Network resource optimization method, device and system, computer equipment and computer storage medium

Abstract

The invention discloses a network resource optimization method, device and system, computer equipment and a computer storage medium, and the method comprises the steps: obtaining physical network information, and generating a virtual network topological graph based on the physical network information; the virtual network topological graph comprises nodes, links between the nodes and weights corresponding to the links; determining shortest path information from a source node to each node in the virtual network topological graph; determining a first time period and a second time period included in the basic time period according to monitoring requirements and / or network flow characteristics; monitoring the performance index of the first link in the basic time period, and performing fault detection on the first link based on the monitored performance index, the first time period and the second time period to obtain a fault detection result; and determining a virtual routing flow table according to the fault detection result, wherein the virtual routing flow table is used for performing optimal configuration on the network equipment and / or the connection between the network equipment.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a network resource optimization method, device, system, computer equipment and computer storage medium. Background Art

[0002] As a new type of network architecture, cloud networks provide users with efficient and flexible network services. With the continuous expansion of cloud networks and the increasing complexity of application scenarios, optimizing network resource allocation has become a pressing issue. Traditional network resource optimization methods, such as load balancing, resource scheduling, and performance optimization, are typically based on experience and rules, and are difficult to adapt to the dynamic changes and complex requirements of cloud networks.

[0003] As an emerging technical means of simulating physical entities through digital models, digital twin technology provides new ideas and methods for optimizing cloud network resources. By building a digital twin model of the cloud network, real-time monitoring, simulation optimization and intelligent decision-making of network resources can be achieved, thereby improving the utilization efficiency and service quality of network resources, building an accurate virtual model to reflect and control the physical network in real time, realizing efficient resource allocation and performance improvement, and promoting the development of cloud networks.

[0004] However, current network resource optimization methods based on digital twin technology lack response strategies for network emergencies such as dynamic changes in network resources, surges in network traffic, and sudden changes in network link performance. This makes it difficult to timely predict potential fault hazards, and may even lead to misjudgments and missed judgments, resulting in unsatisfactory network resource optimization results, seriously affecting overall network performance and resource utilization. Summary of the Invention

[0005] To solve existing technical problems, embodiments of the present invention provide a network resource optimization method, apparatus, system, computer equipment, and computer storage medium.

[0006] To achieve the above-mentioned purpose, the technical solution of the embodiment of the present invention is implemented as follows: In a first aspect, an embodiment of the present invention provides a network resource optimization method, the method comprising: obtaining physical network information, and generating a virtual network topology map based on the physical network information; wherein the virtual network topology map includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to connection relationships between network devices; and the weights represent indicator parameters of the links; Determine the shortest path information from a source node to each node in the virtual network topology graph; the source node is any node in the virtual network topology graph; Determine the first time period and the second time period included in the basic time period according to monitoring requirements and / or network traffic characteristics; monitoring a performance indicator of a first link within the basic time period, and performing fault detection on the first link based on the monitored performance indicator, the first time period, and the second time period to obtain a fault detection result; the first link being a link formed by two nodes included in the shortest path information; A virtual routing flow table is determined according to the fault detection result, and the virtual routing flow table is used to optimize the configuration of the network device and / or the connection between the network devices.

[0007] In the above scheme, the physical network information includes network devices in the physical entity network, the connection relationship between network devices, and the performance indicators corresponding to the connection between network devices; the generation of a virtual network topology diagram based on the physical network information includes: mapping the network devices in the physical network information into nodes, and mapping the connection relationship between network devices in the physical network information into links between nodes to generate an initial virtual network topology diagram; determining weights based on the performance indicators corresponding to the connections between network devices, mapping the weights to the links corresponding to the connections between the network devices, and generating the virtual network topology diagram.

[0008] In the above scheme, determining the shortest path information from the source node to each node in the virtual network topology graph includes: based on the virtual network topology graph, obtaining a first array and a second array corresponding to the source node and each node, and determining the shortest path information between the source node and each node based on the first array and the second array; wherein, the first array includes the shortest distance corresponding to the shortest path from the source node to each node, and the second array includes the predecessor node of each node on the shortest path; the shortest path satisfies the minimum link delay and / or the minimum bandwidth consumption, and the shortest distance represents the corresponding delay and / or bandwidth consumption of the shortest path.

[0009] In the above scheme, obtaining the first array and the second array corresponding to the source node and each node includes: initializing the first array, the second array and the first node set, the first node set including the visited nodes; selecting the first node from the second node set, and adding the first node to the first node set; wherein the second node set includes unvisited nodes, and the first node is the node closest to the source node; determining the second node among the adjacent nodes of the first node, and using the first node as the predecessor node of the second node; wherein the second node satisfies: the sum of the shortest distance between the first node and the source node and the weight between the first node and the second node is less than the shortest distance between the second node and the source node, and the second node does not belong to the first node set; based on the second node, updating the first array and the second array corresponding to the shortest path from the source node to the second node.

[0010] In the above scheme, the virtual network topology map also includes a first mark of the link where the fault occurs in the fault detection result, and / or a second mark of the node where the fault occurs; wherein the weight of the link associated with the first mark is the maximum value; the first mark and / or the second mark are used to update the first array and the second array.

[0011] In the above scheme, the first mark and / or the second mark are used to update the first array and the second array, including: determining the shortest path between the third node and the fourth node based on the nodes not associated with the second mark, the nodes corresponding to the links not associated with the first mark, and the links not associated with the first mark in the virtual network topology diagram; wherein the third node is the predecessor node of the node associated with the second mark, and the fourth node is the end node in the link associated with the first mark; based on the shortest path between the third node and the fourth node, updating the corresponding first array and second array, and deleting the first mark and / or the second mark.

[0012] In the above scheme, the performance indicators of the first link are monitored within the basic time period, and fault detection is performed on the first link based on the monitored performance indicators to obtain a fault detection result, including: obtaining a first performance indicator value of the first link at a first moment within the basic time period; obtaining a second performance indicator value of the first time period and a third performance indicator value of the second time period based on the first performance indicator value; judging whether a fault occurs in the first link within the basic time period based on the second performance indicator value and the third performance indicator value, and obtaining a fault monitoring result.

[0013] In the above scheme, the judgment of whether the first link fails within the basic time period based on the second performance indicator value and the third performance indicator value includes: when the third performance indicator value is greater than or equal to the first threshold and the second performance indicator value is less than the first threshold, determining that the first link fails, and / or determining that the predecessor node in the first link fails.

[0014] In the above solution, the performance indicators include one or more of the following: delay, packet loss rate, and bandwidth utilization.

[0015] In the above scheme, determining the virtual routing flow table based on the fault detection result includes: determining that there is no mark in the virtual network topology map, and obtaining the virtual routing flow table based on the first array and the second array corresponding to the shortest path from the updated source node to each node.

[0016] In a second aspect, an embodiment of the present invention further provides a network resource optimization device, the device comprising: a basic environment module, a multi-path redundancy module and a virtual verification module; wherein, The basic environment module is configured to obtain physical network information and generate a virtual network topology diagram based on the physical network information; wherein the virtual network topology diagram includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to connection relationships between network devices; and the weights represent indicator parameters of the links; The multi-path redundancy module is configured to determine the shortest path information from a source node to each node in the virtual network topology diagram; the source node is any node in the virtual network topology diagram; and is further configured to determine a virtual routing flow table based on the fault detection result, the virtual routing flow table being used to optimize the configuration of network devices and / or connections between network devices; The virtual verification module is used to determine the first time period and the second time period included in the basic time period based on monitoring requirements and / or network traffic characteristics; monitor the performance indicators of the first link within the basic time period, and perform fault detection on the first link based on the monitored performance indicators, the first time period and the second time period to obtain a fault detection result; the first link is a link formed by two nodes included in the shortest path information.

[0017] In a third aspect, an embodiment of the present invention further provides a network resource optimization system, the system comprising: a physical layer, a connection layer, a twin data layer, and an application service layer; wherein, The physical layer is used to provide physical network information, including network devices in the physical network, connection relationships between network devices, and performance indicators corresponding to connections between network devices; The connection layer is used to transmit the physical network information provided by the physical layer to the twin data layer; The twin data layer is used to generate a virtual network topology based on the physical network information, and determine the shortest path information from the source node to each node in the virtual network topology; wherein the virtual network topology includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to the connection relationships between network devices; the weights represent the index parameters of the links; the source node is any node in the virtual network topology; it is also used to determine the first time period and the second time period included in the basic time period according to monitoring requirements and / or network traffic characteristics; the performance indicators of the first link are monitored within the basic time period, and the first link is fault detected based on the monitored performance indicators, the first time period, and the second time period to obtain a fault detection result; the first link is a link formed by two nodes included in the shortest path information; a virtual routing flow table is determined based on the fault detection result, and the virtual routing flow table is mapped to physical network resource optimization information; The application service layer is used to send monitoring requirements to the twin data layer; it is also used to obtain physical network resource optimization information from the twin data layer, and optimize the configuration of network devices and / or connections between network devices according to the physical network resource optimization information to achieve business deployment.

[0018] In a fourth aspect, an embodiment of the present invention further provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of the embodiment of the present invention when executing the program.

[0019] In a fifth aspect, an embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method of the embodiment of the present invention when executed by a processor.

[0020] In a sixth aspect, an embodiment of the present invention further provides a computer program product, comprising a computer program, which implements the method of the embodiment of the present invention when executed by a processor.

