CN115314419B - Cloud network-oriented self-adaptive connectivity analysis method, system, equipment and storage medium - Google Patents
Cloud network-oriented self-adaptive connectivity analysis method, system, equipment and storage medium Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
- H04L43/0811—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking connectivity
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/069—Management of faults, events, alarms or notifications using logs of notifications; Post-processing of notifications
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/50—Reducing energy consumption in communication networks in wire-line communication networks, e.g. low power modes or reduced link rate
Abstract
The invention discloses a self-adaptive connectivity analysis method, a system, equipment and a storage medium, wherein the method comprises the following steps: extracting connectivity data of a network instance from a preset database, and obtaining a connectivity analysis result of the distributed cache according to the connectivity data; acquiring log data of a log center of the network controller, and acquiring change event data according to the log data; determining the variation of the connectivity analysis result according to the change event data and the connectivity analysis result, and updating the connectivity analysis result according to the variation; and generating a self-adaptive analysis result of the cloud network according to the updated connectivity analysis result. The performance of connectivity analysis in the product is greatly improved, a connectivity conclusion is given based on the pre-calculated and real-time updated connectivity analysis result, and real-time peer-to-peer connectivity is not needed to be analyzed hop by hop. Such business parties of the cloud network tenant-level active detection system can be supported, and real-time perception and self-adaption of cloud network connectivity change are facilitated.
Description
Technical Field
The present invention relates to the field of adaptive connectivity analysis technologies, and in particular, to a cloud network adaptive connectivity analysis method, system, device, and storage medium.
Background
As the system of public cloud computing data center networks is becoming more and more abundant, networking modes are flexible, and network forms of users are becoming more and more complex. In the face of a vast and complex cloud network topology, the end-to-end connectivity analysis capability of cloud tenants and cloud service providers is particularly critical when using networks, operating networks and troubleshooting problems.
In addition, classical physical network topologies have small variations after network construction is complete, and topology changes depend on changes in the connections between physical devices. However, the cloud network benefits from the virtualization technology, and the topology change of the cloud network is more flexible. The cloud tenant can change the resources, configuration and routing on the cloud at any time, change the network topology and further influence the network connectivity. Therefore, for cloud service providers to operate the network on the cloud, monitoring the network quality on the cloud of all network tenants, to be able to discover, locate and solve network problems in advance for users, the ability to perceive network connectivity in real time is a necessary capability. Meanwhile, to achieve finer network operations, cloud service providers often need active probing capabilities at the level of network construction tenant instances on the cloud. The active detection system is required to ensure the detection instantaneity and accuracy, and is required to adjust detection objects and detection strategies in real time according to the change of the network topology of the tenant, and the sensing and self-adaption capability of the network connectivity change is also required.
In the invention of cloud network reachability analysis submitted by google Limited liability company, one or more simulated forwarding paths are calculated based on the IP address of a request source and the IP address of a destination and the configuration information of network nodes on a cloud network forwarding path so as to determine the reachability of a request target. In the invention of a network reachability detection method and device submitted by digital technology (Suzhou) limited company, a reachability detection result after forwarding in network equipment is obtained according to network equipment topology information and routing table and request message source and target address information.
The prior art only solves the basic problem of cloud network connectivity analysis, namely, for any two ends on the cloud, route calculation is carried out hop by hop in real time based on the routing configuration and the network topology of the tenant layer, and the end-to-end connectivity is analyzed.
However, the prior art does not maintain the connectivity analysis result of the whole network, which is a real-time triggered one-time connectivity analysis, and each analysis needs to be calculated hop by hop. When the network topology is complex and the access links are long, the time overhead of connectivity analysis is not negligible. However, when the problem is examined for the cloud tenant and the cloud service provider, the efficient connectivity analysis capability is very important for shortening the MTTD (Mean Time to Detect, average detection time) and the MTTR (Mean Time to Repair, average repair time) and improving the operation and maintenance efficiency.
Cloud networks have a large number of tenant-level provisioning operations per day, which can have an impact on cloud network connectivity. In the prior art, the connectivity analysis result is not maintained in real time, and each analysis is based on the current route and configuration data, so that the real-time change of the connectivity is ignored. How to analyze the influence of the change event on the connectivity, and adaptively sense and process the change of the connectivity, and maintain the connectivity analysis result of the whole network tenant in real time is an unsolved problem in the prior art.
