CN111130854A - Multilayer topology automatic discovery method - Google Patents
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Abstract
The invention relates to the technical field of network communication, in particular to a multilayer topology automatic discovery method, which comprises the following steps: step 1: establishing a resource object and an incidence relation model; step 2: a multi-level topology automatic discovery and generation algorithm; and step 3: a data center topological structure analysis function based on a graph database technology; and 4, step 4: a topology intelligent management and maintenance strategy; and 5: and (5) researching a topological structure optimization and maintenance method. Aiming at the problems in the process of managing and optimizing IT infrastructure data of a national network company data center, a resource object model is established by establishing a description method of unified data center infrastructure resources from a topological structure of a management prerequisite, a network topology, a deployment architecture topology and a service view multilevel topology self-discovery algorithm facing national network services are researched, and the analysis, optimization and autonomy of a multilevel topological structure of the data center are completed by combining a graph database technology, so that the full life cycle management of resource objects is realized.
Description
Technical Field
The invention relates to the technical field of network communication, in particular to a multilayer topology automatic discovery method.
Background
Network topology discovery refers to discovering network elements and determining interconnection relationships between network elements (e.g., routers, gateways, bridges, switches, etc.). Network faults can be positioned through the network topological structure information, network bottlenecks are found, the current conditions of the network and the like are known more clearly, and therefore the whole network is optimized and managed better.
At present, the phenomenon that the full-topology technology of the IT infrastructure cannot meet the requirement of service development speed exists in the related operation and maintenance of the actual IT infrastructure; with the deepening of the informatization degree of a company, the rapid development of services leads to more and more complicated systems, more and more devices and more complex architectures, the frequent construction and maintenance brings about the change of assets and configuration, and the requirements on operation and maintenance are higher and higher. The current single-level topology (network topology) lacks comprehensive multi-level topology information, the topology technology is weak, and the latest IT architecture topology structure and the relation between levels cannot be obtained.
In view of this, a multi-layer topology automatic discovery method is proposed to solve the above problems.
Disclosure of Invention
The present invention provides a method for automatically discovering a multi-layer topology, so as to solve the above problems.
In order to achieve the above purpose, the invention provides the following technical scheme:
a method of multi-tier topology auto-discovery, the method comprising:
step 1: establishing a resource object and an incidence relation model;
step 2: a multi-level topology automatic discovery and generation algorithm;
and step 3: a data center topological structure analysis function based on a graph database technology;
and 4, step 4: a topology intelligent management and maintenance strategy;
and 5: and (5) researching a topological structure optimization and maintenance method.
Specifically, the step 1 of establishing the resource object and association relation model includes the following steps:
step 101: formulating a resource object subdivision strategy according to the IT architecture of the national network company;
step 102: and researching a resource object association relation model according to a resource object subdivision strategy.
Specifically, the step 101 of formulating a resource object subdivision policy according to the IT architecture of the national network company includes the following two methods:
the top-down method: according to a service directory externally provided by an enterprise, combing the service directory in the sequence of 'business service → IT system → IT component';
the bottom-up approach: the combing is performed in the order of "internal IT component → IT service".
Specifically, the step 2 multi-level topology automatic discovery and generation algorithm includes the following steps:
step 201: the SNMP-based network topology discovery method comprises the steps of carrying out active equipment check on a specified network by combining ICMP, ARP and SNMP to obtain all active equipment, obtaining basic information of the equipment through the SNMP, determining the type of the equipment according to the basic information, and obtaining information of corresponding equipment according to the type of the equipment;
step 202: the network topology discovery method based on the universal protocol judges the connection relation of each switch according to an cdp neighbor table, a port ifIndex, a port corresponding table and a self-learning table of the switch;
step 203: in the network topology discovery method based on the routing protocol, all equipment nodes of TraceRoute can obtain the routing topology relation of relevant equipment according to the returned routing path.
Specifically, the step 3 is based on the data center topology analysis function of the graph database technology, and comprises the data center topology analysis system function based on the graph database, wherein the mutual relation between the IT resources and the resources is expressed by a graph, and the data center topology analysis system function comprises function module design, performance index design and a communication mechanism.