[0021] The network resource optimization method, device, system, computer equipment and computer storage medium provided by the embodiments of the present invention generate a virtual network topology based on the acquired physical network information. The virtual network topology includes nodes corresponding to network devices in the physical network information and links corresponding to the connection relationships of the network devices. The first time period and the second time period in the basic time period are dynamically adjusted according to the detection requirements and / or network traffic characteristics. Based on the first time period, the second time period, and the performance indicators obtained by monitoring the first link in the basic time period, fault detection is performed on the shortest path information from the source node to each node in the determined virtual network topology, and a virtual routing flow table is determined based on the fault detection results. On the basis of using digital twin technology to realize virtual mapping of the physical network, by introducing a scalable time period fault detection mechanism, the time range of different stages in the basic time period is flexibly adjusted based on network traffic characteristics or requirements, thereby accurately capturing link performance mutations based on fault results, and responding quickly and accurately when a network link encounters a fault, realizing optimal configuration and efficient utilization of network resources, reducing misjudgments and missed judgments, improving network reliability and stability, and ensuring network service continuity, providing new ideas and methods for network resource optimization based on digital twin technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram of a network resource optimization system architecture according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the platform architecture of a digital twin network side according to an embodiment of the present invention; Figure 3 Schematic diagram of the process of the network resource optimization method according to the embodiment of the present invention Figure 1 ; Figure 4 Schematic diagram of the process of the network resource optimization method according to an embodiment of the present invention Figure 2 ; Figure 5 A flowchart of an example of a method for optimizing network resources according to an embodiment of the present invention; Figure 6 A schematic diagram of the structure of a network resource optimization device according to an embodiment of the present invention; Figure 7 A schematic diagram of the structure of a network resource optimization system according to an embodiment of the present invention; Figure 8 A schematic diagram of the structure and operation flow of a network resource optimization system according to an embodiment of the present invention; Figure 9 Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0024] It should be understood that in the embodiments of the present application, devices having communication functions in the network / system may be referred to as communication devices. Communication devices may include network devices and terminals having communication functions. The network devices and terminal devices may be the specific devices described above and will not be described in detail here. Communication devices may also include other devices in the communication system, such as network controllers, mobility management entities, and other network entities, which are not limited in the embodiments of the present invention.

[0025] It should be understood that the terms "system" and "network" are often used interchangeably herein. The term "and / or" is simply a description of an association between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " generally indicates that the related objects are in an "or" relationship.

[0026] The terms "first", "second" etc. in this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable in appropriate circumstances, so that the embodiments of the application described herein, for example, can be implemented in an order other than those illustrated or described herein. In addition, the terms "comprise" and "have" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, method, system, product or equipment comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or that are intrinsic to these processes, methods, products or equipment.

[0027] Before describing the access method according to the embodiment of the present invention in detail, the related technologies are briefly described first.

[0028] Traditional network resource optimization methods rely on experience and rules, such as through load balancing, resource scheduling, and performance optimization. However, due to the dynamic nature and complex demands of cloud networks, their elastically scalable network resources, multi-user nature, and complex interdependent services, these traditional network resource optimization methods struggle to quickly and accurately respond to resource changes, meet the needs of multiple users, and achieve global collaborative optimization. These limitations pose a significant challenge to network resource optimization, necessitating the urgent need for new, smarter, and more flexible optimization strategies and technologies to adapt to the evolving cloud network environment.

[0029] Digital twin technology is a technology that uses digital models to reflect or simulate real-world entities, systems, or processes. This digital model is a virtual replica that can fully and in real time simulate the state, behavior, and performance of the actual object or system. Digital twin technology integrates multiple advanced technologies, including the Internet of Things, big data analytics, cloud computing, and artificial intelligence. It offers features such as virtual-reality mapping, real-time monitoring, simulation prediction, optimized design, and continuous learning. As digital twin technology matures, it is now widely used in smart manufacturing, smart cities, transportation, healthcare, and other fields. It is a key technology for future intelligent upgrades and also provides new ideas and methods for optimizing cloud network resources.

[0030] Currently, existing methods for optimizing network resources based on digital twin technology include the following: The first method builds a data mirror model by integrating the general architecture of digital twins, hardware device groups and network data types, and adopts the virtual load data construction method. After parsing the network data, the key elements are packaged into event packages and filled, providing diverse samples and accurate basis for network resource optimization. The delay coefficient is calculated based on the network delay and the preset value, and the virtual routing table is adjusted according to the actual traffic demand value of the delay coefficient and the event package traffic value, thereby efficiently optimizing network communication, effectively supporting the optimization process, ensuring stable operation of the system, and enhancing network performance.

[0031] However, in the process of using the virtual load data construction method, the keyword preset and data filling methods may be inflexible, making it difficult to accurately simulate complex and changeable network scenarios, thereby affecting the universality and accuracy of the optimization solution, and having poor adaptability to extreme network conditions or new network conditions.

[0032] The second approach integrates digital twin technology with reinforcement learning algorithms to achieve network self-optimization in data centers. Specifically, this approach builds a system consisting of physical and digital twin network layers, collects physical network data to build foundational and functional models, and uses a Q-learning algorithm with the traffic matrix as the state, link weights as the action, and negative maximum link utilization as the reward function. Through multi-module interactive iterative training, the optimization strategy intelligently determines the path algorithm based on traffic volume during deployment. The strategy is then validated through digital twin network simulation to build a real-time mirror of the physical network, achieving precise control and optimization of the physical network. This effectively overcomes the training sample difficulties of traditional reinforcement learning algorithms and the adverse interference they cause to the physical network, giving the physical network simulation capabilities and improving network management and control.

[0033] However, this method has a complex system architecture, is difficult to develop and operate, and is costly. In addition, when responding to large-scale network dynamic changes, model updates are slow and algorithm adjustments lag, making it difficult to ensure the continuity and quality of network services. Moreover, the system architecture is tightly coupled and difficult to integrate with new network technologies, which hinders technological evolution and seriously affects the long-term optimization, upgrading, and sustainable development of cloud networks.

[0034] The third method applies digital twin technology to communication network fault analysis, adopts a unique fully closed test signal parameter processing, obtains the network structure distribution to construct a topological structure, builds a mirror digital model and integrates multi-cycle operation data to realize node data prediction, and optimizes the value of the constant coefficient based on the node historical data to improve the prediction accuracy. In the fault judgment link, based on the positive and negative characteristics of the operation data, the measured and predicted deviations are used as the core to construct detailed rules, accurately assess the node fault risk level, realize intelligent and accurate fault detection, improve the reliability and stability of the communication network, reduce the scope and duration of the fault impact, and provide strong support for communication network maintenance.

[0035] However, this method involves many process links, a high degree of technical integration, and a large demand for professional knowledge, from network topology construction to prediction model parameter determination and then to fault judgment rule design. This makes the implementation and operation of technical personnel too difficult and the cost investment too high.

[0036] The fourth method is to build a digital twin network, combine virtual communication equipment data processing and business intention deduction mechanism, and feed back the physical network after optimizing the network by changing equipment parameters and routing algorithms according to the model during the business deduction process. The digital twin network deploys communication elements and sets up middleware and probe software to achieve dynamic optimization of the network, improve operation and maintenance intelligence and risk prevention capabilities, thereby driving the optimization and upgrade of the communication network in all directions.

[0037] However, this method does not take into account network emergencies such as surges in network traffic, and does not have a preset emergency mechanism for traffic surges. This can easily cause delays in data processing and transmission, exacerbating network congestion and dramatically lengthening response time. It is difficult to predict potential faults in a timely manner, greatly affecting user experience, wasting network resources, and failing to effectively prevent them, making it impossible to guarantee network availability.

[0038] It can be seen that the current network resource optimization methods based on digital twin technology lack response strategies for network emergencies such as dynamic changes in network resources, surges in network traffic, and sudden changes in network link performance. This makes it difficult to timely predict potential fault hazards, and even leads to misjudgments and missed judgments, resulting in unsatisfactory network resource optimization results, seriously affecting overall network performance and resource utilization.

[0039] Based on this, the present invention proposes a user-oriented network resource optimization system architecture. This system architecture can be deployed in a cloud service network, specifically in a mobile cloud virtual network console. For example, based on user service needs, the specific process of optimizing the physical network resources using this network resource optimization system architecture is as follows: When the user's operations such as routing table selection, virtual private cloud routing table creation, and routing table selection subnet product are obtained when operating the mobile cloud virtual control service platform, the network resource optimization system will automatically start to execute the network resource optimization process deployed on the digital twin network side, and through the interface, the mechanism can be introduced to transmit the intelligent decision-making network resource information generated by the digital twin network side of the system to the cloud network server. The server issues instructions to pass the optimized decision information to the physical interface corresponding to the cloud network console, and realizes the intelligent optimization selection of routing table network resources on the page user side based on the cloud management control platform, and deploys the corresponding network resources in the user's own cloud product network environment.

[0040] Figure 1 FIG. 1 is a schematic diagram of a network resource optimization system architecture according to an embodiment of the present invention; FIG. Figure 1 As shown in the figure, the process of optimizing the resource configuration of the physical network based on the network resource optimization system architecture is as follows: First, in the early stage of network resource optimization, relevant information of each network device in the physical entity network is collected, such as the hardware information of each network element, traffic data information, connection relationship between each network element, etc., and the early physical network information is obtained through data information screening to realize the physical entity space of network connection and data traffic processing of each physical network element.

[0041] Secondly, the preliminary physical network information is uploaded through the IoT gateway and transmitted to the router connection point on the digital twin network side. The router then routes and forwards the information to the working platform on the virtual digital twin network side of the cloud server. After receiving the physical network information, the platform performs network function modeling and algorithm model calls. Based on the predicted traffic flow during the current scalable period, it performs fault detection and management on the network equipment in the current period, optimizes network resources, and obtains the updated network resource optimization configuration, namely the digital twin network side information.

