CN112533246B - Monitoring system and method for frequent network requests of intelligent equipment - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/04—Arrangements for maintaining operational condition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/14—Session management
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/10—Scheduling measurement reports ; Arrangements for measurement reports
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W52/00—Power management, e.g. TPC [Transmission Power Control], power saving or power classes
- H04W52/02—Power saving arrangements
- H04W52/0209—Power saving arrangements in terminal devices
- H04W52/0212—Power saving arrangements in terminal devices managed by the network, e.g. network or access point is master and terminal is slave
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W76/00—Connection management
- H04W76/20—Manipulation of established connections
- H04W76/27—Transitions between radio resource control [RRC] states
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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
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- 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
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
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Abstract
The invention discloses a monitoring system and a method for frequent network requests of intelligent equipment, comprising the following steps: when RRC is released each time, counting the application triggering the network request in the RCC and generating an RRC counting result; adding one to the accumulated network request times of the application triggering the network request in the RCC; when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times, marking the application as a problem application, and pushing the problem application and network request data thereof to the appointed external equipment. The invention has the technical effects that: through analyzing the network request times of the application, the problem application with abnormal power consumption on the network request is found, a problem application developer is informed to process and repair the problem application, the searching speed of the problem application with abnormal power consumption on the network request is improved, and further power consumption is saved.
Description
Technical Field
The invention relates to network communication, in particular to a monitoring system and method for frequent network requests of intelligent equipment.
Background
As telephone watches become increasingly popular and more functional, not only are there built-in applications within the watch, but a large number of third party applications are introduced. Because of the different policies of the third party applications introduced, many applications will either keep alive in the background or have their own heartbeats. Therefore, under the condition that the watch is not in use, the electricity is consumed quickly due to many background network requests, the cruising of the telephone watch is greatly influenced, and the public praise of the product is also greatly influenced.
At present, no method is available for monitoring the type of application, the conventional means is that customer complaints consume fast electricity, then logs of a problem machine are acquired through a specific method for power consumption analysis, as the network request has little log printing information, which application frequently triggers the network request is difficult to analyze and locate, the type of application can be found only by grabbing a packet, the efficiency is low, the analysis and the location of the problem are difficult, the problem solving period is long, and the system is passive. At present, the application is forced to be closed by the background, and the phenomenon that the application is frequently forced to be closed and restarted is caused by automatic pulling or daemon process automatic pulling even if the system is forced to be closed by a special way is avoided because the background keep-alive mechanism is not capable of completely stopping the application. In addition, the traffic is consumed by the monitoring application, but the traffic monitoring method cannot identify the type of application because the type of application triggers RRC (radio resource control) each time and does not send a lot of data, namely the power consumption cannot be early-warned and monitored because of frequent network requests of the type of application.
Disclosure of Invention
In order to solve the technical problems, the invention provides a monitoring system and a method for frequent network requests of intelligent equipment, and the specific solution is as follows:
in one aspect, a monitoring system for frequent network requests of an intelligent device is provided, including:
the RCC statistics module is used for counting the application triggering the network request in the RCC at this time and generating an RRC statistics result when RRC is released every time;
the data statistics module is used for adding one to the accumulated network request times of the application triggering the network request in the RCC;
and the problem application output module is used for marking the application as a problem application and pushing the problem application and network request data thereof to the appointed external equipment when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times.
In the technical scheme, the problem application with abnormal power consumption on the network request is found through analyzing the network request times of the application, and then a developer of the problem application is informed to process and repair the problem application, so that the technical problems of low efficiency and difficult analysis and positioning in the prior art are overcome, the searching speed of the problem application with abnormal power consumption on the network request is improved, and the power consumption is further reduced.
Preferably, the problem application output module is deployed at the cloud;
the cloud computing system further comprises an interval generation module which is used for periodically transmitting the accumulated network request times of all the applications to the cloud computing system, and resetting all the accumulated network request times to be zero.
In the technical scheme, the data is uploaded periodically, and meanwhile, the data is cleaned and the accumulated network request times are zeroed, so that the data volume uploaded each time is greatly reduced, timely useless data processing is realized, and the resources consumed by data storage are reduced.
Further preferably, the period of the interval data uploading module is one day.
Preferably, the problem application report generating module is configured to generate an analysis report of the problem application according to the network request data of the problem application, and push the analysis report to a specified external device.
Preferably, the system further comprises a network request distribution report module, which is used for generating a network request distribution report according to the network request data of all the applications and pushing the analysis report to the appointed external equipment.
In another aspect, the present invention provides a method for monitoring frequent network requests of an intelligent device, including:
when RRC is released each time, counting the application triggering the network request in the RCC and generating an RRC counting result;
adding one to the accumulated network request times of the application triggering the network request in the RCC according to the RRC statistics result;
when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times, marking the application as a problem application, and pushing the problem application and the network request data thereof to the appointed external equipment.