Specifically, the step 4 of intelligent topology management and maintenance strategy includes the following steps:
step 401: according to a topological intelligent management strategy, strongly adapting to the resource object quantity scene to complete topological display;
step 402: and sensing the change state of the IT infrastructure resource object, finishing the timely updating of the topology and realizing the full life cycle management of the resource object.
Specifically, the step 5 of researching the topological structure optimization and maintenance method comprises the following steps:
step 501: according to the basic architecture topology dynamic sensing technology, a self-governing model of an IT architecture is researched, and IT architecture change is reflected in real time;
step 502: and formulating a system architecture dynamic evaluation system based on the national network service characteristics and the architecture rules.
The method has the advantages that aiming at the main problems in the process of managing and optimizing the IT infrastructure data of the national network company data center, a resource object model is established by establishing a description method of unified data center infrastructure resources from a topological structure of a management prerequisite condition, a network topology, a deployment architecture topology and a business view multilevel topology self-discovery algorithm facing national network business are researched, and the analysis, optimization and autonomy of the multilevel topological structure of the data center are completed by combining a graph database-based technology, so that the full life cycle management of resource objects is realized.
Drawings
FIG. 1 is a diagram of the multi-level topology automatic generation display process of the present invention;
FIG. 2 is a diagram of an association model according to the present invention;
FIG. 3 is a process diagram of the multi-level topology auto-discovery and generation algorithm of the present invention;
FIG. 4 is a diagram of the IT operation data association rule knowledge base construction according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
According to the data center IT infrastructure multilayer topological structure automatic discovery and intelligent management technology research, a data center IT infrastructure resource object self-discovery technology is researched, automatic discovery is conducted on network resources, server resources and application software resources, and a resource object association relation model is established; based on a graph database technology, a scene with a large number of resource objects is strongly adapted, IT infrastructure resources and the interrelation among the resources are automatically and efficiently displayed, and finally, the automatic generation and display of multilayer topologies such as a data center network topology, a physical topology and an application topology are realized; seamless switching and automatic updating can be realized among multilevel topologies, and IT architecture topology display with different visual angles is provided aiming at different roles and different service requirements. Thus, referring to FIG. 1, the present invention is divided into 4 sub-contents.
Referring to fig. 2, in the resource object and association relationship model establishment and resource object model design method of the IT infrastructure according to the present invention, a resource object subdivision strategy is formulated according to the characteristics of the IT architecture of the national network company, and the depth and the breadth of resource object subdivision are determined; and researching the association relation of the resource objects according to the object subdivision strategy, and establishing a resource object model which takes the service as a core, is attached to the service and has reasonable granularity.
Associative relationship combing can generally use two methods:
the top-down method: enterprises are generally required to firstly clearly identify service directories provided externally and then to comb the service directories in the order of "business service → IT system → IT component".
The bottom-up approach: then, in the reverse flow, the relationship of the internal IT components is first sorted, and then the IT components are gradually mapped to the IT service logical relationship, so that what middleware, database users, instances and table spaces are used by the service system, which operating system runs on, what IP address is used, which PC server the service system is installed on, through which port of which switch the PC server is connected to the network, how the PC server is connected to the storage, in which cabinet and machine room the PC server is stored, and through which breaker and UPS the PC server is powered on, etc. can be obtained.
Referring to fig. 3, the multi-level topology automatic discovery and generation algorithm of the present invention researches a network topology automatic discovery algorithm based on main stream protocols such as SNMP, ARP, ICMP, etc., and designs a topology algorithm adapted to an IT infrastructure of a data center of a national network company in combination with service characteristics of the national network company; the method realizes automatic capture of the data center network and related equipment aiming at different layers of the network system structure involved in network topology self-discovery; further fusing multiple protocols such as SSH, Telnet, JDBC, JMX, WMI, SNMP and the like, researching a data center software and hardware self-discovery algorithm, and realizing second-level self-discovery of soft and hard resources; and finally, combining a resource object model to realize automatic generation of the IT basic multi-layer topological structure of the data center.
