CN116828513A - Real-time maintenance method for mobile communication network - Google Patents
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Abstract
The invention relates to the field of network communication, and discloses a mobile communication network real-time maintenance method, which comprises the following steps: step 1: inserting a designated network monitoring system, a sensor and user equipment, and collecting communication data in a mobile communication link; step 2: the method comprises the steps of analyzing and processing collected communication data, identifying abnormal behaviors in a communication network by using a machine learning algorithm, detecting abnormal data packets, attack behaviors and abnormal resource parameters in a mobile communication link, and outputting performance indexes; by collecting and processing data in real time, abnormal behaviors in the mobile communication network can be timely found and processed, the stability and usability of the network are improved, the abnormal behaviors in the mobile communication network can be automatically identified, the detection accuracy and efficiency of the abnormal behaviors are further improved, maintenance behaviors and results are recorded, and the results can be traced and verified through analysis of the maintenance records and the results.
Description
Technical Field
The invention relates to the technical field of network communication, in particular to a mobile communication network real-time maintenance method.
Background
With the rapid increase of the number of mobile communication users and data traffic, network congestion becomes a common problem, security risks such as network attack, hacking invasion and the like exist in a mobile communication network, and the risks can lead to user data leakage, network paralysis and the like, so that the faults and defects can be timely found and repaired through real-time maintenance, and the normal operation and high availability of the network are ensured;
however, the existing mobile communication network real-time maintenance method has disadvantages, such as:
1. the existing mobile communication network maintenance method generally only depends on manual or backward maintenance systems to monitor and process, lacks timeliness and accuracy, and meanwhile, maintenance results cannot be effectively traced and verified, so that maintenance effects and improvement strategies are difficult to evaluate;
2. the maintenance means of the mobile communication network is difficult to continuously improve the performance, the requirements of users on the speed, the quality and the reliability are difficult to meet, and the problems of hardware faults, software defects and the like possibly exist in the mobile communication network, and the problems can lead to network interruption, data loss, service quality reduction and the like, so that the problems are difficult to be timely checked and solved.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides a mobile communication network real-time maintenance method, which can effectively solve the problems that the mobile communication network maintenance method in the prior art is usually monitored and processed only by manual or backward maintenance systems, the timeliness and the accuracy are lacking, meanwhile, maintenance results cannot be effectively traced and verified, so that the maintenance effect and the improvement strategy are difficult to evaluate, the performance of the maintenance means of the mobile communication network is difficult to continuously improve, the requirements of users on the speed, the quality and the reliability are difficult to meet, and the problems of hardware faults, software defects and the like possibly exist in the mobile communication network, and the problems of network interruption, data loss, service quality reduction and the like are possibly caused, so that the problems of timely investigation and solution are difficult.
In order to achieve the above object, the present invention discloses a mobile communication network real-time maintenance method, which comprises the following steps:
step 1: inserting a designated network monitoring system, a sensor and user equipment, and collecting communication data in a mobile communication link;
step 2: the method comprises the steps of analyzing and processing collected communication data, identifying abnormal behaviors in a communication network by using a machine learning algorithm, detecting abnormal data packets, attack behaviors and abnormal resource parameters in a mobile communication link, and outputting performance indexes;
step 3: when judging that the abnormal situation exists, immediately intercepting abnormal flow, limiting network access of an abnormal user, sending an alarm to a management end, acquiring the identified abnormal behavior parameters, comprehensively analyzing, acquiring the characteristics of the abnormal behavior parameters, comparing and correlating the characteristics with other related data, and determining the reason and the source of the abnormal situation;
step 4: analyzing the type and severity of the abnormal behavior, and calling corresponding maintenance measures;
step 5: the system records and stores all maintenance actions and maintenance results, intercepted flow and limited users, and performs tracing;
step 6: continuously monitoring the abnormal source, collecting feedback information, returning the system to a normal state if the abnormal source does not feed back data in a preset monitoring period, and uploading an alarm to a management end if the abnormal source still feeds back data in the preset monitoring period;
step 7: analyzing and evaluating the maintenance effect by using statistical analysis and visualization technology through the recorded maintenance result, and periodically generating performance indexes and maintenance logs;
step 8: and analyzing the maintenance log and report, optimizing maintenance strategies and flows, and displaying maintenance effects and network conditions by using a visualization tool.
Still further, the communication data in step 1 includes: network device status, traffic data, and log records.
Further, the performance indexes output in the step 2 include: network delay, data transmission rate, and packet loss rate.
Further, in the machine learning process in the step 2, an abnormal behavior recognition model is designed and trained to analyze abnormal data traffic, abnormal connection requests and abnormal user behaviors in the mobile communication network.