In addition, in the prior art, explicit source end addresses and destination end addresses are used as input, and all reachable communication scenes of a network instance on a single cloud of a tenant cannot be automatically identified according to the instance. For example, the prior art may analyze whether two given virtual machine instances are reachable from each other. However, if only a single virtual machine instance is specified, the prior art cannot analyze all the connectivity scenarios of the virtual machine.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems in the related art to some extent.
Therefore, the invention aims to provide a cloud network-oriented self-adaptive connectivity analysis method, a cloud network-oriented self-adaptive connectivity analysis system, cloud network-oriented self-adaptive connectivity analysis equipment and a cloud network-oriented self-adaptive storage medium, which can also self-adaptively analyze the influence of events such as tenant instance resource change, route change and the like on network connectivity on the basis of solving the problem of cloud network end-to-end connectivity analysis, and maintain the latest full-network tenant connectivity analysis result in real time.
In order to achieve the above objective, in one aspect, the present invention provides a cloud network-oriented adaptive connectivity analysis method, including:
extracting connectivity data of a network instance from a preset database, and obtaining a connectivity analysis result of a distributed cache according to the connectivity data;
acquiring log data of a log center of a network controller, and obtaining change event data according to the log data;
determining the variation of the connectivity analysis result according to the change event data and the connectivity analysis result, and updating the connectivity analysis result according to the variation;
and generating a self-adaptive analysis result of the cloud network according to the updated connectivity analysis result.
The cloud network-oriented adaptive connectivity analysis method according to the embodiment of the invention can also have the following additional technical characteristics:
further, in one embodiment of the present invention, the method further comprises: querying the updated connectivity analysis result to trigger analysis of the connectivity data in real time according to the query result; wherein the query results include connectivity analysis results of the query that are not stored in the distributed cache.
Further, in an embodiment of the present invention, the extracting connectivity data of different types of network instances from a preset database, and obtaining a connectivity analysis result of a distributed cache according to the connectivity data includes: performing pattern matching on the database, and identifying different types of network instances in the database according to the network ID; obtaining a communication scene identification result of the current type network instance through the resource relation data and the routing data stored in the database; and calculating a communication path according to the route data based on the communication scene recognition result to obtain the connectivity analysis result.
Further, in an embodiment of the present invention, the determining the variation of the connectivity analysis result according to the provisioning event data and the connectivity analysis result, and updating the connectivity analysis result according to the variation includes: obtaining the transformation event data and the associated data of the network instances of different types according to the resource relation data; aggregating the associated data according to an instance dimension to obtain change instance data; and updating the connectivity analysis result of the change instance data according to the overall connectivity data of the change instance data.
In order to achieve the above objective, another aspect of the present invention provides a cloud network-oriented adaptive connectivity analysis system, including:
the connectivity analysis module is used for extracting connectivity data of the network instance from a preset database and obtaining a connectivity analysis result of the distributed cache according to the connectivity data;
the data acquisition module is used for acquiring log data of a log center of the network controller and acquiring the change event data according to the log data;
the transformation self-adaptation module is used for determining the variation of the connectivity analysis result according to the transformation event data and the connectivity analysis result and updating the connectivity analysis result according to the variation;
and the calculation analysis module is used for generating a self-adaptive analysis result of the cloud network according to the updated connectivity analysis result.
A third aspect of the invention provides a computer device comprising a processor and a memory;
the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to be used for realizing a cloud network-oriented adaptive connectivity analysis method.
A fourth aspect of the present invention proposes a non-transitory computer readable storage medium, on which a computer program is stored, characterized in that the program, when executed by a processor, implements a cloud network oriented adaptive connectivity analysis method.