In the technical scheme, the problem application with abnormal power consumption on the network request is found through analyzing the network request times of the application, and then a developer of the problem application is informed to process and repair the problem application, so that the technical problems of low efficiency and difficult analysis and positioning of the problem existing in the prior art are overcome, and the speed of finding the problem application with abnormal power consumption on the network request is improved.
Preferably, adding one to the accumulated number of network requests of the application triggering the network request in the current RCC includes:
and when the specified period point is reached, transmitting the accumulated network request times of all the applications to the cloud end, and resetting all the accumulated network request times to be zero.
In the technical scheme, the data is uploaded periodically, and meanwhile, the data is cleaned and the accumulated network request times are zeroed, so that the data volume uploaded each time is greatly reduced, timely useless data processing is realized, and the resources consumed by data storage are reduced.
Further preferably, the period of the interval data uploading module is one day.
Preferably, the method further comprises: and generating an analysis report of the problem application according to the network request data of the problem application, and pushing the analysis report to the appointed external equipment.
Preferably, the method further comprises: and generating a network request distribution report according to the network request data of all the applications, and pushing the analysis report to the appointed external equipment.
The invention at least comprises the following technical effects:
(1) Through analyzing the network request times of the application, then finding out the problem application with abnormal power consumption on the network request, and then informing a developer of the problem application to process and repair the problem application, the technical problems of low efficiency and difficult analysis and positioning of the problem existing in the prior art are overcome, and the finding speed of the problem application with abnormal power consumption on the network request is improved.
(2) The data is uploaded periodically, and meanwhile, data cleaning and zero returning of the accumulated network request times are carried out, so that the data volume uploaded each time is greatly reduced, timely useless data processing is realized, and resources consumed by data storage are reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments will be briefly described below, it will be apparent that the drawings in the following description are only some embodiments of the present invention, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic structural diagram of embodiment 1 of the present invention;
FIG. 2 is a schematic structural diagram of embodiment 2 of the present invention;
FIG. 3 is a schematic structural diagram of embodiment 3 of the present invention;
FIG. 4 is a schematic structural diagram of embodiment 4 of the present invention;
FIG. 5 is a schematic structural diagram of embodiment 5 of the present invention;
FIG. 6 is a schematic structural diagram of embodiment 6 of the present invention;
fig. 7 is a schematic structural diagram of embodiment 7 of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. However, it will be apparent to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
For the sake of simplicity of the drawing, the parts relevant to the present invention are shown only schematically in the figures, which do not represent the actual structure thereof as a product. Additionally, in order to facilitate a concise understanding of the drawings, components having the same structure or function in some of the drawings are depicted schematically only one of them, or only one of them is labeled. Herein, "a" means not only "only this one" but also "more than one" case.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
In addition, in the description of the present application, the terms "first," "second," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description will explain the specific embodiments of the present invention with reference to the accompanying drawings. It is evident that the drawings in the following description are only examples of the invention, from which other drawings and other embodiments can be obtained by a person skilled in the art without inventive effort.
Example 1:
as shown in fig. 1, this embodiment provides a monitoring system for frequent network requests of an intelligent device, including:
the RCC statistics module (1) is used for counting the application triggering the network request in the RCC at this time and generating an RRC statistics result when RRC is released every time;
the data statistics module (2) is used for adding one to the accumulated network request times of the application triggering the network request in the RCC;
and the problem application output module (3) is used for marking the application as a problem application and pushing the problem application and network request data thereof to the appointed external equipment (6) when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times.
In the traditional technology, because the network request has little log printing information, which application frequently triggers the network request is difficult to analyze and locate, the packet is required to be grabbed to find out that the application type is low in efficiency, the analysis and locating problem is difficult, the problem solving period is long, and the application type is passive, even in a mode of forcibly closing the application in the background, because a mechanism of the background keep-alive is not used for completely stopping the application, and meanwhile, a phenomenon that frequent forced closing and restarting are caused by automatic pulling or daemon is caused by automatic pulling through a special way even if the system is forcibly closed, and if the application consumes traffic is monitored, a method that the application type cannot be identified by a method that the application type frequently triggers RRC (radio resource control) and does not send much data to cause traffic monitoring, namely, the power consumption caused by frequent network request of the application type cannot be early-warned and monitored.