[0042] Finally, in the later stage of network resource optimization, the working platform on the digital twin network side maps the digital twin network side information into the later mapped network resource information, and transmits the information to the router connection point of the cloud management and control platform. By promoting the bidirectional drive judgment of the model, the optimized network resource configuration (i.e., the later mapped network resource information) is distributed to the corresponding physical entity routing network, and sent to the physical entity network through the flow table to complete the established traffic work task forwarding and cloud service product facility configuration for multiple users.

[0043] Based on Figure 1 the network resource optimization system architecture shown, Figure 2 is a digital twin network side platform architecture schematic diagram of an embodiment of the application; as Figure 2 The digital twin network side platform architecture mainly includes four levels, from bottom to top, which are physical layer, connection layer, twin data layer and application service layer. The description of each level is as follows: The physical layer is deployed in the physical network element system environment of the real world. In the physical network element system environment, various hardware devices are used to realize control control, latest collection of related data, and storage of historical data. The physical layer is used to obtain the network connection conditions of each basic network element in the physical entity network and the identifiable traffic environment information in the physical world of each network element link.

[0044] The connection layer is a "bridge" for information interaction between the physical layer and the twin data layer. It can be deployed on the router connecting the physical entity network and the digital twin network. The physical network information collected by the physical layer is transmitted to the twin data layer through the routing request. The network resource optimization configuration generated by the twin data layer is transmitted to the physical layer through the flow table delivery, ensuring the information synchronization, consistency and integrity between the physical and virtual.

[0045] The twin data layer is in the core level in the digital twin network side platform architecture of the embodiment of the application. A plurality of sub-models based on digital twin technology are deployed, such as data mapping, data warehouse and service mapping model. Among them, the data mapping is used for virtual data mapping processing of the physical network information collected by the physical layer; the data warehouse has data collection, storage, management and service functions, and is mainly responsible for storing the virtual network data after mapping processing; the service mapping model includes a basic sub-model and a functional sub-model. The basic sub-model is mainly responsible for collecting and storing various network element data, and provides a variety of data services (such as network resource optimization, predictive fault diagnosis, predictive maintenance, etc.) and unified interfaces for the functional sub-model, models based on data, and provides data model examples of various network applications; the functional sub-model has the functions of maintaining, predicting, optimizing, managing and running data, mainly based on the data service interface provided by the basic sub-model, realizing the network resource optimization configuration of the virtual network data through the iterative optimization of algorithm, and realizing the simulation verification of the network resource optimization configuration through the steps of scalable time period prediction running verification, predictive fault diagnosis, etc. The functions of this level maximize the agility and programmability of network services, and realize higher level maintenance, optimization and reasonable intelligent optimization.

[0046] The application service layer is deployed in the cloud service network. It is mainly responsible for transmitting the acquired user business requirements to the twin data layer. After fully verifying the network optimization strategy, it optimizes the network resource configuration provided by the twin data layer to model business deployment.

[0047] In the embodiment of the present invention, the twin digital virtual routing table dynamic adjustment technology is used to design a four-layer architecture. The functional design of each layer is reasonable and the layers are closely coordinated. It fully supports cloud network resource optimization, from basic resources to business mapping applications, to achieve efficient interaction and intelligent control as well as real-time dynamic adjustment of routing strategies.

[0048] Based on the above-mentioned network resource optimization architecture and the platform architecture of the digital twin network side, an embodiment of the present invention proposes a network resource optimization method. Figure 3 Schematic diagram of the process of the network resource optimization method according to an embodiment of the present invention Figure 1 ;like Figure 3 As shown, the method includes: Step 101: Obtain physical network information and generate a virtual network topology based on the physical network information; wherein the virtual network topology includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to connection relationships between network devices; and the weights represent indicator parameters of the links; Step 102: Determine the shortest path information from the source node to each node in the virtual network topology graph; the source node is any node in the virtual network topology graph; Step 103: Determine a first time period and a second time period included in the basic time period according to monitoring requirements and / or network traffic characteristics; Step 104: Monitor the performance indicator of the first link during the basic time period, perform fault detection on the first link based on the monitored performance indicator, the first time period, and the second time period, and obtain a fault detection result; the first link is a link formed by the two nodes included in the shortest path information; Step 105: Determine a virtual routing flow table according to the fault detection result, where the virtual routing flow table is used to optimize the configuration of the network device and / or the connection between the network devices.

[0049] In this embodiment, physical network information related to the actual physical network is obtained, twin processing is performed on the physical network information, and a virtual network topology corresponding to the physical network is generated.

[0050] Among them, physical network information is information collected based on the physical network element system environment in the real world, including various information such as real-time collected network information and / or stored historical data, and can also include network information filtered based on user business needs.

[0051] The virtual network topology corresponds to the actual physical network, specifically including multiple nodes, links between nodes, and weights corresponding to each link; each node in the virtual network topology corresponds to a network device in the physical network information; the links between nodes correspond to the connection relationships between network devices in the actual physical network; weights are used to represent the indicator parameters of the link, which are specifically determined based on the link's delay and / or bandwidth consumption measurement indicators.

[0052] In this embodiment, after obtaining the virtual network topology corresponding to the physical network information, the shortest path information from the source node to each node in the virtual network topology is determined to provide data information for the subsequent construction of the virtual routing flow table, thereby effectively guiding the efficient transmission of data in the network.

[0053] The source node may be any node in the virtual network topology diagram, or a node in the virtual network topology diagram may be determined as the source node based on the acquired business needs of the user.

[0054] In this embodiment, after obtaining the shortest path information from the source node to each node in the virtual network topology diagram, the first time period and the second time period included in the basic time period are dynamically adjusted according to the monitoring requirements and / or network traffic characteristics to facilitate subsequent fault detection of the shortest path information.

[0055] Among them, monitoring demand refers to the traffic demand monitored in real time or the predicted traffic demand value. The embodiment of the present invention does not impose any specific restrictions on the method of monitoring traffic demand or predicting traffic demand value; network traffic characteristics refer to the traffic fluctuation of the network, such as the large fluctuation of network traffic caused by a surge or drop in network traffic, or the small fluctuation of network traffic caused by a low network traffic demand.

[0056] The first time period refers to the first time period in the basic time period, and the second time period refers to the second time period in the basic time period. The first time period and the second time period dynamically constitute a complete basic time period, that is, the basic time period is divided into the first time period and the second time period.

[0057] For example, Is the length of the basic time period, in the basic time period Define the first time period (i.e. the first time period) based on and the second time period (i.e., the later time period) , forming a scalable time period, which can be flexibly adjusted according to monitoring requirements and / or network traffic characteristics and , satisfy .

[0058] It should be noted that when it is determined that the network traffic fluctuation is large, the link at the latest time in the basic time period needs to be detected, and therefore the adjustment made to the first time period and the second time period is to shorten the first time period and lengthen the second time period, so as to more accurately capture the link performance change trend; when it is determined that the network traffic fluctuation is small, the detection results of the front time period and the rear time period are relatively close, and there is no need to detect the link at the latest time, and therefore the adjustment made to the first time period and the second time period is to lengthen the first time period and shorten the second time period, so as to obtain the stable situation of the link performance.

[0059] In the embodiment, after the first time period and the second time period in the basic time period are determined, the performance indicators of the first link formed by the two nodes contained in the shortest path information are monitored in the basic time period, the first link is detected based on the monitored performance indicators, the first time period and the second time period, the fault link and / or the fault node in the shortest path are determined, and the corresponding fault detection result is obtained.

[0060] It should be noted that since the failure of the node in the shortest path will cause the link composed of the node and the subsequent node to fail, when the fault node in the shortest path is determined, it can be further determined that the link with the fault node as the starting node fails, that is, the fault link in the shortest path is determined. That is to say, the fault detection result corresponding to the fault link in the embodiment of the application is similar to the fault detection result corresponding to the fault node.

[0061] In the embodiment, after the fault detection result is obtained, the virtual routing flow table is determined according to the fault detection result, the network device and / or the connection relationship between the network devices are optimized based on the virtual routing flow table, and therefore the optimization configuration of the physical network resource is realized.

[0062] In an embodiment of the present invention, a virtual network topology is generated based on the acquired physical network information, the first time period and the second time period in the basic time period are dynamically adjusted according to the detection requirements and / or network traffic characteristics, and based on the first time period, the second time period, and the performance indicators obtained by monitoring the first link in the basic time period, fault detection is performed on the shortest path information from the source node to each node in the determined virtual network topology, and a virtual routing flow table is determined based on the fault detection results. On the basis of using digital twin technology to achieve virtual mapping of the physical network, by introducing a scalable time period fault detection mechanism, the time range of different stages in the basic time period is flexibly adjusted based on network traffic characteristics or requirements, thereby accurately capturing link performance mutations based on fault results, and responding quickly and accurately when a network link encounters a fault, achieving optimal configuration and efficient utilization of network resources, reducing misjudgments and missed judgments, improving network reliability and stability, and ensuring network service continuity.

[0063] In some optional embodiments, the physical network information includes network devices in the physical entity network, connection relationships between network devices, and performance indicators corresponding to the connections between network devices; generating a virtual network topology map based on the physical network information includes: mapping the network devices in the physical network information into nodes, and mapping the connection relationships between network devices in the physical network information into links between nodes to generate an initial virtual network topology map; determining weights based on the performance indicators corresponding to the connections between network devices, mapping the weights to links corresponding to the connections between the network devices, and generating the virtual network topology map.