The self-adaptive connectivity analysis method, the system, the equipment and the storage medium can also self-adaptively analyze the influence of events such as tenant instance resource change, route change and the like on network connectivity on the basis of solving the problem of cloud network end-to-end connectivity analysis, and maintain the latest full-network tenant connectivity analysis result in real time.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
The foregoing and/or additional aspects and advantages of the invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
fig. 1 is a flowchart of a cloud network-oriented adaptive connectivity analysis method according to an embodiment of the present invention;
FIG. 2 is a diagram of a cloud network oriented adaptive connectivity analysis architecture according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of connectivity analysis according to an embodiment of the present invention;
FIG. 4 is a flow chart of a variant adaptation according to an embodiment of the invention;
fig. 5 is a schematic structural diagram of a cloud network-oriented adaptive connectivity analysis system according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of a connectivity analysis module according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a configuration of a variable-configuration adaptive module according to an embodiment of the present invention;
fig. 8 is a computer device according to an embodiment of the invention.
Detailed Description
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The invention will be described in detail below with reference to the drawings in connection with embodiments.
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
The following describes a cloud network-oriented adaptive connectivity analysis method, a cloud network-oriented adaptive connectivity analysis system, cloud network-oriented adaptive connectivity analysis equipment and a cloud network-oriented storage medium according to an embodiment of the invention with reference to the accompanying drawings.
Fig. 1 is a flow chart of a cloud network oriented adaptive connectivity analysis method according to an embodiment of the present invention.
As shown in fig. 1, the method includes, but is not limited to, the steps of:
s1, extracting connectivity data of a network instance from a preset database, and obtaining a connectivity analysis result of a distributed cache according to the connectivity data;
s2, acquiring log data of a log center of the network controller, and acquiring change event data according to the log data;
s3, determining the variation of the connectivity analysis result according to the transformation event data and the connectivity analysis result, and updating the connectivity analysis result according to the variation;
and S4, generating a self-adaptive analysis result of the cloud network according to the updated connectivity analysis result.
According to the cloud network-oriented self-adaptive connectivity analysis method, on the basis of solving the problem of cloud network end-to-end connectivity analysis, the influence of events such as tenant instance resource change, route change and the like on network connectivity can be adaptively analyzed, and the latest full-network tenant connectivity analysis result is maintained in real time.
Further, inquiring the updated connectivity analysis result to trigger the analysis of the connectivity data in real time according to the inquiry result; wherein the query results include connectivity analysis results of the query that are not stored in the distributed cache.
Further, in the above step S1, pattern matching is performed on a database, and different types of network instances in the database are identified according to a network ID; obtaining a communication scene identification result of the current type network instance through the resource relation data and the routing data stored in the database; and calculating a communication path according to the route data based on the communication scene recognition result to obtain a connectivity analysis result.
Further, in the step S3, according to the resource relationship data, the configuration event data and the association data of different types of network instances are obtained; aggregating the associated data according to the instance dimension to obtain changed instance data; and updating the connectivity analysis result of the change instance data according to the overall connectivity data of the change instance data.
Further, the cloud network-oriented adaptive connectivity analysis architecture of the present invention is shown in fig. 2.
As one example, the architecture mainly contains 5 parts of connectivity query, resource subscription, adaptation, connectivity analysis and data collection. After the system is started, connectivity analysis carries out full initialization on connectivity of all instance resources of the whole network. Based on the cloud network resource relation data and the route configuration data stored in the general operation and data base, calculating the connectivity analysis results of all network instances, and writing the connectivity analysis results into the distributed cache. The change adaptation can consume network resources and route change events from data acquisition delivery in real time, convert the events into changes of connectivity results, push update of the connectivity results to resource subscribers, and write the latest connectivity results into a cache, so that the self-adaptive analysis of network connectivity is realized.
Specifically, connectivity queries. And directly querying connectivity analysis results in the distributed cache, which are updated in real time by the variant adaptation, and providing the connectivity analysis capability of the specified end-to-end or single network instance for the user. When the connectivity results of the query instance are not stored in the distributed cache, a relatively time-consuming real-time hop-by-hop connectivity analysis is triggered. The calculation process of connectivity analysis and the query process are decoupled through the pre-calculated and real-time updated connectivity result cache, so that the analysis efficiency is greatly improved, and the average time consumption is in the millisecond level.
End-to-end: the user inputs two ends (load equalizer instance and virtual machine instance) in the cloud network, and analyzes whether the two ends are reachable. For example, the user designates the source VM1 and the destination VM2, and returns a communication path existing between VM1 and VM2, including cloud network nodes on the path, such as the virtual router VRT and its routing table and the specifically matched routing table entry.