Further, the comprehensive analysis in the step 3 includes the following steps: and checking configuration and upgrading conditions of network equipment and checking network topology problems.
Further, the maintenance measure in step 4 includes: adjusting network resource allocation, optimizing routing configuration, isolating abnormal nodes or traffic and intrusion firewalls.
Still further, the tracing process in step 5 includes: recording and storing time, type, influence range, maintenance measures and maintenance result information of abnormal behavior by using a database and a log file;
when the result is required to be traced and verified, searching maintenance results according to time, type and influence range conditions, and acquiring maintenance records and results in a specified time period;
and searching the obtained maintenance results, checking the detailed information in each record, knowing the specific situation of the abnormal behavior and the maintenance measures and results adopted, and finishing the cause and the backtracking of the maintenance process.
Furthermore, the maintenance record judges the maintenance effect by comparing the network performance indexes before and after maintenance with the user feedback, if the maintenance result reaches the expected effect, the maintenance is judged to be successful, otherwise, the improvement opinion is uploaded.
Furthermore, the performance index generated periodically in the step 7 is displayed by obtaining the average downloading delay of the content through D2D communication, and the calculation formula is as follows:
；
in the method, in the process of the invention,representing the average download latency; />Representing the bandwidth of the D2D communication link; />Representing a distance average of the D2D communication link; />Representing D2D representing user caching content file +.>A number average of encoded data packets; p represents the transmit power; />Is Gaussian white noise power; k and w represent the path loss constant and the exponent, respectively; />Representing the number of segments of the file that are segmented; />Representing a set of segmented fragments.
Furthermore, in the optimization process of the maintenance policy in step 8, the content of the cacheable file is assisted by other servers in the cooperation domain until the transmission delay is reduced to a preset threshold, and the calculation formula for assisting in transmitting the energy consumption is as follows:
；
wherein E represents the power consumption of the auxiliary transmission; n represents the power consumption of the cache;representing the number of user requests during a time period t; />Representing the normalized length of the file; />Representing the average cooperative transmission rate.
Compared with the known public technology, the technical scheme provided by the invention has the following beneficial effects:
1. the invention can timely find and process the abnormal behavior in the mobile communication network by collecting and processing the data in real time, improve the stability and the usability of the network, automatically identify the abnormal behavior in the mobile communication network, further improve the detection accuracy and the detection efficiency of the abnormal behavior, record the maintenance behavior and the result, trace and verify the result by analyzing the maintenance record and the result, evaluate the maintenance effect, find the improved direction, improve the maintenance accuracy and the maintenance efficiency, and finally improve the stability and the reliability of the mobile communication network.
2. The invention can timely discover and repair the faults and defects through real-time maintenance, ensure the normal operation and high availability of the network, monitor the network traffic condition, timely adjust the distribution of network resources, avoid congestion, ensure the smooth communication experience of users, monitor and analyze network security events, timely take corresponding security measures, ensure the security and privacy protection of user data, monitor network performance indexes such as delay, transmission rate, packet loss rate and the like, and perform optimization strategies to improve the network performance and user experience.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
Fig. 1 is a flow chart of a method for real-time maintenance of a mobile communication network.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. It will be apparent that the described embodiments are some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention is further described below with reference to examples.
Example 1: the method for maintaining the mobile communication network in real time in this embodiment, as shown in fig. 1, includes the following steps:
step 1: and (2) intervening a designated network monitoring system, a sensor and user equipment, and collecting communication data in a mobile communication link, wherein the communication data in the step (1) comprises the following steps: network equipment status, traffic data and log records;
step 2: for analyzing and processing the collected communication data, identifying abnormal behavior in the communication network by using a machine learning algorithm, detecting abnormal data packets, attack behaviors and abnormal parameters of resources in the mobile communication link, and outputting performance indexes, wherein the performance indexes output in the step 2 comprise: network delay, data transmission rate and packet loss rate, wherein in the machine learning process in the step 2, an abnormal behavior recognition model is designed and trained to analyze abnormal data traffic, abnormal connection requests and abnormal user behaviors in the mobile communication network;
step 3: when the abnormality is judged to exist, the abnormal flow is immediately intercepted, the network access of an abnormal user is limited, an alarm is sent to a management end, the identified abnormal behavior parameters are obtained, the characteristics of the abnormal behavior parameters are obtained after comprehensive analysis, the characteristics are compared with other related data and are associated, the cause and the source of the abnormality are determined, and the comprehensive analysis in the step 3 comprises the following steps: checking configuration and upgrading conditions of network equipment and checking network topology problems;
step 4: analyzing the type and severity of the abnormal behavior, and calling corresponding maintenance measures, wherein the maintenance measures in the step 4 comprise: adjusting network resource allocation, optimizing routing configuration, isolating abnormal nodes or traffic and intrusion firewalls;
step 5: the system records and stores all maintenance actions and maintenance results, intercepted flow and limited users, and performs tracing;
step 6: continuously monitoring the abnormal source, collecting feedback information, returning the system to a normal state if the abnormal source does not feed back data in a preset monitoring period, and uploading an alarm to a management end if the abnormal source still feeds back data in the preset monitoring period;
step 7: analyzing and evaluating the maintenance effect by using statistical analysis and visualization technology through the recorded maintenance result, and periodically generating performance indexes and maintenance logs;
step 8: and analyzing the maintenance log and report, optimizing maintenance strategies and flows, and displaying maintenance effects and network conditions by using a visualization tool.