[0064] In this embodiment, the physical network information includes network devices (such as routers) in the physical entity network (such as a cloud server network), the connection relationship between network devices, and the performance indicators corresponding to the connections between network devices. The performance indicators include indicators such as delay and bandwidth consumption between network devices.

[0065] For example, the process of generating the network topology corresponding to the physical network is as follows: mapping the network devices in the physical network information into nodes to obtain the total node set V , the total number of nodes ; Map the connection relationship between network devices in the physical network information into links between nodes to obtain a link set E ; According to the performance indicators corresponding to the connection between network devices, for each link between two nodes with a connection relationship Assign a corresponding weight , mapping the weights to the links corresponding to the connection relationships between network devices, thereby obtaining a virtual network topology graph including all nodes and all links G ( V,EIt should be noted that the embodiment of the present invention does not impose any specific limitation on the method of determining the weight corresponding to the link according to the performance indicator.

[0066] In some optional embodiments, determining the shortest path information from the source node to each node in the virtual network topology graph includes: based on the virtual network topology graph, obtaining a first array and a second array corresponding to the source node and each node, and determining the shortest path information between the source node and each node based on the first array and the second array; wherein, the first array includes the shortest distance corresponding to the shortest path from the source node to each node, and the second array includes the predecessor node of each node on the shortest path; the shortest path satisfies the minimum link delay and / or the minimum bandwidth consumption, and the shortest distance represents the corresponding delay and / or bandwidth consumption of the shortest path.

[0067] In this embodiment, the process of determining the shortest path information from the source node to each node in the virtual network topology graph is to obtain the first array and the second array corresponding to the links between the source node and each node in the virtual network topology graph, and determine the shortest path information between the source node and each node based on the first array and the second array.

[0068] Among them, the first array is a distance array, specifically including the shortest distance corresponding to the shortest path from the source node to each node in the virtual network topology diagram. Each shortest path corresponds to a first array. The distance in this embodiment represents the delay and / or bandwidth consumption of the path, that is, the shortest path refers to the link with the lowest delay and / or the least bandwidth consumption between the source node and each node.

[0069] The second array is a predecessor node array, specifically including the predecessor node of each node on the shortest path, that is, the previous node of each node on the shortest path. The embodiment of the present invention does not impose any specific restrictions on the storage method of the second array, and each shortest path corresponds to a set of predecessor node sequences.

[0070] Figure 4 Schematic diagram of the process of the network resource optimization method according to an embodiment of the present invention Figure 2 ;like Figure 4 As shown, the method of obtaining the first array and the second array corresponding to the source node and each node includes: Step 201: Initialize a first array, a second array, and a first node set, where the first node set includes visited nodes.

[0071] In this embodiment, in the process of obtaining the first array and the second array corresponding to the source node and each node, it is necessary to first initialize the data structure, specifically including initializing the first array, the second array and the first node set including the visited nodes.

[0072] For example, initialize the source node to each node ( V The first array corresponding to the total node set) D , set the source node The corresponding first array , set up other nodes The corresponding first array .

[0073] Initialize the source node to the second array corresponding to each node P , except the source node s In addition, other nodes v The corresponding second array is empty ( Null ).

[0074] Initialize the first node set S An empty set, indicating that there are currently no visited nodes.

[0075] Step 202: Select a first node from a second node set, and add the first node to the first node set; wherein the second node set includes unvisited nodes, and the first node is the node closest to the source node.

[0076] In this embodiment, after completing the initialization of the first array, the second array and the first node set, if there is a node in the second node set including the unvisited nodes, the first node closest to the source node is selected from the second node set and the first node is added to the first node set.

[0077] For example, when the second node set I= ( VS ) has unvisited nodes (ie, the total node set V The first node set S The number of nodes in is not equal to the total number of nodes ), select a node from the second set u , making , that is, select a node u , so that the node u Compared to other currently unvisited nodes and the source node s The distance is the shortest, the node u Add to the first node set S In, that is .

[0078] Step 203: Determine a second node among the adjacent nodes of the first node, and use the first node as the predecessor node of the second node; wherein, the second node satisfies: the sum of the shortest distance between the first node and the source node and the weight between the first node and the second node is less than the shortest distance between the second node and the source node, and the second node does not belong to the first node set.

[0079] In this embodiment, after the first node is selected, the second node is selected from all adjacent nodes of the first node in the second set as the next node of the first node, that is, the first node is used as the predecessor node of the second node.

[0080] Specifically, the second node is determined by calculating the sum of the shortest distance between the first node and the source node and the weights between the first node and each adjacent node. When it is determined that the value of the above sum is less than the shortest distance between the adjacent node and the source node, and the adjacent node is not in the first node set, the adjacent node is determined to be the second node.

[0081] For example, for the first node u Each adjacent node ,like ,and , that is, the first node u and source node s The shortest distance between D [ u ] and the first node s and each adjacent node v The weight between Less than the shortest distance between the adjacent node and the source node D [ v ], then the adjacent node v As the second node, the first node u As the second node v The predecessor node.

[0082] Step 204: Update the first array and the second array corresponding to the shortest path from the source node to the second node based on the second node.

[0083] In this embodiment, after the second node is determined, the shortest path between the source node and the second node is determined, and the first array and the second array corresponding to the shortest path from the source node to the second node are updated.

[0084] For example, based on the source node s To the first node u The shortest distance D[u] , and the first node to the second node v Weight , update the first array corresponding to the shortest path from the source node to the second node to , the first node u and source node s The shortest distance between D [ u ] and the first node s and each adjacent node v The weight between The sum of the adjacent nodes is updated to the shortest distance between the source node and the adjacent node. D [ v ], based on the second array corresponding to the shortest path from the source node to the first node, the first node is used as the predecessor node of the second node , added to the second array corresponding to the shortest path from the source node to the first node, thereby updating the second array corresponding to the shortest path from the source node to the second node.

[0085] It should be noted that the embodiment of the present invention uses the Dijkstra algorithm to repeatedly perform algorithm iteration processing from step 201 to step 204 from the source node to each node, thereby obtaining the first array and the second array corresponding to the shortest path between the source node and each node.

[0086] In this embodiment, by running the algorithm of steps 201 to 204 above, the algorithm parameters are optimized according to the virtual network topology map after virtual mapping, the link weight is adjusted according to the link evaluation index to calculate the shortest path, and the algorithm model is optimized based on the execution result of the algorithm to achieve dynamic bidirectional optimization, thereby improving network resources and dynamically adjusting the network status to maintain the optimal operating state.

[0087] In some optional embodiments, the virtual network topology map also includes a first mark of the failed link in the fault detection result, and / or a second mark of the failed node; wherein the weight of the link associated with the first mark is the maximum value; the first mark and / or the second mark are used to update the first array and the second array.

[0088] In this embodiment, after determining the first array and the second array corresponding to the shortest path from the source node to each node, fault detection is performed on the shortest path. After obtaining the corresponding fault detection result, the faulty link and / or faulty node determined in the fault detection result is marked, so that the virtual network topology diagram includes the first mark of the faulty link in the fault detection result and / or the second mark of the faulty node.

[0089] Among them, the first mark and / or the second mark indicates that the current link and / or node is in a pending update state, that is, the first mark and / or the second mark are used to update the first array and the second array corresponding to the shortest path related to the marked link and / or node. Since a faulty link and / or faulty node appears in the virtual network topology, the weight of the faulty link needs to be adjusted to the maximum value. .

[0090] It should be noted that, for multiple shortest paths, when a faulty node and / or faulty link in one of the shortest paths is determined, information related to the faulty node and / or faulty link in the first array and the second array corresponding to the other shortest paths will be marked.

[0091] In some optional embodiments, the first mark and / or the second mark are used to update the first array and the second array, including: determining the shortest path between the third node and the fourth node based on the nodes not associated with the second mark, the nodes corresponding to the links not associated with the first mark, and the links not associated with the first mark in the virtual network topology diagram; wherein the third node is the predecessor node of the node associated with the second mark, and the fourth node is the end node in the link associated with the first mark; based on the shortest path between the third node and the fourth node, updating the corresponding first array and second array, and deleting the first mark and / or the second mark.

[0092] In this embodiment, the process of updating the first array and the second array corresponding to the shortest paths related to the marked links and / or nodes is to determine the nodes that are not associated with the second mark, the nodes corresponding to the links that are not associated with the first mark, and the links that are not associated with the first mark in the virtual network topology map, that is, to determine all nodes in the virtual network topology map except the faulty nodes and / or nodes corresponding to the faulty links, and all links in each shortest path except the faulty links, and determine the shortest path between the third node and the fourth node based on the above nodes and links.

[0093] The third node represents the predecessor node of the node corresponding to the second label of the faulty node, and the fourth node represents the last node in the first label of the faulty link.

[0094] For example, the source node s To the end node k The shortest path between e =( s , k ), that is, the complete link is ( s,..., h,i,j,...k ) in the first marked fault link , and the second marked faulty node iFor example, the third node is a faulty node i Predecessor node h , the fourth node is the faulty link The end node of j , remove nodes from the virtual network topology i and nodes j The nodes outside are regarded as nodes not associated with the second mark and nodes corresponding to links not associated with the first mark, and the corresponding node set is obtained. Eliminate faulty links External links (i.e. and ) as a link not associated with the first tag, obtain the corresponding link set, and determine the link based on the above node set and link set The shortest path.

[0095] It should be noted that after the third node and the fourth node are determined, the shortest path between the third node and the fourth node may be determined by repeatedly iteratively executing steps 201 to 204 .