In this embodiment, the traffic is not monitored, but the number of network requests in the accumulated RRC is monitored instead, specifically, when each RRC release is monitored, the application of the network requests is performed in the RRC, for example, in the RRC process, the accumulated number of network requests of applications of A, B, C and A, B, C is 998, 999 and 1000 respectively, which means A, B, C respectively performs the network requests of 998, 999 and 1000 respectively in the RRC process in the past, then the network requests are performed, and as A, B, C all perform the network requests, the accumulated number of network requests of A, B, C and A, B, C are added by 1 respectively, which means that in the RRC connection, the accumulated number of network requests of A, B, C is now 999, 1000 and 1001 respectively, and assuming that the maximum number of network requests is 1000, the maximum abnormal number is 100, and now, since the accumulated number of network requests of C is greater than 1000, and the number of abnormal network requests is greater than 100, that is, the C application is determined to be the problem application, the C application should perform the optimization process, and the application is assigned to the developer, and the developer should perform the network repair process, and the device is frequently analyzed.
According to the method and the device, the problem application with abnormal power consumption on the network request is found through analysis of the network request times of the application, and then a developer of the problem application is informed to process and repair the problem application, so that the technical problems of low efficiency and difficult analysis and positioning in the prior art are solved, and the searching speed of the problem application with abnormal power consumption on the network request is improved.
Example 2:
as shown in fig. 2, the present embodiment provides a monitoring system for frequent network requests of intelligent equipment based on embodiment 1, where the problem application output module is deployed at the cloud end;
the cloud computing system further comprises a section generating module (4) which is used for periodically transmitting the accumulated network request times of all the applications to the cloud computing system, and resetting all the accumulated network request times to be zero.
Since the number of requests for the network from the start of the application to the termination of the application is cumbersome, and is not suitable for data analysis and processing, in this embodiment, a periodic method is adopted, that is, uploading of data is performed periodically, and data cleaning and zeroing of the accumulated number of requests for the network are performed simultaneously.
Meanwhile, it is further preferable that the period of the section data uploading module is one day.
In this embodiment, the amount of network requests of each application is obtained at regular intervals each day, typically 7 points each day, and the amount of network requests of all applications from 7 points each day to 7 points today is obtained, and from the perspective of updating and running period of the application itself, the running process of one application can be exactly reflected in the period of one day, so that the running condition of the application about the network requests can be effectively collected, and meanwhile, when the intelligent device is started for the first time, data uploading is also performed.
According to the embodiment, the data is uploaded periodically, and meanwhile, data cleaning and zero returning of the accumulated network request times are carried out, so that the data volume uploaded each time is greatly reduced, timely useless data processing is realized, and resources consumed by data storage are reduced.
Example 3:
as shown in fig. 3, the present embodiment is based on embodiment 1, a problem application report generating module (5) for generating an analysis report of the problem application according to network request data of the problem application, and pushing the analysis report to a specified external device (6).
Since in the actual application process, the developer is simply and simply told that "your application has a problem" is equal to what is not told to the developer, in this embodiment, the developer is told not only that "your application has a problem" but also that "your application has a problem", so in the actual application process, the network request data of the problem application is analyzed to generate a corresponding analysis report and send the corresponding analysis report to the developer, thereby informing the developer of what kind of problem the application has.
Preferably, the system further comprises a network request distribution report module for generating a network request distribution report according to the network request data of all the applications, and pushing the analysis report to a designated external device (6).
In the preferred embodiment, the developer is not only informed of what the problem is about your application, but also informed of what the average level is in normal condition or is now, so that the method plays a guiding role in the optimization activity of the developer.
Example 4:
as shown in fig. 4, this embodiment provides a method for monitoring frequent network requests of an intelligent device, including:
s1: when RRC is released each time, counting the application triggering the network request in the RCC and generating an RRC counting result;
s2: adding one to the accumulated network request times of the application triggering the network request in the RCC;
s4: when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times, marking the application as a problem application;
s6: and pushing the problem application and the network request data to the appointed external equipment.
In the traditional technology, because the network request has little log printing information, which application frequently triggers the network request is difficult to analyze and locate, the packet is required to be grabbed to find out that the application type is low in efficiency, the analysis and locating problem is difficult, the problem solving period is long, and the application type is passive, even in a mode of forcibly closing the application in the background, because a mechanism of the background keep-alive is not used for completely stopping the application, and meanwhile, a phenomenon that frequent forced closing and restarting are caused by automatic pulling or daemon is caused by automatic pulling through a special way even if the system is forcibly closed, and if the application consumes traffic is monitored, a method that the application type cannot be identified by a method that the application type frequently triggers RRC (radio resource control) and does not send much data to cause traffic monitoring, namely, the power consumption caused by frequent network request of the application type cannot be early-warned and monitored.