Single instance: and the user inputs an end or network instance in the cloud network, and gives all connected scenes of the instance. The network instance comprises a virtual private network VPC and a virtual switch VSW dividing the subnetwork. For example, the user designates a single VPC instance, and the portion returns all reachable connectivity scenarios of the VPC, such as private network interviews on the cloud, private network and public network interviews on the cloud, IDC under the cloud access by private network on the cloud, and so on. Each scene contains the segment addresses that are actually connected.
And subscribing resources. The user is provided with the capability of subscribing to resource connectivity changes on the cloud, supporting subscription at VPC granularity. After the user successfully subscribes to the appointed VPC instance, the change self-adaption perceives connectivity update caused by the change, and the connectivity change of the subscribed VPC is included, and the content of the connectivity change is pushed to the subscriber in an asynchronous callback mode. Through this section, subscribers can achieve real-time awareness of network connectivity changes on the cloud.
Further, as shown in fig. 3, a schematic diagram of connectivity analysis is shown. And when the system is started and at a fixed time every day, all tenant network data of the whole network are pulled from the universal operation data base, full connectivity analysis is carried out, and the result is written into the distributed cache. When the connectivity query misses the cache, a real-time connectivity analysis is triggered. This section contains 4 key steps of object recognition, scene recognition, path computation, and endpoint resolution.
And (5) object identification. By pattern matching, the network type is identified as VPC (tenant data center network, hereinafter referred to as VPC) or cross-regional network according to the network ID. Different types of instances have different connectivity scenarios. For example, the inter-visit scene in the cloud and the private network is a communication scene only belonging to the VPC instance, and is irrelevant to a cross-regional network, and the cross-regional network only relates to inter-visit among different private networks in the cloud.
And (5) scene recognition. And identifying all the connected scenes existing in the current analysis instance according to the resource relation data and the routing data stored in the universal operation data base. The resource relationship data includes association relationships between network resources such as VPC and virtual switch, VPC and NAT gateway, VPC and cross-regional network, virtual switch and routing table, virtual switch and VM, VM and public network IP. The routing data comprises all routing table entries of a virtual router under VPC, a cross-regional router under a cross-regional network and a virtual boundary router connected by a physical special line. The communication scene comprises inter-access of the cloud with the private network, inter-access of the cloud with the private network and the public network, inter-access of the cloud with different private networks (same region or cross region) and inter-access of the cloud with the private network and the off-line IDC. The identification mode is that if the VM is bound with the public network IP, the VM is communicated with the public network; when the next hop of the route in the virtual router is a virtual boundary router, the communication between the VPC corresponding to the virtual router and the off-line IDC is indicated, and the specific communication network segment is required to be further analyzed in the path calculation.
And (5) path calculation. And calculating a communication path hop by hop based on the routing data for each scene according to the scene identification result, and finally obtaining the connectivity result under all scenes. The result contains the network segment addresses of both connected ends and the corresponding connected paths (each hop of routing node on the path is recorded). For example, the scene recognition result shows that the next hop of the virtual router points to the cross-regional router, which indicates that the VPC associated with the virtual router may be communicated with other VPCs via the cross-regional network, the virtual router points to the destination CIDR of the cross-regional network routing table entry, so as to try to match the routing table entry of the virtual router to obtain the next hop of the virtual router, and the route matching operation is performed on the next hop of the virtual router until the route matching fails or reaches the end in the network, i.e. the virtual machine or the load balancer, which indicates that the unidirectional path calculation is completed, and a final destination CIDR is obtained through the hop-by-hop route matching. However, in this case, only the unidirectional communication of the path is described, and it is necessary to perform path calculation again from the end point of the path calculation to the source instance, thereby obtaining the connectivity of the loop. The final destination CIDR obtained by bidirectional calculation forms a communication pair of network segments at two ends of different private networks, namely a connectivity result, and corresponds to a communication path formed by intermediate routing nodes (virtual router/virtual boundary router/cross-regional network router).