When the embodiment is implemented, through real-time collection and processing of data, abnormal behaviors in a mobile communication network can be timely found and processed, the stability and usability of the network are improved, the abnormal behaviors in the mobile communication network can be automatically identified, the detection accuracy and efficiency of the abnormal behaviors are further improved, maintenance behaviors and results are recorded, through analysis of the maintenance records and the results, the faults and defects can be timely found and repaired through real-time maintenance, the normal operation and the high usability of the network are ensured, the network flow condition can be monitored, the distribution of network resources is timely adjusted, congestion is avoided, the smooth communication experience of a user is ensured, the network security event is monitored and analyzed, corresponding security measures are timely adopted, the security and privacy protection of the user data are ensured, the network performance indexes such as delay, transmission rate and packet loss rate are monitored, an optimization strategy is performed, and the network performance and user experience are improved.
Example 2: the embodiment further provides a tracing process, where the tracing process in step 5 includes: recording and storing time, type, influence range, maintenance measures and maintenance result information of abnormal behavior by using a database and a log file;
when the result is required to be traced and verified, searching maintenance results according to time, type and influence range conditions, and acquiring maintenance records and results in a specified time period;
and searching the obtained maintenance results, checking the detailed information in each record, knowing the specific situation of the abnormal behavior and the maintenance measures and results adopted, and finishing the cause and the backtracking of the maintenance process.
And comparing the network performance indexes before and after maintenance with user feedback to judge the maintenance effect, judging that the maintenance is successful if the maintenance result reaches the expected effect, and otherwise, uploading the improvement opinion.
When the embodiment is specifically implemented, the result tracing and verification can be performed, the maintenance effect can be evaluated, the improvement direction is found, the maintenance accuracy and efficiency are improved, and the stability and reliability of the mobile communication network are finally improved.
Example 3: in this embodiment, the performance index generated periodically in step 7 is displayed by obtaining an average download delay of the content through D2D communication, and the calculation formula is as follows:
；
in the method, in the process of the invention,representing the average download latency; />Representing the bandwidth of the D2D communication link; />Representing a distance average of the D2D communication link; />Representing D2D representing user caching content file +.>A number average of encoded data packets; p represents the transmit power; />Is Gaussian white noise power; k (k)And w represents a path loss constant and an exponent, respectively; />Representing the number of segments of the file that are segmented; />Representing a set of segmented segments;
in the optimization process of the maintenance strategy in the step 8, the content of the cacheable file is assisted by other servers in the cooperation domain until the transmission delay is reduced to a preset threshold value, and the calculation formula for assisting in transmitting the energy consumption is as follows:
；
wherein E represents the power consumption of the auxiliary transmission; n represents the power consumption of the cache;representing the number of user requests during a time period t; />Representing the normalized length of the file; />Representing the average cooperative transmission rate.
