CN116405407A - Network management method and system based on big data - Google Patents

Abstract

The invention discloses a network management method and system based on big data, which relate to the field of network management and solve the problems that the conventional daily network management operation and maintenance of a network company needs to be manually performed, the intelligent degree is low, the operation and maintenance efficiency is underground, and the workload of personnel is increased. The method can effectively and intelligently monitor and operate and maintain the network server, and can intelligently monitor and control safety and faults and operation at the same time, thereby realizing the effect of effectively saving energy consumption.

Description

A network management method and system based on big data

technical field

The invention relates to the field of network management, in particular to a network management method and system based on big data.

Background technique

Network management includes the use, integration, and coordination of hardware, software, and human resources to monitor, test, configure, analyze, evaluate, and control network resources so that some network requirements, such as real-time operational performance, can be met at a reasonable price , service quality, etc. In addition, when the network fails, it can report and deal with it in time, and coordinate and maintain the efficient operation of the network system. Network management is often referred to simply as network management.

However, some network companies now set up monitoring terminals for network servers in their daily operations to ensure real-time monitoring of the operation of each network server in order to ensure the stable operation of the server. When risks, fluctuations, etc. are found, it is necessary to There are operation and maintenance personnel to deal with it in a timely manner, but the operation and maintenance management method that requires manual processing is relatively inefficient, and it also increases the workload of relevant personnel, which is not convenient for intelligent operation and maintenance management. Therefore, a network management method and system based on big data is proposed.

Contents of the invention

The purpose of the present invention is to provide a network management method and system based on big data, which solves the problem that the daily network management operation and maintenance of existing network companies need to be carried out manually, and the degree of intelligence is low, which leads to low operation and maintenance efficiency and increases the burden of personnel. workload problem.

In order to achieve the above object, the present invention provides the following technical solution: a network management method based on big data, comprising the following steps:

S1: Monitor the running status of each network server through the running status detection system connected to the server detection system;

S2: The running status monitoring system is connected to the time recording system, and through it is connected to the network speed monitoring system, power consumption monitoring system, storage redundancy monitoring system, network flow monitoring system, and computer room temperature monitoring system, which is convenient for multiple server groups Effective real-time monitoring of network speed, power consumption, storage redundancy, network traffic, and computer room temperature, and feedback to the operating status monitoring system;

S3: The operating status monitoring system is also connected with the network speed optimization system, temperature control system, and memory control system, so that the network speed of the network server can be adjusted conveniently through the network speed optimization system, and the temperature of the computer room can be adjusted through the temperature control system. Expand the use of network servers through the memory control system, and connect new servers in parallel;

S4: As well as network speed, power consumption, storage redundancy, network traffic, and computer room monitoring and control information can also be sent to the convolutional neural network training system to train relevant data information features and establish a prediction model;

S5: Then, the convolutional neural network prediction system can also use the trained prediction model, and then the next time it receives monitoring information related to network speed, power consumption, storage redundancy, network traffic, and computer room temperature, the information data can be directly processed. Features are extracted and predicted;

S6: After predicting the results, you can directly make relevant operation adjustments to the network speed optimization system, temperature control system, and memory control system through the control command module system.

A network management system based on big data, comprising a network server, a gateway module, and a server detection system, the server detection system is connected to a plurality of network servers, the server detection system is also connected to a running status monitoring system, and each of the network servers is also Both are connected with the network speed monitoring system, power consumption monitoring system, storage redundancy monitoring system, network flow monitoring system, computer room temperature monitoring system, and the network speed monitoring system, power consumption monitoring system, storage redundancy monitoring system, network flow monitoring system, the computer room temperature monitoring system are also commonly connected with a time recording system, a server determination system, a convolutional neural network training system, and a convolutional neural network prediction system. The time recording system is connected with an operating state monitoring system, and the operating state monitoring system Also connected with network speed optimization system, temperature control system and memory control system respectively, described memory control system is connected with network server, described network speed optimization system is connected with convolutional neural network training system, and convolutional neural network training system is connected There is a convolutional neural network prediction system, the operating state monitoring system is connected to a network security monitoring system, and the network security monitoring system is connected to a fault detection system and a background control system in turn, and the server determination system is bidirectionally connected to a server detection system, and The server detection system is bidirectionally connected with a fault detection system.

Preferably, the network speed optimization system is also connected with a plurality of gateway modules, and the temperature control system is also connected with a heat dissipation system, and the heat dissipation system includes a control control module and a fan control module.

Preferably, the server detection system is used to monitor each server, the running status monitoring system is used to monitor the running status of each server, and the network security monitoring system is used to first monitor the network security when the operation is abnormal. Monitoring, the fault detection system is used to detect and troubleshoot the faults of the network server when the operation is abnormal and the network security is ruled out.