[0096] In this embodiment, after determining the shortest path between the third node and the fourth node, the corresponding first array and second array are updated based on the shortest path, including information related to the current faulty node and / or faulty link in the first array and second array corresponding to other shortest paths, and the corresponding first mark and / or second mark are deleted after the update is completed.

[0097] In some optional embodiments, the performance indicators of the first link are monitored within the basic time period, and fault detection is performed on the first link based on the monitored performance indicators to obtain a fault detection result, including: obtaining a first performance indicator value of the first link at a first moment within the basic time period; obtaining a second performance indicator value of the first time period and a third performance indicator value of the second time period based on the first performance indicator value; judging whether a fault occurs in the first link within the basic time period based on the second performance indicator value and the third performance indicator value, and obtaining a fault monitoring result.

[0098] In this embodiment, the process of obtaining a fault detection result by performing fault detection on the first link within the basic time period is as follows: monitoring the performance indicator of the first link at the first moment within the basic time period to obtain a first performance indicator value at the first moment; predicting the performance indicator values ​​of the first time period and the second time period based on the first performance indicator value to obtain corresponding second performance indicator values ​​and third performance indicator values; and judging whether a fault occurs in the first link within the basic time period based on the second performance indicator value and the third performance indicator value, thereby obtaining a fault detection result.

[0099] For example, by link e= ( i,j ) in the basic time period The first moment inside t Monitor the performance indicators and obtain the corresponding first performance indicators , use the differential method to predict the first time period The average performance index value is obtained to obtain the second performance index value. The prediction method of the second performance index value is designed as the following formula: (1) in, i and j They represent the preceding node and the last node in the link of the current fault detection respectively; T is the maximum moment of the basic time period; Indicates the first time period, that is, the first time period set in the basic time period.

[0100] As shown in formula (1), the first performance index is described by differentiation from Time to t Time (i.e. in the first time period The linear change of the first time period is divided by , and obtain the average performance index value of the previous time period in the basic time period, that is, the second performance index value.

[0101] At the same time, the second time period is predicted by differentiation The average performance index value of the third performance index value is obtained, and the prediction method of the third performance index value is designed as the following formula: (2) in, i and j They represent the preceding node and the last node in the link of the current fault detection respectively; T As the basic time period The biggest moment; t is the first moment in the base time period; Indicates the first time period, that is, the basic time period The previous time period set in ; Indicates the second time period, namely the basic time period The post-time period set in .

[0102] As shown in formula (2), the first performance index is described by differentiation from Time to Time (i.e. in the second time period The linear change of the second time period is divided by , and obtain the average performance index value of the latter time period in the basic time period, that is, the third performance index value.

[0103] In some optional embodiments, determining whether the first link fails within the basic time period based on the second performance indicator value and the third performance indicator value includes: when the third performance indicator value is greater than or equal to a first threshold and the second performance indicator value is less than the first threshold, determining that the first link fails, and / or determining that a predecessor node in the first link fails.

[0104] In this embodiment, after predicting the performance indicator values ​​of the first link in the first time period and the second time period within the basic time period, the second performance indicator value and the third performance indicator value are respectively compared with the preset first threshold value. When the third performance indicator value is greater than or equal to the first threshold value and the second performance indicator value is less than the first threshold value, it is determined that the first link has failed, and / or it is determined that the predecessor node in the first link has failed, and the specific cause of the failure is related to the monitored performance indicator.

[0105] For example, for the link e= ( i,j ), with a preset first threshold For example, based on the above formulas (1) and (2), the conditions for determining whether a link and / or node fails in the basic time period can be designed as follows: ,and (3) in, i and j They represent the preceding node and the last node in the link of the current fault detection respectively; T As the basic time period The biggest moment; t is the first moment in the base time period; Indicates the first time period, that is, the basic time period The previous time period set in ; Indicates the second time period, namely the basic time period The post-time period set in ; represents the first performance indicator; is the preset first threshold.

[0106] As shown in formula (3), when it is determined that the third performance indicator value is greater than or equal to the first threshold and the second performance indicator value is less than the first threshold, the link is determined to be e= ( i,j ) fails, and / or, determines the node i A malfunction occurred.

[0107] In some optional implementations, the performance indicator includes one or more of the following: delay, packet loss rate, and bandwidth utilization.

[0108] In this embodiment, the performance indicator of the first link monitored includes one or more indicators of delay, packet loss rate, and bandwidth utilization. In other words, the first performance indicator value of the first link monitored at the first moment in the scalable basic time period includes one or more indicators of delay, packet loss rate, and bandwidth utilization.

[0109] Correspondingly, the second performance indicator value corresponding to the first time period predicted based on the first performance indicator value, and the third performance indicator value corresponding to the second time period, also include one or more of delay, packet loss rate and bandwidth utilization.

[0110] It should be noted that the present invention does not impose any specific limitation on the method of obtaining the delay amount, packet loss rate and bandwidth utilization at the first moment in the basic time period.

[0111] For example, the first performance indicator value Specifically, it may include performance indicator values ​​representing delay time (i.e., delay amount) , which represents the performance indicator value of packet loss rate , which represents the performance indicator value of bandwidth utilization One or more of .

[0112] Accordingly, when determining whether a link failure and / or node failure has occurred on the shortest path based on the second and third performance indicator values, the judgment conditions used include one or more rules related to one or more of delay, packet loss rate, and bandwidth utilization, and the corresponding first threshold is related to one or more of delay, packet loss rate, and bandwidth utilization. In other words, if one or more of the judgment conditions are met, it can be determined that a link failure and / or node failure has occurred on the shortest path.

[0113] For example, taking the above formula (3) as an example, the first threshold value set may include a delay threshold value , Packet loss rate threshold and bandwidth utilization thresholds , the judgment conditions may include one or more of the following rules: ,and (4) ,and (5) ,and (6) Among them, among them, i andj They represent the preceding node and the last node in the link of the current fault detection respectively; T As the basic time period The biggest moment; t As the basic time period The first moment in Indicates the first time period, that is, the basic time period The previous time period set in ; Indicates the second time period, namely the basic time period The post-time period set in ; representing a first performance indicator related to delay amount; represents the first performance indicator related to packet loss rate; Indicates the first performance indicator related to bandwidth utilization.

[0114] Based on formula (4), when the second performance indicator value representing the average delay amount of the previous time period is determined to be less than the delay amount threshold , and the third performance indicator value representing the average delay amount in the later time period is greater than or equal to the delay amount threshold In the case of e= ( i,j ) a delayed failure occurs, and / or, determine the node i A delayed failure occurred.

[0115] Based on formula (5), when the second performance indicator value representing the average packet loss rate of the previous time period is judged to be less than the packet loss rate threshold , and the third performance indicator value representing the average packet loss rate in the later time period is greater than or equal to the packet loss rate threshold In the case of e= ( i,j ) packet loss failure occurs, and / or, determine the node i A packet loss failure occurred.

[0116] Based on formula (6), when the second performance indicator value representing the average bandwidth utilization of the previous time period is determined to be less than the bandwidth utilization threshold , and the third performance indicator value representing the average bandwidth utilization in the later time period is greater than or equal to the bandwidth utilization threshold In the case of e= ( i,j ) bandwidth utilization failure, and / or, determine the node i A bandwidth utilization failure occurred.

[0117] This embodiment introduces a scalable fault diagnosis mechanism, monitors performance indicators based on the time range before and after dynamic network adjustments, and uses preset thresholds to determine fault types. This accurately captures sudden changes in link performance and reduces false positives and missed detections. Compared to fixed thresholds or other simple monitoring methods, this method can accurately locate faults under complex network fluctuations, such as accurately identifying faulty links during network traffic peaks. This allows for faster repairs, improves network reliability and stability, ensures network service continuity, effectively reduces false positives and missed detections, and improves the accuracy and timeliness of fault detection.

[0118] In some optional embodiments, determining the virtual routing flow table based on the fault detection result includes: when there is no mark in the virtual network topology map, obtaining the virtual routing flow table based on the first array and the second array corresponding to the shortest path from the updated source node to each node.

[0119] In this embodiment, after completing fault detection on the shortest link between the source node and each node in the virtual network topology graph, information of the marked faulty link and / or faulty node in the fault detection result is updated. By searching whether the first mark and / or the second mark exist in the first array and the second array corresponding to the shortest link between the source node and each node in the virtual network topology graph, if it is determined that the mark still exists in the virtual network topology graph, the corresponding first array and the second array are updated for the marked link and / or node until it is determined that there is no mark in the virtual network topology graph. When it is determined that there is no mark in the virtual network topology diagram, the virtual link verification is determined to be successful. According to the first array and the second array corresponding to the updated shortest path from the source node to each node, the updated virtual routing flow table is output. Subsequently, the updated routing flow table data will be sent to the actual cloud service network side through virtual mapping to realize the status update of the connection relationship between physical entity network elements and network elements. The data is updated in real time with the service platform side, and the intelligently optimized information is updated for user use and the task node is generated.

[0120] In this embodiment, routing is adjusted through feedback from a fault detection mechanism, marking faulty links and / or faulty nodes to update node information and obtain an updated virtual routing flow table. This mechanism ensures network connectivity and data transmission reliability. In complex scenarios with multiple link failures, routing is quickly adjusted to avoid faulty links and / or faulty nodes, balancing network load, maintaining network stability, minimizing the impact of failures on network services, reducing operation and maintenance costs and service interruption losses, and improving overall network resilience and service quality.

[0121] As an example, Figure 5 FIG. 1 is a flow chart of an example of a method for optimizing network resources according to an embodiment of the present invention; FIG. Figure 5As shown in the figure, the specific process of achieving network resource optimization is as follows: Step 301: Obtain physical network information.