The data center topological structure analysis function based on the graph database technology is used for researching the data center topological analysis system function based on the graph database, and expressing the IT resources and the interrelation among the resources by using a graph, wherein the data center topological structure analysis function comprises functional module design, performance index design, a communication mechanism and the like; techniques for extracting data table structure data from a conventional relational database or file system and corresponding translation to graph data points and edge type data are investigated.
The intelligent management and maintenance strategy of the topology, which is disclosed by the invention, researches the intelligent management strategy of the topology, strongly adapts to the scene of the quantity of resource objects and completes automatic and efficient topology display; rapidly sensing the change state of the IT infrastructure resource object, finishing the timely updating of the topology and realizing the full life cycle management of the resource object; meanwhile, the IT architecture topology display with different visual angles is provided according to different roles and different service requirements, and seamless switching is realized among multi-level topologies.
According to the topological structure optimization and maintenance method, a self-governing model of an IT framework is researched by means of a basic framework topology dynamic perception technology, and the IT framework change is reflected in real time; and meanwhile, a system architecture dynamic evaluation system is formulated based on national network service characteristics and architecture rules, architecture changes and configuration change changes are scored in real time, and an optimized data basis is provided for operation and maintenance personnel of the IT architecture of the data center.
Furthermore, the invention respectively carries out the following content researches on the service and data characteristics of the IT basic architecture system of the data center of the national power grid company:
1. building IT infrastructure operation data clustering model
The operation data of the current IT infrastructure, such as alarms, faults, logs, performance and the like, is large in quantity and complex in variety and troublesome to process. Firstly, marking original unordered data such as alarms, faults, logs, performance and the like, and converting the data into label type data; the first step of establishing the IT operation data association rule knowledge base is to accurately cluster data, then accurately classify the data according to a clustering result, design an IT infrastructure operation data clustering method facing a national network company data center and an application model thereof, and prepare for constructing the knowledge base in the next step.
2. Creating graph database rule design and analysis models
The relational database applied in the existing data center has poor effect of storing 'relational' data, the query is complex and slow and exceeds expectation, and the unique design of the graphic database can make up for the defect. Compared with the traditional relational database technology, the graph database technology has great technical advantages in the aspect of application based on a network type data structure; on the aspects of system modeling and data management, a large number of invalid links can be removed, the required memory is smaller, the query speed is higher, the data is easier to update, and the expression mode is more intuitive; by adopting a message-driven distributed system architecture and a highly parallelized algorithm, the computing efficiency of the electric power system with the scale of more than one million nodes is greatly improved.
A graph database rule design and analysis model of the association rule knowledge base is established, a foundation is established for application of graph database technology in a data center, and a solution thought with great potential is provided for data management and high-speed analysis and calculation of the data center.
3. Design and construction of IT operation data association rule knowledge base
After clustering and classifying original operation data such as alarm, fault, log, performance and the like, establishing a relation model of multi-dimensional operation data, mining potential association relation of the multi-source operation data based on causal relation and time sequence, and establishing an operation data association rule knowledge base.
The first step of constructing the IT infrastructure operation data association rule knowledge base of the national network data center is to process increasingly complex and huge system operation data such as alarm, fault, log, performance and the like, perform cluster classification, construct an IT infrastructure operation data clustering model, mark original disordered alarm, fault, log, performance and the like data, and convert the original disordered alarm, fault, log, performance and the like data into label type data.
When the data center operation source data is converted into system event data, the category attribute in the operation source data is required to be used as the category of the corresponding system event data; the system operation source data has no category attribute, so when the data of the original information system operation source data such as alarm, fault, log, performance and the like are converted into the system event data, the system operation source data needs to be labeled by categories first, and then the system event data is converted into corresponding system events based on the categories of the data; the class marking of the system operation data is divided into two processes of clustering and classifying. The clustering process finishes the work of extracting the characteristics of the operation data categories of the information system and constructing a category characteristic knowledge base; and finishing the operation data without class marking in the classification process, and performing class matching and marking according to a class characteristic knowledge base. And accurately classifying data such as alarms, faults, logs, performances and the like according to the class characteristic knowledge base, constructing an IT infrastructure operation data clustering model, and preparing for constructing an association rule knowledge base in the next step.