And (5) end point analysis. The path calculation to obtain the connectivity result is described by a pair of network segment addresses CIDR and its associated network instance VPC, and to improve the readability of the result, both ends in the connectivity result are to be resolved. Through the CIDR of the VPC, the CIDR of the virtual switch, the IP of the VM, the IP of the load balancer and the like in the general operation database resource relation data, two ends in the connectivity result can be analyzed from the CIDR into a VPC instance, a virtual switch instance, a VM instance and a load balancer instance.
Further, a variant adaptation flow chart is shown in fig. 4. The part inputs full network resources and route change events delivered by data acquisition, and the method comprises 7 steps of event impact surface analysis, associated network instance, event aggregation, connectivity change calculation, connectivity difference analysis, change push subscribers and update distributed cache. And finally pushing the connectivity change of the subscribed instance to the subscriber, and updating the latest connectivity result into the distributed cache, thereby realizing the self-adaption of the connectivity change caused by the change event.
Events affect the surface analysis. The change event comprises ADD, UPDATE, DELETE three types, and each change event can correspond to a data table in the general operation and maintenance database. If a subscriber newly allocates a subnet, i.e., ADDs a virtual switch instance, an ADD event of a virtual switch instance table is generated accordingly. The influence of the current event on connectivity can be determined through analysis of the type of the change event, a data table corresponding to the change event and specific change information. For the change event that does not affect connectivity, it is filtered. For example, an ADD-type change event, where the corresponding data table is a VPC routing table, and the change information is a VPC route whose next hop is a public network NAT gateway, may cause a change in connectivity of the VPC, and needs to enter a subsequent procedure. If an UPDATE type of event improves the bandwidth packet specification of the public network IP, the event obviously does not directly affect network connectivity and needs filtering.
And associating network instances. The basic objects of the connectivity analysis mentioned above are VPC and cross-regional network instances, while the change events are fine-grained, specific to generic operation-data base table level information. Therefore, the configuration event needs to be associated with the VPC and the cross-regional network instance based on the resource association relationship data in the universal operation and data database for subsequent analysis. For example, an NAT gateway adds an SNAT rule, and then the NAT gateway instance can be obtained by transforming the information carried by the event itself. The provisioning event may be associated with the VPC instance by the resource relationship data of the NAT gateway and the VPC instance.
Event aggregation. The occurrence of a large number of instances of the same VPC or the same cross-regional network in a short time can lead to frequent connectivity change calculation of the same instance, so that the part sets a time window of 5 seconds when a change event is processed, repeated calculation of the same instance is reduced, and system calculation force is saved. And aggregating a plurality of transformation events arriving in the same time window according to instance dimensions according to the VPC or cross-regional network instance associated in the last step. For example, 1000 change events were generated within 5 seconds, but only 30 VPC instances were corresponded after aggregation by instance. Minimizing the computational effort consumption of otherwise frequent and redundant computations can also reduce overall processing time.
Connectivity change calculation. The last step has aggregated the change events according to the VPC and cross-regional network instance dimensions, resulting in a changed instance. The current step multiplexes the connectivity analysis capability, directly calculates the overall connectivity of the VPC and the cross-regional network instance, and obtains the latest connectivity analysis result of the instances.
Connectivity variance analysis. Before updating the distributed cache, the latest connectivity analysis result obtained by calculation needs to be subjected to difference analysis with the connectivity results existing in the current distributed cache, so as to obtain a connectivity change part. In the connectivity analysis, the connectivity results have been described in terms of a pair of connected CIDRs and their associated VPC instances, where the CIDRs may also be parsed into end instances in a specific network such as a VPC, virtual switch, VM, or load balancer. The connectivity difference analysis mode is to directly compare whether the two ends VPC and CIDR (or as an example of the end) of the two connectivity result data are the same, and finally obtain the change of the connectivity, including the newly added connectivity and the deleted connectivity.
The change pushes subscribers. After the difference analysis is completed, checking the examples subscribed by the user through the resource subscription part, wherein different users have different subscription groups. And for each subscription group, determining the VPC and the cross-regional network instance which are subscribed by the user and change in the current event processing time window, and pushing the connectivity change through the asynchronous callback interface appointed by the user according to the dimensionality of the VPC and the cross-regional network instance.