Preferably, the network speed monitoring system is used to monitor the running network speed of each network server, the power consumption monitoring system is used to monitor the power consumption of each network server, and the storage redundancy monitoring system is used to monitor each network server For the remaining storage capacity, the network flow monitoring system is used to monitor the data access flow of each network server, the computer room temperature monitoring system is used to monitor the temperature of the computer room where each network server is located, and the time recording system is used to record the above-mentioned The acquisition time corresponding to the monitoring data.

Preferably, the network speed optimization system is used to adjust the number of connected gateway modules to adjust the network speed of the network server, and the temperature control system is used to control the air conditioner control module and the fan control module, so as to achieve The fan regulates the temperature of the computer room, and the memory control system is used to control and connect a new network server to support operation when the running speed of the network server is affected by insufficient storage redundancy.

Preferably, the convolutional neural network training system is used to collect the operation data of the network server and the control data of the operation status monitoring system, extract data features for training, and train the prediction model.

Preferably, the convolutional neural network prediction system is used to input the newly obtained network server into the prediction model to obtain corresponding prediction results.

Preferably, the control command module system is used to regulate the network speed optimization system, the temperature control system, and the memory control system according to the prediction results to realize autonomous intelligent management and control of the network server.

Preferably, the data storage system is used to store and record the operation monitoring data, regulation data and prediction data of the network server.

Compared with related technologies, a network management method and system based on big data provided by the present invention has the following beneficial effects:

1. The present invention provides a network management method and system based on big data. It is convenient to monitor each The network speed, power consumption, storage redundancy, network flow, and room temperature of the network server are monitored during operation, and fed back to the operation status monitoring system, making it convenient to monitor the operation data of the network server.

2. The present invention provides a network management method and system based on big data. By setting up an operating status monitoring system, a safety monitoring system, and a fault monitoring system, it is convenient to timely and efficiently discover and process server network security issues and fault issues .

3. The present invention provides a network management method and system based on big data, through the network speed optimization system, temperature control system, and memory control system, it is convenient to carry out specific control, so that during specific operation, there is no need for too many When the air conditioner, fan, gateway module and network server are running, they can be turned off, and they can be turned on in time to reduce their energy consumption when needed.

4. The present invention provides a network management method and system based on big data. The prediction model is trained through the convolutional neural network training system, and then the prediction model is used to input new monitoring data information for prediction through the convolutional neural network prediction system. Finally, the network speed optimization system, temperature control system, and memory control system are optimized and regulated by the control command module system according to the prediction results, so that intelligent control can be performed, and the control efficiency is greatly improved.

The method enables effective and intelligent monitoring and operation and maintenance management of the network server, and at the same time, intelligently performs safety and fault monitoring, and operation regulation, thereby achieving an effective effect of saving energy consumption.

Description of drawings

Fig. 1 is a flow chart of the method of the present invention.

Fig. 2 is a system diagram of the present invention.

Detailed ways

The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them; based on The embodiments of the present invention and all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

Embodiment one:

Referring to Fig. 1-2, the present invention provides a technical solution: a network management method based on big data, comprising the following steps:

S1: Monitor the running status of each network server through the running status detection system connected to the server detection system;

S2: The running status monitoring system is connected to the time recording system, and through it is connected to the network speed monitoring system, power consumption monitoring system, storage redundancy monitoring system, network flow monitoring system, and computer room temperature monitoring system, which is convenient for multiple server groups Effective real-time monitoring of network speed, power consumption, storage redundancy, network traffic, and computer room temperature, and feedback to the operating status monitoring system;

S3: The operating status monitoring system is also connected with the network speed optimization system, temperature control system, and memory control system, so that the network speed of the network server can be adjusted conveniently through the network speed optimization system, and the temperature of the computer room can be adjusted through the temperature control system. Expand the use of network servers through the memory control system, and connect new servers in parallel;

S4: As well as network speed, power consumption, storage redundancy, network traffic, and computer room monitoring and control information can also be sent to the convolutional neural network training system to train relevant data information features and establish a prediction model;

S5: Then, the convolutional neural network prediction system can also use the trained prediction model, and then the next time it receives monitoring information related to network speed, power consumption, storage redundancy, network traffic, and computer room temperature, the information data can be directly processed. Features are extracted and predicted;

S6: After predicting the results, you can directly make relevant operation adjustments to the network speed optimization system, temperature control system, and memory control system through the control command module system.