[0122] Specifically, by collecting data from the real-world physical network element system environment, we obtain physical network information related to the actual physical network. This physical network information includes the network devices in the physical network, the connections between network devices, and the performance indicators corresponding to the connections between network devices. Performance indicators include latency between network devices, bandwidth consumption, and other indicators.

[0123] Step 302: Generate a virtual network topology map based on the physical network information.

[0124] Specifically, the physical network information is virtually mapped, the network devices in the physical network information are mapped to nodes to obtain a node set, the connection relationship between the network devices in the physical network information is mapped to links between the nodes to obtain a link set, and according to the performance indicators corresponding to the connection between the network devices, a corresponding weight is assigned to each link between two nodes with a connection relationship, and the weight is mapped to the link corresponding to the connection relationship between the network devices, thereby obtaining a virtual network topology diagram including all nodes and all links.

[0125] Step 303: Determine the shortest path information from the source node to each node in the virtual network topology graph.

[0126] Specifically, initialize the first array, the second array and the first node set including visited nodes, select the first node closest to the source node from the second node set including unvisited nodes, add the first node to the first node set including visited nodes, determine the second node among the adjacent nodes of the first node, so that the second node satisfies: the sum of the shortest distance between the first node and the source node and the weight between the first node and the second node is less than the shortest distance between the second node and the source node, and the second node does not belong to the first node set, use the first node as the predecessor node of the second node, and update the first array and second array corresponding to the shortest path from the source node to the second node based on the second node.

[0127] Step 304: Determine a first time period and a second time period in the basic time period, monitor the performance indicator of the first link at the first moment in the basic time period, and predict a second performance indicator value corresponding to the first time period and a third performance indicator value corresponding to the second time period based on the obtained first performance indicator value.

[0128] Specifically, the first time period and the second time period included in the basic time period are dynamically adjusted according to monitoring requirements and / or network traffic characteristics. By monitoring the performance indicators of the first link at the first moment in the basic time period, the first performance indicator value at the first moment is obtained. Based on the first performance indicator value, the performance indicator values ​​of the first time period and the second time period are predicted respectively to obtain corresponding second performance indicator values ​​and third performance indicator values.

[0129] The first performance indicator value of the first link monitored at the first moment in the scalable basic time period includes one or more of delay, packet loss rate, and bandwidth utilization. Accordingly, the second performance indicator value corresponding to the first time period and the third performance indicator value corresponding to the second time period predicted based on the first performance indicator value also include one or more of delay, packet loss rate, and bandwidth utilization.

[0130] Step 305: Based on the second performance indicator value and the third performance indicator value, determine whether a fault occurs on the shortest path.

[0131] Specifically, when the second performance indicator value is less than the preset first threshold and the third performance indicator value is greater than or equal to the preset first threshold, it is determined whether there is a link failure and / or node failure in the first link within the basic time period, thereby obtaining a fault detection result.

[0132] Among them, the judgment conditions used in the fault detection process include one or more rules related to one or more of the delay amount, packet loss rate and bandwidth utilization, and the corresponding first threshold is related to one or more of the delay amount, packet loss rate and bandwidth utilization. When one or more of the judgment conditions are met, it can be determined that a link failure and / or node failure has occurred in the shortest path.

[0133] Step 306: Mark the fault according to the fault detection result.

[0134] Specifically, when a fault detection result is obtained indicating that the current shortest path contains a faulty link and / or a faulty node, the faulty link and / or the faulty node determined in the fault detection result are marked so that the virtual network topology diagram includes a first mark of the faulty link in the fault detection result, and / or a second mark of the faulty node. By repeatedly executing steps 303 to 305, the shortest path of the faulty link is re-determined, and the first array and the second array corresponding to the shortest path related to the marked link and / or node are updated according to the re-determined shortest path, and the corresponding first mark and / or second mark are deleted.

[0135] Step 307: Determine whether the current shortest path has a fault.

[0136] Specifically, by querying whether there is a flag to be updated in the current shortest path, it is determined whether there is a faulty link and / or a faulty node in the current shortest path.

[0137] If there are still markers to be updated on the current path, the shortest path of the faulty link is re-determined by repeating steps 303 to 306. The first array and the second array corresponding to the shortest paths associated with the marked links and / or nodes are updated based on the re-determined shortest path, and the corresponding first markers and / or second markers are deleted.

[0138] Step 308: Determine the first array and the second array corresponding to the current path information.

[0139] Specifically, when it is determined that the current shortest path has no flag to be updated, the first array and the second array corresponding to the updated current shortest path are stored.

[0140] Step 309: Check whether there is a fault flag.

[0141] Specifically, check whether there are marks to be updated in the shortest paths between the source node and each node in the virtual network topology map. If there are still marks to be updated in the virtual network topology map, redetermine the shortest path of the faulty link by repeating steps 303 to 308, and update the first array and the second array corresponding to the shortest paths related to the marked links and / or nodes according to the redetermined shortest path, and delete the corresponding first mark and / or second mark.

[0142] Step 310: Determine a virtual routing flow table.

[0143] Specifically, when it is determined that there is no mark in the virtual network topology map, the virtual link verification is determined to be successful, and the updated virtual routing flow table is output according to the first array and the second array corresponding to the updated shortest path from the source node to each node.

[0144] In an embodiment of the present invention, the Dijkstra algorithm is organically integrated with the fault detection feedback mechanism, and the judgment logic of the scalable time period is introduced, providing a new idea and method for network link fault judgment and network resource optimization. Through the digital twin fine-grained modeling of the network topology structure, the efficient execution of the Dijkstra algorithm, the accurate fault detection based on the scalable time period, and the intelligent routing adjustment after the fault feedback, the method can timely update the virtual routing flow table when the network link encounters a fault, and respond quickly and accurately, so that the network can cleverly bypass the faulty link or faulty node for data transmission, thereby ensuring the connectivity of the network and the reliability and efficiency of data transmission, realizing the optimal configuration and efficient utilization of network resources, and significantly improving the overall performance and fault tolerance of the network.

[0145] In addition, since the virtual digital twin space and the physical space interact continuously during the network resource optimization process, it is necessary to adopt technologies such as cloud computing that have efficient data interaction capabilities, real-time transmission capabilities, as well as excellent computing performance and decision-making modules that can process large amounts of data in the virtual digital twin space. Only in this way can the simulation effect be more in line with actual application scenarios, so as to achieve real-time response of virtual and real spaces and dynamic data feedback.

[0146] Therefore, the network resource optimization method provided by the embodiment of the present invention has extremely broad application prospects in diversified network environments such as cloud computing networks and enterprise internal networks, and is of great significance for ensuring the stability and continuity of network services and meeting the growing network communication needs.

[0147] Based on the above embodiments, the present invention further provides a network resource optimization device. Figure 6 FIG. 1 is a schematic diagram showing the structure of a network resource optimization device according to an embodiment of the present invention; FIG. Figure 6 As shown, the device includes: a basic environment module 41, a multi-path redundancy module 42 and a virtual verification module 43; wherein, The basic environment module 41 is configured to obtain physical network information and generate a virtual network topology based on the physical network information; wherein the virtual network topology includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to connection relationships between network devices; and the weights represent indicator parameters of the links; The multi-path redundancy module 42 is configured to determine the shortest path information from a source node to each node in the virtual network topology; the source node is any node in the virtual network topology; and is further configured to determine a virtual routing flow table based on the fault detection result, the virtual routing flow table being used to optimize the configuration of network devices and / or connections between network devices; The virtual verification module 43 is used to determine the first time period and the second time period included in the basic time period according to monitoring requirements and / or network traffic characteristics; monitor the performance indicators of the first link within the basic time period, and perform fault detection on the first link based on the monitored performance indicators, the first time period and the second time period to obtain a fault detection result; the first link is a link formed by two nodes included in the shortest path information.

[0148] In an optional embodiment of the present invention, the physical network information includes network devices in the physical entity network, connection relationships between network devices, and performance indicators corresponding to the connections between network devices; the basic environment module 41 is used to map the network devices in the physical network information into nodes, and map the connection relationships between network devices in the physical network information into links between nodes to generate an initial virtual network topology diagram; determine weights based on the performance indicators corresponding to the connections between network devices, map the weights to links corresponding to the connections between the network devices, and generate the virtual network topology diagram.

[0149] In an optional embodiment of the present invention, the multi-path redundancy module 42 is used to obtain a first array and a second array corresponding to the source node and each node based on the virtual network topology diagram, and determine the shortest path information between the source node and each node based on the first array and the second array; wherein the first array includes the shortest distance corresponding to the shortest path from the source node to each node, and the second array includes the predecessor node of each node on the shortest path; the shortest path satisfies the minimum link delay and / or the minimum bandwidth consumption, and the shortest distance represents the corresponding delay and / or bandwidth consumption of the shortest path.

[0150] In an optional embodiment of the present invention, the multi-path redundancy module 42 is used to initialize a first array, a second array and a first node set, wherein the first node set includes visited nodes; select a first node from the second node set, and add the first node to the first node set; wherein the second node set includes unvisited nodes, and the first node is the node closest to the source node; determine a second node among the adjacent nodes of the first node, and use the first node as the predecessor node of the second node; wherein the second node satisfies: the sum of the shortest distance between the first node and the source node and the weight between the first node and the second node is less than the shortest distance between the second node and the source node, and the second node does not belong to the first node set; based on the second node, the first array and the second array corresponding to the shortest path from the source node to the second node are updated.