Updating the distributed cache. The latest connectivity result obtained by the example calculation of the change is updated and cached, so that the real-time updating of the connectivity result in the cache is realized, and the self-adaptive processing of the influence of the change event on the connectivity is realized.
Further, when resource or route change operation occurs in the cloud network, the cloud network necessarily depends on the network controller to issue an operation instruction. After the join operation is performed, the network controller may issue one or more join-event logs in the dimension of the data table in the generic operation database. The part takes the change event log of the cloud network controller as input, and uniformly delivers the change events collected from different network controller log centers to a change self-adaption part of the system for processing.
According to the cloud network-oriented self-adaptive connectivity analysis method, products are supported to identify all connectivity scenes according to a single network instance, and other products do not have the capability. The performance of connectivity analysis in the product is greatly improved, a connectivity conclusion is given based on the pre-calculated and real-time updated connectivity analysis result, and real-time peer-to-peer connectivity is not needed to be analyzed hop by hop. Providing resource subscription capability, and pushing the connectivity change of the subscribed instance in real time. Such business parties of the cloud network tenant-level active detection system can be supported, and real-time perception and self-adaption of cloud network connectivity change are facilitated.
In order to implement the above embodiment, as shown in fig. 5, there is further provided a cloud network-oriented adaptive connectivity analysis system 10, where the system 10 includes: connectivity analysis module 100, data acquisition module 200, adaptation module 300, and computational analysis module 400.
The connectivity analysis module 100 is configured to extract connectivity data of a network instance from a preset database, and obtain a connectivity analysis result of the distributed cache according to the connectivity data;
the data acquisition module 200 is configured to acquire log data of a log center of the network controller, and obtain the transformation event data according to the log data;
the transformation adaptive module 300 is configured to determine a variation of the connectivity analysis result according to the transformation event data and the connectivity analysis result, and update the connectivity analysis result according to the variation;
the calculation analysis module 400 is configured to generate an adaptive analysis result of the cloud network according to the updated connectivity analysis result.
Further, the system 10 further includes:
the connectivity query module is used for querying the updated connectivity analysis result to trigger the analysis of the connectivity data by the connectivity analysis module 100 in real time according to the query result; wherein the query results include connectivity analysis results of the query that are not stored in the distributed cache.
Further, as shown in fig. 6, the connectivity analysis module 100 includes an object recognition unit 101, a scene recognition unit 102, and a path calculation unit 103; wherein, the liquid crystal display device comprises a liquid crystal display device,
an object recognition unit 101, configured to perform pattern matching on the database, and recognize different types of network instances in the database according to the network ID;
the scene recognition unit 102 is configured to obtain a connected scene recognition result of the current type network instance through the resource relationship data and the routing data stored in the database;
and a path calculation unit 103, configured to calculate a connectivity path according to the route data based on the connectivity scene recognition result to obtain a connectivity analysis result.
Further, as shown in fig. 7, the above-mentioned adaptation module 300 includes:
an associated network instance unit 301, configured to obtain, according to the resource relationship data, configuration event data and associated data of different types of network instances;
an event aggregation unit 302, configured to aggregate the associated data according to an instance dimension to obtain change instance data;
and the connectivity change unit 303 is configured to update the connectivity analysis result of the change instance data according to the overall connectivity data of the change instance data.
According to the cloud network-oriented self-adaptive connectivity analysis system provided by the embodiment of the invention, products are supported to identify all connectivity scenes according to a single network instance, and other products do not have the capability. The performance of connectivity analysis in the product is greatly improved, a connectivity conclusion is given based on the pre-calculated and real-time updated connectivity analysis result, and real-time peer-to-peer connectivity is not needed to be analyzed hop by hop. Providing resource subscription capability, and pushing the connectivity change of the subscribed instance in real time. Such business parties of the cloud network tenant-level active detection system can be supported, and real-time perception and self-adaption of cloud network connectivity change are facilitated.
In order to implement the method of the above embodiment, the present invention further provides a computer device, as shown in fig. 8, the computer device 600 includes a memory 601, and a processor 602; wherein the processor 602 runs a program corresponding to the executable program code by reading the executable program code stored in the memory 601 for implementing the steps of the above-described cloud network oriented adaptive connectivity analysis method.