Embodiment two:

Please refer to Figure 1-2, a network management system based on big data, including a network server, a gateway module, and a server detection system. The server detection system is connected to multiple network servers, and the server detection system is also connected to a running status monitoring system. The network servers are also connected to the network speed monitoring system, electricity consumption monitoring system, storage redundancy monitoring system, network flow monitoring system, computer room temperature monitoring system, and the network speed monitoring system, power consumption monitoring system, storage redundancy monitoring system, The network traffic monitoring system and the computer room temperature monitoring system are also connected to the time recording system, the server determination system, the convolutional neural network training system, and the convolutional neural network prediction system. The time recording system is connected to the operation status monitoring system, and the operation status monitoring system is also The network speed optimization system, the temperature control system and the memory control system are respectively connected, the memory control system is connected to the network server, the network speed optimization system is connected to the convolutional neural network training system, and the convolutional neural network training system is connected to the convolutional neural network The prediction system, the operation status monitoring system is connected to the network security monitoring system, and the network security monitoring system is connected to the fault detection system and the background control system in turn, the server confirms that the system is bidirectionally connected to the server detection system, and the server detection system is bidirectionally connected to the fault detection system .

The network speed optimization system is also connected with multiple gateway modules. The temperature control system is also connected with a cooling system. The cooling system includes a control control module and a fan control module. The network security monitoring system is used to first monitor the network security when the operation is abnormal. The detection system is used to detect and troubleshoot network server failures when the operation is abnormal and the network security is ruled out.

The server detection system is used to monitor each server, and the running status monitoring system is used to monitor the running status of each server.

Furthermore, the running status monitoring system monitors the running status. When an abnormal operation is found, the network security monitoring system is first used to monitor the network security. Fault detection is carried out, and the server determines the system to finally determine the faulty server, so as to facilitate timely and efficient discovery and processing of the server's network security problems and fault problems.

Embodiment three:

Please refer to Figure 1-2, the network speed monitoring system is used to monitor the running network speed of each network server, the power consumption monitoring system is used to monitor the power consumption of each network server, and the storage redundancy monitoring system is used to monitor the remaining power of each network server Storage capacity, the network flow monitoring system is used to monitor the data access flow of each network server, the computer room temperature monitoring system is used to monitor the temperature of the computer room where each network server is located, and the time recording system is used to record the acquisition time corresponding to the above monitoring data.

Furthermore, each network server is connected with a server detection system, which is connected with a running state monitoring system, so that the running state of each network server can be monitored conveniently, and each network server is also connected with a network speed monitoring system and a power consumption monitoring system. , Storage redundancy monitoring system, network flow monitoring system and computer room temperature monitoring system, so that it is convenient to monitor the network speed, power consumption, storage redundancy, network flow, and computer room temperature of each network server when it is running, and cooperate with the time recording system The time at which each recorded information is obtained is fed back to the operating status monitoring system, making it convenient to monitor the operating data of the network server.

Embodiment four:

Please refer to Figure 1-2. The network speed optimization system is used to adjust the number of connected gateway modules to adjust the network speed of the network server. The temperature control system is used to control the air conditioner control module and the fan control module. The fan regulates the temperature of the computer room, and the memory control system is used to regulate the connection of a new network server to support the operation when the storage redundancy is insufficient and the running speed of the network server is affected.

Furthermore, when the operation status monitoring system detects that the network server is operating normally, the network speed can be adjusted by controlling the number of connected gateway modules through the network speed optimization system, and the temperature of the computer room can be adjusted by controlling the heat dissipation system through the temperature control system. According to the remaining situation of storage redundancy, the memory control system adjusts and optimizes by adding new network servers when the storage is not enough, so that in the specific operation, there is no need for too many air conditioners, fans, gateway modules and network When the server is running, it can be turned off, and it can be turned on in time to reduce its energy consumption when needed.

Embodiment five:

Please refer to Figure 1-2. The convolutional neural network training system is used to collect the operating data of the network server and its control data from the operating status monitoring system, extract data features for training, and train the prediction model.

The convolutional neural network prediction system is used to input the newly obtained network server into the prediction model to obtain corresponding prediction results.

The control command module system is used to regulate the network speed optimization system, the temperature control system, and the memory control system according to the prediction results, so as to realize the independent intelligent management and control of the network server.

The data storage system is used to store and record the operation monitoring data, regulation data and forecast data of the network server.

Furthermore, the background control system is connected with a convolutional neural network training system, which can extract the data features from the operating data of the network server and the optimization and control data of the network speed optimization system, temperature control system, and memory control system, and then Training to form a prediction model, and then use the prediction model to input new monitoring data information for prediction through the convolutional neural network prediction system, and finally use the control command module system to optimize the network speed, temperature control system, and memory according to the prediction results. The control system is optimized for control, and at the same time, the operation monitoring data, control data and forecast data of the network server can be stored, recorded and archived through the data storage system.

