parameter of the candidate route is obtained by performing an addition operation based on the values ​​of the additive parameters of all links constituting the candidate route; Regarding the multiplicative parameter, the value of the multiplicative parameter of the candidate route is obtained by performing a multiplication operation based on the values ​​of the multiplicative parameters of all the links constituting the candidate route. The method of claim 7.

9. A communication device including a memory and a processor, a memory coupled to a processor, the memory being for storing instructions executable by the processor, the processor, when executing the instructions, performing the method of any one of claims 1 to 8; Communication equipment.

10. 1. A computer-readable storage medium, comprising: The computer-readable storage medium stores computer instructions, which, when executed by a communication device, cause the communication device to perform the method according to any one of claims 1 to 8. A computer-readable storage medium.

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