In order to implement the method of the above embodiment, the present invention further provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a cloud network oriented adaptive connectivity analysis method.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "plurality" means at least two, for example, two, three, etc., unless specifically defined otherwise.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
While embodiments of the present invention have been shown and described above, it will be understood that the above embodiments are illustrative and not to be construed as limiting the invention, and that variations, modifications, alternatives and variations may be made to the above embodiments by one of ordinary skill in the art within the scope of the invention.
Claims (6)
1. The cloud network-oriented self-adaptive connectivity analysis method is characterized by comprising the following steps of:
extracting connectivity data of a network instance from a preset database, and obtaining a connectivity analysis result of a distributed cache according to the connectivity data;
acquiring log data of a log center of a network controller, and obtaining change event data according to the log data;
determining the variation of the connectivity analysis result according to the change event data and the connectivity analysis result, and updating the connectivity analysis result according to the variation;
generating a self-adaptive analysis result of the cloud network according to the updated connectivity analysis result;
the extracting connectivity data of different types of network examples from a preset database, and obtaining a connectivity analysis result of a distributed cache according to the connectivity data comprises the following steps:
performing pattern matching on the database, and identifying different types of network instances in the database according to the network ID;
obtaining a communication scene identification result of the current type network instance through the resource relation data and the routing data stored in the database;
based on the communication scene recognition result, calculating a communication path according to the routing data to obtain the connectivity analysis result;
the determining the variation of the connectivity analysis result according to the change event data and the connectivity analysis result, and updating the connectivity analysis result according to the variation, includes:
obtaining the transformation event data and the associated data of the network instances of different types according to the resource relation data;
aggregating the associated data according to an instance dimension to obtain change instance data;
and updating the connectivity analysis result of the change instance data according to the connectivity data of the change instance data.
2. The method of claim 1, wherein after the updating the connectivity analysis result according to the change amount, the method further comprises: querying the updated connectivity analysis result to trigger analysis of the connectivity data in real time according to the query result; wherein the query results include connectivity analysis results of the query that are not stored in the distributed cache.
3. A cloud network-oriented adaptive connectivity analysis system, comprising:
the connectivity analysis module is used for extracting connectivity data of the network instance from a preset database and obtaining a connectivity analysis result of the distributed cache according to the connectivity data;
the data acquisition module is used for acquiring log data of a log center of the network controller and acquiring the change event data according to the log data;
the transformation self-adaptation module is used for determining the variation of the connectivity analysis result according to the transformation event data and the connectivity analysis result and updating the connectivity analysis result according to the variation;
the calculation analysis module is used for generating a self-adaptive analysis result of the cloud network according to the updated connectivity analysis result;
the connectivity analysis module comprises an object recognition unit, a scene recognition unit and a path calculation unit; wherein, the liquid crystal display device comprises a liquid crystal display device,
the object identification unit is used for carrying out pattern matching on the database and identifying different types of network instances in the database according to the network ID;
the scene recognition unit is used for obtaining a communication scene recognition result of the current type network instance through the resource relation data and the routing data stored in the database;
the path calculation unit is used for calculating a communication path according to the communication scene recognition result and the route data to obtain the connectivity analysis result;
the variable adaptation module comprises:
the associated network instance unit is used for obtaining the configuration event data and associated data of the network instances of different types according to the resource relation data;
the event aggregation unit is used for aggregating the associated data according to the instance dimension to obtain change instance data;
and the connectivity change unit is used for updating the connectivity analysis result of the change instance data according to the connectivity data of the change instance data.
4. The system of claim 3, wherein after the adaptation module, the system further comprises:
the connectivity query module is used for querying the updated connectivity analysis result so as to trigger the analysis of the connectivity data by the connectivity analysis module in real time according to the query result; wherein the query results include connectivity analysis results of the query that are not stored in the distributed cache.
5. A computer device comprising a processor and a memory;
wherein the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory for implementing the cloud network oriented adaptive connectivity analysis method according to any of claims 1-2.
6. A non-transitory computer readable storage medium, having stored thereon a computer program, which when executed by a processor, implements the cloud network oriented adaptive connectivity analysis method according to any of claims 1-2.
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