[0151] In an optional embodiment of the present invention, the virtual network topology map also includes a first mark of the link where the fault occurs in the fault detection result, and / or a second mark of the node where the fault occurs; wherein the weight of the link associated with the first mark is the maximum value; the first mark and / or the second mark are used to update the first array and the second array.

[0152] In an optional embodiment of the present invention, the multipath redundancy module 42 is used to determine the shortest path between a third node and a fourth node based on the nodes not associated with the second mark, the nodes corresponding to the links not associated with the first mark, and the links not associated with the first mark in the virtual network topology diagram; wherein the third node is the predecessor node of the node associated with the second mark, and the fourth node is the end node in the link associated with the first mark; based on the shortest path between the third node and the fourth node, the corresponding first array and second array are updated, and the first mark and / or the second mark are deleted.

[0153] In an optional embodiment of the present invention, the virtual verification module 43 is used to obtain a first performance indicator value of the first link at a first moment within the basic time period; obtain a second performance indicator value of the first time period and a third performance indicator value of the second time period based on the first performance indicator value; determine whether the first link fails within the basic time period based on the second performance indicator value and the third performance indicator value, and obtain a fault monitoring result.

[0154] In an optional embodiment of the present invention, the virtual verification module 43 is used to determine that the first link has failed, and / or determine that the predecessor node in the first link has failed when the third performance indicator value is greater than or equal to the first threshold and the second performance indicator value is less than the first threshold.

[0155] In an optional embodiment of the present invention, the performance indicator includes one or more of the following: delay, packet loss rate, and bandwidth utilization.

[0156] In an optional embodiment of the present invention, the multipath redundancy module 42 is used to determine that there is no mark in the virtual network topology map, and obtain the virtual routing flow table according to the first array and the second array corresponding to the updated shortest path from the source node to each node.

[0157] In an optional embodiment of the present invention, the device further includes a communication processing module 44, which is used to connect the basic environment module 41, the multipath redundancy module 42 and the virtual verification module 43; and is further used to initialize communication configuration and establish a communication protocol service, and transmit the virtual network topology map generated by the basic environment module 41 to the multipath redundancy module 42 through the protocol, and transmit the virtual routing flow table to the virtual verification module 43; For example, the communication processing module 44 may encapsulate the algorithm into a service interface, such as using a Representational State Transfer (RESTful) Application Programming Interface (API), a message queue, or a full-duplex communication interface (such as WebSockets).

[0158] In the implementation of the present invention, the basic environment module 41, the multi-path redundancy module 42 and the virtual verification module 43 in the device can be implemented by a central processing unit (CPU), a digital signal processor (DSP), a microcontroller unit (MCU) or a field-programmable gate array (FPGA) in actual applications; the communication processing module 44 in the device can be implemented by a communication module (including: basic communication kit, operating system, communication module, standardized interface and protocol, etc.) and a transceiver antenna in actual applications.

[0159] It should be noted that: when the above-mentioned network resource optimization device performs network resource optimization, only the division of the above-mentioned program modules is used as an example to illustrate. In actual applications, the above-mentioned processing can be assigned to different program modules as needed, that is, the internal structure of the device can be divided into different program modules to complete all or part of the processing described above. In addition, the network resource optimization device provided in the above embodiment and the network resource optimization method embodiment are of the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0160] The embodiment of the present invention also provides a network resource optimization system, which is deployed on the digital twin network side in the network resource optimization system architecture. Figure 2 The platform architecture shown in the figure corresponds to the digital twin network side.

[0161] Figure 7 FIG. 1 is a schematic diagram of the structure of a network resource optimization system according to an embodiment of the present invention; FIG. Figure 7 As shown, the system includes: a physical layer 51, a connection layer 52, a twin data layer 53 and an application service layer 54; wherein, The physical layer 51 is used to provide physical network information, including network devices in the physical network, connection relationships between network devices, and performance indicators corresponding to connections between network devices; The connection layer 52 is used to transmit the physical network information provided by the physical layer 51 to the twin data layer 53; The twin data layer 53 is used to generate a virtual network topology based on the physical network information, and determine the shortest path information from the source node to each node in the virtual network topology; wherein the virtual network topology includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to the connection relationships between network devices; the weights represent index parameters of the links; the source node is any node in the virtual network topology; it is also used to determine the first time period and the second time period included in the basic time period according to monitoring requirements and / or network traffic characteristics; the performance indicators of the first link are monitored within the basic time period, and the first link is fault detected based on the monitored performance indicators, the first time period, and the second time period to obtain a fault detection result; the first link is a link formed by two nodes included in the shortest path information; a virtual routing flow table is determined based on the fault detection result, and the virtual routing flow table is mapped to physical network resource optimization information; The application service layer 54 is used to send monitoring requirements to the twin data layer 53; it is also used to obtain physical network resource optimization information from the twin data layer 53, and optimize the configuration of network devices and / or connections between network devices according to the physical network resource optimization information to achieve business deployment.

[0162] In the embodiment of the present invention, a four-layer architecture is designed, in which the physical layer provides the network connection and traffic data foundation of the physical network elements, the connection layer serves as the transmission bridge between physical and virtual information, the twin data layer includes key sub-models such as data mapping, data warehouse and service mapping models, performs data processing and modeling, and the application service layer implements business demand input, modeled deployment and control updates of the physical layer. Compared with the existing technology, the four-layer architecture is more refined and coordinated more closely. The data mapping, data warehouse and service mapping model subsystems are subdivided in the twin data layer to achieve accurate data processing, improve the depth and breadth of network resource optimization, expand the optimization from local to global, improve network performance stability and resource utilization, adapt to the complex and changing needs of cloud networks, and can perform various tests and optimization decisions without affecting the actual network operation, thereby improving the reliability and security of cloud networks.

[0163] As an example, the twin data layer 53 is based on Figure 6 The various modules in the network resource optimization device shown are implemented by calling the encapsulated modules through the API interface to implement the various functions in the twin data layer 53. Figure 8 FIG. 1 is a schematic diagram of the structure and operation flow of the network resource optimization system according to an embodiment of the present invention; FIG. Figure 8 As shown, the structural operation process of realizing network resource optimization based on each module in the network resource optimization device is as follows: The basic environment module 41 corresponds to the data mapping and data warehouse in the twin data layer 53, and is used to receive the physical network information sent by the physical layer 51 through the connection layer 52, and model the network element link scenarios that require twinning, specifically including twin network element information mapping of network devices in the physical network information, twin link information mapping of the connection relationship between network elements in the physical network information, and storage of the traffic parameter information obtained related to the physical network.

[0164] The multi-path redundancy module 42 is used to implement some functions of the service mapping model in the twin data layer 53, specifically for loading and running the algorithm program. The input of this module is determined by the communication processing module 44. The basic sub-module in the service mapping model receives the content input through the communication processing module 44. The input content can be parameter information related to business needs entered by the user in the custom interface, and / or the routing initial state parameters, destination address and traffic information stored in the basic environment module 41. The functional sub-module in the service mapping model performs forward data processing on the input content through algorithm iteration, and outputs the initial virtual routing flow table to the virtual verification module 43 after the processing is completed. In addition, the initial virtual routing flow table is updated according to the fault detection results fed back by the virtual verification module 43, and the updated virtual routing flow table is transmitted to the virtual verification module 43.

[0165] The virtual verification module 43 is used to implement some functions of the service mapping model in the twin data layer 53. Specifically, it is used to receive the initial virtual routing flow table from the multi-path redundancy module 42 through the communication protocol established by the communication processing module 44, and verify the initial virtual routing flow table in combination with the fault detection feedback mechanism of the scalable time period. After detecting the fault path and / or fault node, the fault detection result is fed back to the multi-path redundancy module 42 to obtain an updated virtual routing flow table; after obtaining the verification success information, the relevant data parameters are selected, and the data parameter configuration is mapped into physical network elements and data information, which are forwarded to the cloud server platform side through routing, and corresponding decision feedback is obtained to implement early optimization measures in scenarios such as network resource optimization, time period traffic prediction, and fault detection and early warning.

[0166] The communication processing module 44 is used to initialize the communication configuration, build the communication protocol service, and connect the data warehouse, data mapping and service mapping model in the twin data layer 53 to realize the information interaction between the above functional modules, obtain the virtual routing flow table output by the multi-path redundancy module 42 in the form of message receiving notification, and transmit the virtual routing flow table to the virtual verification module 43 in the form of message sending notification.

[0167] In the embodiment of the present invention, by designing the above-mentioned multiple modules, the basic environment module constructs a network element link scenario model, the multi-path redundancy module runs an algorithm and combines it with a fault detection feedback mechanism to determine a virtual routing flow table after network resource optimization, the communication processing module is responsible for communication configuration and information transmission, and the virtual verification module performs network element link path planning and feedback in the virtual mapping environment. Based on the verification results, network parameters are intelligently adjusted to improve the network's adaptability, enabling the network to operate stably and efficiently under complex conditions such as different loads and faults, and enhancing the network's adaptability to complex and changing cloud network environments. Through the collaborative work of various modules, the automation and intelligence of the network resource optimization process are achieved, the interaction of module functions is systematically guaranteed, and the module functions are flexibly expanded to adapt to various network scenarios.

[0168] An embodiment of the present invention further provides a computer device, Figure 9 FIG. 1 is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention; FIG. Figure 9 As shown, the computer device includes a memory 62 , a processor 61 , and a computer program stored in the memory 62 and executable on the processor 61 .

[0169] Optionally, the processor 61 implements the steps of the network resource optimization method of the embodiment of the present invention when executing the program.