Referring to fig. 4, the graph database rule design and analysis model establishment of the association rule knowledge base adopted in the invention is to study a graph database modeling method facing the operation data management of a power grid data center aiming at the study and application of a graph database technology in the data center, closely link the business logic required by the data center with the modeling language of a graph database, and form a plurality of data analysis models according to the rules and the relations by designing the rules of points and edges through the modeling language; the method for further improving the data query performance of the data center by utilizing the characteristic of dynamic real-time update of the graph database is researched.
According to the invention, through the multilayer topology automatic discovery based on the data resource object management model, the topology containing resource objects of each layer from the network equipment to the upper application layer can be automatically generated, the data center IT architecture topological relation is truly reflected, and meanwhile, the system can automatically update the model according to the change of the sensing configuration and change of the system architecture in real time.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, but rather as the intention of all modifications, equivalents, improvements, and equivalents falling within the spirit and scope of the invention.
Claims (7)
1. A method for multi-tier topology auto-discovery, the method comprising:
step 1: establishing a resource object and an incidence relation model;
step 2: a multi-level topology automatic discovery and generation algorithm;
and step 3: a data center topological structure analysis function based on a graph database technology;
and 4, step 4: a topology intelligent management and maintenance strategy;
and 5: and (5) researching a topological structure optimization and maintenance method.
2. The method for automatically discovering the multi-layer topology according to claim 1, wherein the step 1 of establishing a resource object and association relation model comprises the following steps:
step 101: formulating a resource object subdivision strategy according to the IT architecture of the national network company;
step 102: and researching a resource object association relation model according to a resource object subdivision strategy.
3. The method according to claim 2, wherein the step 101 of formulating the resource object subdivision policy according to the IT architecture of the national network company includes the following two methods:
the top-down method: according to a service directory externally provided by an enterprise, combing the service directory in the sequence of 'business service → IT system → IT component';
the bottom-up approach: the combing is performed in the order of "internal IT component → IT service".
4. The method for automatically discovering the multi-level topology according to claim 1, wherein the step 2 multi-level topology automatic discovery and generation algorithm comprises the following steps:
step 201: the SNMP-based network topology discovery method comprises the steps of carrying out active equipment check on a specified network by combining ICMP, ARP and SNMP to obtain all active equipment, obtaining basic information of the equipment through the SNMP, determining the type of the equipment according to the basic information, and obtaining information of corresponding equipment according to the type of the equipment;
step 202: the network topology discovery method based on the universal protocol judges the connection relation of each switch according to an cdp neighbor table, a port ifIndex, a port corresponding table and a self-learning table of the switch;
step 203: in the network topology discovery method based on the routing protocol, all equipment nodes of TraceRoute can obtain the routing topology relation of relevant equipment according to the returned routing path.
5. The method according to claim 1, wherein step 3 is based on the data center topology analysis function of graph database technology, and comprises the data center topology analysis system function based on graph database, and the IT resources and the interrelations among the resources are expressed by graph, including function module design, performance index design and communication mechanism.
6. The method for automatically discovering multi-layer topology according to claim 1, wherein the step 4 topology intelligent management and maintenance strategy comprises the following steps:
step 401: according to a topological intelligent management strategy, strongly adapting to the resource object quantity scene to complete topological display;
step 402: and sensing the change state of the IT infrastructure resource object, finishing the timely updating of the topology and realizing the full life cycle management of the resource object.
7. The method for automatically discovering multi-layer topology according to claim 1, wherein the step 5 topology optimization and maintenance method research comprises the following steps:
step 501: according to the basic architecture topology dynamic sensing technology, a self-governing model of an IT architecture is researched, and IT architecture change is reflected in real time;
step 502: and formulating a system architecture dynamic evaluation system based on the national network service characteristics and the architecture rules.
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