In summary, the invention can timely find and process the abnormal behavior in the mobile communication network by collecting and processing the data in real time, improve the stability and usability of the network, automatically identify the abnormal behavior in the mobile communication network, further improve the detection accuracy and efficiency of the abnormal behavior, record the maintenance behavior and result, trace and verify the result by analyzing the maintenance record and result, evaluate the maintenance effect, find the improved direction, improve the maintenance accuracy and efficiency, and finally improve the stability and reliability of the mobile communication network;
through real-time maintenance, the faults and defects can be timely found and repaired, normal operation and high availability of a network are ensured, network traffic conditions can be monitored, distribution of network resources is timely adjusted, congestion is avoided, smooth communication experience of users is ensured, network safety events are monitored and analyzed, corresponding safety measures are timely taken, safety and privacy protection of user data are ensured, network performance indexes such as delay, transmission rate, packet loss rate and the like are monitored, and optimization strategies are carried out, so that network performance and user experience are improved.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; while the invention has been described in detail with reference to the foregoing embodiments, it will be appreciated by those skilled in the art that variations may be made in the techniques described in the foregoing embodiments, or equivalents may be substituted for elements thereof; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A method for real-time maintenance of a mobile communication network, comprising the steps of:
step 1: inserting a designated network monitoring system, a sensor and user equipment, and collecting communication data in a mobile communication link;
step 2: the method comprises the steps of analyzing and processing collected communication data, identifying abnormal behaviors in a communication network by using a machine learning algorithm, detecting abnormal data packets, attack behaviors and abnormal resource parameters in a mobile communication link, and outputting performance indexes;
step 3: when judging that the abnormal situation exists, immediately intercepting abnormal flow, limiting network access of an abnormal user, sending an alarm to a management end, acquiring the identified abnormal behavior parameters, comprehensively analyzing, acquiring the characteristics of the abnormal behavior parameters, comparing and correlating the characteristics with other related data, and determining the reason and the source of the abnormal situation;
step 4: analyzing the type and severity of the abnormal behavior, and calling corresponding maintenance measures;
step 5: the system records and stores all maintenance actions and maintenance results, intercepted flow and limited users, and performs tracing;
step 6: continuously monitoring the abnormal source, collecting feedback information, returning the system to a normal state if the abnormal source does not feed back data in a preset monitoring period, and uploading an alarm to a management end if the abnormal source still feeds back data in the preset monitoring period;
step 7: analyzing and evaluating the maintenance effect by using statistical analysis and visualization technology through the recorded maintenance result, and periodically generating performance indexes and maintenance logs;
step 8: and analyzing the maintenance log and report, optimizing maintenance strategies and flows, and displaying maintenance effects and network conditions by using a visualization tool.
2. The method for real-time maintenance of a mobile communication network according to claim 1, wherein the communication data in step 1 comprises: network device status, traffic data, and log records.
3. The method according to claim 1, wherein the performance index outputted in step 2 comprises: network delay, data transmission rate, and packet loss rate.
4. The method according to claim 1, wherein during the machine learning in the step 2, an abnormal behavior recognition model is designed and trained to analyze abnormal data traffic, abnormal connection requests and abnormal user behaviors in the mobile communication network.
5. The method for real-time maintenance of a mobile communication network according to claim 1, wherein the comprehensive analysis in step 3 comprises the following steps: and checking configuration and upgrading conditions of network equipment and checking network topology problems.
6. The method according to claim 1, wherein the maintenance in step 4 comprises: adjusting network resource allocation, optimizing routing configuration, isolating abnormal nodes or traffic and intrusion firewalls.
7. The method for real-time maintenance of a mobile communication network according to claim 1, wherein the tracing process in step 5 comprises: recording and storing time, type, influence range, maintenance measures and maintenance result information of abnormal behavior by using a database and a log file;
when the result is required to be traced and verified, searching maintenance results according to time, type and influence range conditions, and acquiring maintenance records and results in a specified time period;
and searching the obtained maintenance results, checking the detailed information in each record, knowing the specific situation of the abnormal behavior and the maintenance measures and results adopted, and finishing the cause and the backtracking of the maintenance process.
8. The method according to claim 7, wherein the maintenance record compares the network performance indexes before and after maintenance with user feedback to determine the maintenance effect, and if the maintenance result reaches the expected effect, the maintenance is determined to be successful, otherwise, the improvement opinion is uploaded.
9. The method for maintaining a mobile communication network in real time according to claim 1, wherein the performance index generated periodically in step 7 is displayed by obtaining an average download delay of the content through D2D communication, and the calculation formula is as follows:
；
in the method, in the process of the invention,representing the average download latency; />Representing the bandwidth of the D2D communication link; />Representing a distance average of the D2D communication link; />Representing D2D representing user caching content file +.>A number average of encoded data packets; p represents the transmit power; />Is Gaussian white noise power; k and w represent the path loss constant and the exponent, respectively; />Representing the number of segments of the file that are segmented; />Representing a set of segmented fragments.
10. The method according to claim 1, wherein in the optimization process of the maintenance policy in step 8, the content of the cacheable file is assisted by other servers in the cooperation domain until the transmission delay is reduced to a preset threshold, and the calculation formula for assisting in transmitting the energy consumption is as follows:
;
wherein E represents the power consumption of the auxiliary transmission; n represents the power consumption of the cache;representing the number of user requests during a time period t;representing the normalized length of the file; />Representing the average cooperative transmission rate.
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