[0170] Optionally, the computer device further includes at least one communication component 64. The various components in the computer device can be coupled together via a bus system 63. It is understood that the bus system 63 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 63 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Figure 9 Various buses are labeled as bus system 63.

[0171] It is understood that the memory 62 can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory, a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM); the magnetic surface memory can be a magnetic disk or a magnetic tape. The volatile memory can be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static random access memory (SRAM), synchronous static random access memory (SSRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct rambus random access memory (DRRAM).The memory 62 described in the embodiments of the present invention is intended to include, but is not limited to, these and any other suitable types of memory.

[0172] The methods disclosed in the above embodiments of the present invention can be applied to or implemented by processor 61. Processor 61 may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by hardware integrated logic circuits in processor 61 or by software instructions. The above processor 61 may be a general-purpose processor, a DSP, or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc. Processor 61 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present invention can be directly implemented and executed by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium located in memory 62. Processor 61 reads information from memory 62 and, in conjunction with its hardware, completes the steps of the above method.

[0173] In an exemplary embodiment, the computer device may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, MCUs, microprocessors, or other electronic components to perform the aforementioned methods.

[0174] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored.

[0175] Optionally, the computer-readable storage medium can be applied to the network resource optimization device of the embodiment of the present invention; then, when the program is executed by the processor, the steps of the network resource optimization method of the embodiment of the present invention are implemented.

[0176] An embodiment of the present invention further provides a computer program product, including a computer program, which can be executed by the processor 61 of a computer device to complete the steps of the network resource optimization method described in the embodiment of the present invention.

[0177] The methods disclosed in the several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0178] The features disclosed in the several product embodiments provided in this application can be arbitrarily combined without conflict to obtain new product embodiments.

[0179] The features disclosed in the several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0180] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0181] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0182] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0183] Those skilled in the art will appreciate that all or part of the steps of the above-mentioned method embodiments may be implemented by hardware associated with program instructions, and the aforementioned program may be stored in a computer-readable storage medium. When the program is executed, the program executes the steps of the above-mentioned method embodiments. The aforementioned storage medium includes various media that can store program codes, such as mobile storage devices, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0184] Alternatively, if the integrated units described above are implemented as software modules and sold or used as standalone products, they can also be stored on a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product, stored on a storage medium, includes instructions for enabling a computer device (such as a personal computer, server, or network device) to execute all or part of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as removable storage devices, ROM, RAM, magnetic disks, or optical disks.

[0185] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed by the present invention, which should be covered by the scope of protection of the present invention.

Claims

1. A network resource optimization method, characterized in that: The method comprises: Obtaining physical network information and generating a virtual network topology diagram based on the physical network information; wherein the virtual network topology diagram includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to connection relationships between network devices; and the weights represent indicator parameters of the links; Determine the shortest path information from a source node to each node in the virtual network topology graph; the source node is any node in the virtual network topology graph; Determine the first time period and the second time period included in the basic time period according to monitoring requirements and / or network traffic characteristics; monitoring a performance indicator of a first link within the basic time period, and performing fault detection on the first link based on the monitored performance indicator, the first time period, and the second time period to obtain a fault detection result; the first link being a link formed by two nodes included in the shortest path information; A virtual routing flow table is determined according to the fault detection result, and the virtual routing flow table is used to optimize the configuration of the network device and / or the connection between the network devices.

2. The method according to claim 1, characterized in that The physical network information includes network devices in the physical network, connection relationships between network devices, and performance indicators corresponding to connections between network devices; generating a virtual network topology map based on the physical network information includes: Mapping the network devices in the physical network information into nodes, and mapping the connection relationships between the network devices in the physical network information into links between the nodes, to generate an initial virtual network topology graph; Weights are determined based on performance indicators corresponding to connections between network devices, and the weights are mapped to links corresponding to connections between the network devices to generate the virtual network topology graph.

3. The method according to claim 1, characterized in that Determining the shortest path information from the source node to each node in the virtual network topology graph includes: Based on the virtual network topology graph, obtaining a first array and a second array corresponding to the source node and each node, and determining shortest path information between the source node and each node based on the first array and the second array; Among them, the first array includes the shortest distance corresponding to the shortest path from the source node to each node, and the second array includes the predecessor node of each node on the shortest path; the shortest path satisfies the minimum link delay and / or the minimum bandwidth consumption, and the shortest distance represents the corresponding delay and / or bandwidth consumption of the shortest path.

4. The method according to claim 3, characterized in that The step of obtaining the first array and the second array corresponding to the source node and each node includes: Initializing a first array, a second array, and a first node set, wherein the first node set includes visited nodes; Selecting a first node from a second node set, and adding the first node to the first node set; wherein the second node set includes unvisited nodes, and the first node is the node closest to the source node; Determine a second node from among the adjacent nodes of the first node, and use the first node as a predecessor node of the second node; wherein the second node satisfies: the sum of the shortest distance between the first node and the source node and the weight between the first node and the second node is less than the shortest distance between the second node and the source node, and the second node does not belong to the first node set; The first array and the second array corresponding to the shortest path from the source node to the second node are updated based on the second node.

5. The method according to claim 3, characterized in that The virtual network topology map also includes a first mark of the link where the fault occurred in the fault detection result, and / or a second mark of the node where the fault occurred; wherein the weight of the link associated with the first mark is the maximum value; the first mark and / or the second mark are used to update the first array and the second array.

6. The method according to claim 5, characterized in that The first flag and / or the second flag are used to update the first array and the second array, including: Determining a shortest path between a third node and a fourth node based on nodes not associated with the second tag, nodes corresponding to links not associated with the first tag, and links not associated with the first tag in the virtual network topology graph; wherein the third node is a predecessor node of the node associated with the second tag, and the fourth node is a tail node in the link associated with the first tag; Based on the shortest path between the third node and the fourth node, the corresponding first array and second array are updated, and the first mark and / or the second mark are deleted.

7. The method according to any one of claims 1 to 6, characterized in that The monitoring of the performance indicator of the first link within the basic time period, performing fault detection on the first link based on the monitored performance indicator, and obtaining a fault detection result includes: Obtaining a first performance indicator value of the first link at a first moment in the basic time period; Obtaining a second performance indicator value for the first time period and a third performance indicator value for the second time period based on the first performance indicator value; It is determined whether a fault occurs on the first link within the basic time period based on the second performance indicator value and the third performance indicator value, and a fault monitoring result is obtained.

8. The method according to claim 7, characterized in that The determining whether a fault occurs on the first link within the basic time period based on the second performance indicator value and the third performance indicator value includes: When the third performance indicator value is greater than or equal to the first threshold and the second performance indicator value is less than the first threshold, it is determined that the first link fails and / or that a predecessor node in the first link fails.

9. The method according to claim 1, characterized in that The performance indicators include one or more of the following: delay, packet loss rate, and bandwidth utilization.

10. The method according to claim 6, characterized in that Determining a virtual routing flow table according to the fault detection result includes: When it is determined that there is no mark in the virtual network topology map, a virtual routing flow table is obtained according to the first array and the second array corresponding to the updated shortest path from the source node to each node.

11. A network resource optimization device, characterized in that: The device includes: a basic environment module, a multi-path redundancy module and a virtual verification module; wherein, The basic environment module is configured to obtain physical network information and generate a virtual network topology diagram based on the physical network information; wherein the virtual network topology diagram includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to connection relationships between network devices; and the weights represent indicator parameters of the links; The multi-path redundancy module is configured to determine the shortest path information from a source node to each node in the virtual network topology diagram; the source node is any node in the virtual network topology diagram; and is further configured to determine a virtual routing flow table based on the fault detection result, the virtual routing flow table being used to optimize the configuration of network devices and / or connections between network devices; The virtual verification module is used to determine the first time period and the second time period included in the basic time period based on monitoring requirements and / or network traffic characteristics; monitor the performance indicators of the first link within the basic time period, and perform fault detection on the first link based on the monitored performance indicators, the first time period and the second time period to obtain a fault detection result; the first link is a link formed by two nodes included in the shortest path information.

12. A network resource optimization system, characterized in that: The system includes: a physical layer, a connection layer, a twin data layer and an application service layer; wherein, The physical layer is used to provide physical network information, including network devices in the physical network, connection relationships between network devices, and performance indicators corresponding to connections between network devices; The connection layer is used to transmit the physical network information provided by the physical layer to the twin data layer; The twin data layer is used to generate a virtual network topology based on the physical network information, and determine the shortest path information from the source node to each node in the virtual network topology; wherein the virtual network topology includes nodes, links between nodes, and weights corresponding to the links; the nodes correspond to network devices in the physical network information; the links correspond to the connection relationships between network devices; the weights represent the index parameters of the links; the source node is any node in the virtual network topology; it is also used to determine the first time period and the second time period included in the basic time period according to monitoring requirements and / or network traffic characteristics; the performance indicators of the first link are monitored within the basic time period, and the first link is fault detected based on the monitored performance indicators, the first time period, and the second time period to obtain a fault detection result; the first link is a link formed by two nodes included in the shortest path information; a virtual routing flow table is determined based on the fault detection result, and the virtual routing flow table is mapped to physical network resource optimization information; The application service layer is used to send monitoring requirements to the twin data layer; it is also used to obtain physical network resource optimization information from the twin data layer, and optimize the configuration of network devices and / or connections between network devices according to the physical network resource optimization information to achieve business deployment.

13. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method according to any one of claims 1 to 10 are implemented.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 10 are implemented.

15. A computer program product comprising a computer program, characterized in that The computer program implements the method according to any one of claims 1 to 10 when executed by a processor.

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