Claims (10)

1. A network management method based on big data, characterized in that, comprising the following steps: S1: Monitor the running status of each network server through the running status detection system connected to the server detection system; S2: The running status monitoring system is connected to the time recording system, and through it is connected to the network speed monitoring system, power consumption monitoring system, storage redundancy monitoring system, network flow monitoring system, and computer room temperature monitoring system, which is convenient for multiple server groups Effective real-time monitoring of network speed, power consumption, storage redundancy, network traffic, and computer room temperature, and feedback to the operating status monitoring system; S3: The operating status monitoring system is also connected with the network speed optimization system, temperature control system, and memory control system, so that the network speed of the network server can be adjusted conveniently through the network speed optimization system, and the temperature of the computer room can be adjusted through the temperature control system. Expand the use of network servers through the memory control system, and connect new servers in parallel; S4: As well as network speed, power consumption, storage redundancy, network traffic, and computer room monitoring and control information can also be sent to the convolutional neural network training system to train relevant data information features and establish a prediction model; S5: Then, the convolutional neural network prediction system can also use the trained prediction model, and then the next time it receives monitoring information related to network speed, power consumption, storage redundancy, network traffic, and computer room temperature, the information data can be directly processed. Features are extracted and predicted; S6: After predicting the results, you can directly make relevant operation adjustments to the network speed optimization system, temperature control system, and memory control system through the control command module system. 2. a kind of network management system based on big data according to claim 1, comprises network server, gateway module, server detection system, and server detection system is connected with a plurality of network servers, it is characterized in that, described server detection system also A running status monitoring system is connected, and each of the network servers is also connected to a network speed monitoring system, a power consumption monitoring system, a storage redundancy monitoring system, a network flow monitoring system, and a computer room temperature monitoring system. The electricity monitoring system, the storage redundancy monitoring system, the network flow monitoring system, and the computer room temperature monitoring system are also jointly connected with a time recording system, a server determination system, a convolutional neural network training system, and a convolutional neural network prediction system. The time recording system A running state monitoring system is connected, and the running state monitoring system is also respectively connected with a network speed optimization system, a temperature control system and a memory control system, the memory control system is connected with a network server, and the network speed optimization system is connected with a convolution A neural network training system, and the convolutional neural network training system is connected with a convolutional neural network prediction system, the operation state monitoring system is connected with a network security monitoring system, and the network security monitoring system is connected with a fault detection system and a background control system in turn, The server determination system is bidirectionally connected with a server detection system, and the server detection system is bidirectionally connected with a fault detection system. 3. a kind of network management system based on big data according to claim 2, is characterized in that, described network speed optimization system is also connected with a plurality of gateway modules, and described temperature control system is also connected with cooling system, and described The cooling system includes a control control module and a fan control module. The network security monitoring system is used to first monitor the network security when the operation is abnormal, and the fault detection system is used to monitor the network server when the operation is abnormal and the network security is excluded. fault detection and troubleshooting. 4. A network management system based on big data according to claim 3, wherein the server detection system is used to monitor each server, and the operating status monitoring system is used to monitor the operating status of each server Monitor. 5. A network management system based on big data according to claim 4, wherein the network speed monitoring system is used to monitor the running network speed of each network server, and the power consumption monitoring system is used to monitor each The power consumption of network servers, the storage redundancy monitoring system is used to monitor the remaining storage capacity of each network server, the network flow monitoring system is used to monitor the data access flow of each network server, and the computer room temperature monitoring system is used to In order to monitor the temperature of the computer room where each network server is located, the time recording system is used to record the acquisition time corresponding to the above monitoring data. 6. a kind of network management system based on big data according to claim 5, is characterized in that, described network speed optimization system is used for regulating and controlling the gateway module quantity of access and adjusts the network speed that network server runs, and described temperature The control system is used to control the air conditioner control module and the fan control module, so as to adjust the temperature of the computer room through the air conditioner or the fan. The memory control system is used to control the operating speed of the network server due to insufficient storage redundancy. A new web server was plugged in to support the operation. 7. a kind of network management system based on big data according to claim 6, is characterized in that, described convolutional neural network training system is used for collecting the running data of network server and running status monitoring system to its control data, And extract the data features for training, and the prediction model at the training place. 8. A network management system based on big data according to claim 7, wherein the convolutional neural network prediction system is used to input the newly acquired network server into the prediction model to obtain corresponding prediction results. 9. A network management system based on big data according to claim 8, wherein the control instruction module system is used to regulate the network speed optimization system, the temperature control system, and the memory control system according to the prediction results Realize independent intelligence to manage and control the network server. 10. A network management system based on big data according to claim 2, wherein the data storage system is used to store and record the operation monitoring data, control data and prediction data of the network server.

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