In this embodiment, the traffic is not monitored, but the number of network requests in the accumulated RRC is monitored instead, specifically, when each RRC release is monitored, the number of network requests in the RRC is monitored, for example, in the RRC process, the accumulated number of network requests for applications of A, B, C and A, B, C is 998, 999 and 1000 respectively, which means A, B, C is the problem application in the RRC process in the past, 998, 999 and 1000 respectively, the network requests are made, then, since A, B, C is all made, the accumulated number of network requests of A, B, C is added with 1 respectively, which means that in the RRC connection, A, B, C is all made, so the accumulated number of network requests is 999, 1000 and 1001 respectively, and assuming that the maximum number of network requests is 1000, the maximum number of abnormal is 100, and now, since the accumulated number of network requests of C is greater than 1000, and the number of abnormal network requests is greater than 100, that is, the C application is determined to be the problem application, the C application should be optimized, the C application should be transmitted to the developer, and the developer should be notified that the application should be optimized, and the developer should be frequently analyzed.
According to the method and the device, the problem application with abnormal power consumption on the network request is found through analysis of the network request times of the application, and then a developer of the problem application is informed to process and repair the problem application, so that the technical problems of low efficiency and difficult analysis and positioning in the prior art are solved, and the searching speed of the problem application with abnormal power consumption on the network request is improved.
Example 5:
as shown in fig. 5, this embodiment provides a method for monitoring frequent network requests of an intelligent device, including:
s1: when RRC is released each time, counting the application triggering the network request in the RCC and generating an RRC counting result;
s2: adding one to the accumulated network request times of the application triggering the network request in the RCC;
s3: and when the specified period point is reached, transmitting the accumulated network request times of all the applications to the cloud end, and resetting all the accumulated network request times to be zero.
S4: when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times, marking the application as a problem application;
s6: and pushing the problem application and the network request data to the appointed external equipment.
Since the number of requests for the network from the start of the application to the termination of the application is cumbersome, and is not suitable for data analysis and processing, in this embodiment, a periodic method is adopted, that is, uploading of data is performed periodically, and data cleaning and zeroing of the accumulated number of requests for the network are performed simultaneously.
Meanwhile, it is further preferable that the period of the section data uploading module is one day.
In this embodiment, the amount of network requests of each application is obtained at regular intervals each day, typically 7 points each day, and the amount of network requests of all applications from 7 points each day to 7 points today is obtained, and from the perspective of updating and running period of the application itself, the running process of one application can be exactly reflected in the period of one day, so that the running condition of the application about the network requests can be effectively collected, and meanwhile, when the intelligent device is started for the first time, data uploading is also performed.
According to the embodiment, the data is uploaded periodically, and meanwhile, data cleaning and zero returning of the accumulated network request times are carried out, so that the data volume uploaded each time is greatly reduced, timely useless data processing is realized, and resources consumed by data storage are reduced.
Example 6:
as shown in fig. 6, this embodiment provides a method for monitoring frequent network requests of an intelligent device, including:
s1: when RRC is released each time, counting the application triggering the network request in the RCC and generating an RRC counting result;
s2: adding one to the accumulated network request times of the application triggering the network request in the RCC;
s3: when the appointed period point is reached, transmitting the accumulated network request times of all the applications to a cloud end, and resetting all the accumulated network request times to be zero; the period of the interval data uploading module is one day.
S4: when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times, marking the application as a problem application;
s5: and generating an analysis report of the problem application according to the network request data of the problem application, and pushing the analysis report to the appointed external equipment.
S6: and pushing the problem application and the network request data to the appointed external equipment.
Since in the actual application process, the developer is simply and simply told that "your application has a problem" is equal to what is not told to the developer, in this embodiment, the developer is told not only that "your application has a problem" but also that "your application has a problem", so in the actual application process, the network request data of the problem application is analyzed to generate a corresponding analysis report and send the corresponding analysis report to the developer, thereby informing the developer of what kind of problem the application has.
Preferably, S7: and generating a network request distribution report according to the network request data of all the applications, and pushing the analysis report to the appointed external equipment.
In the preferred embodiment, the developer is not only informed of what the problem is about your application, but also informed of what the average level is in normal condition or is now, so that the method plays a guiding role in the optimization activity of the developer.
Example 7:
as shown in fig. 7, this embodiment provides a method for monitoring frequent network requests of an intelligent device, including:
s1: and acquiring how many applications trigger the network request in the RRC every time the RRC is released, counting the accumulated times of the application network requests, and writing the accumulated times into a database.
And S2, starting up for 7 hours in the morning or for the first time in the next day, and detecting whether the application network request data collected yesterday is uploaded to a server or not, and if the application network request data is not uploaded to the server, then emptying the data. And re-counting the number of application network requests.
And S3, judging that the number of network request times of each device on the application day is larger than a preset value, such as 1000, by the server background according to the strategy, wherein the mark of the application day is frequent network request abnormality, meanwhile, the number of the network request times marked as abnormal on the application day is larger than the preset value, and if ten percent of the activation quantity of the application on the same day is ten, the application has abnormal network request behaviors and generates an early warning report to be pushed to a developer, and meanwhile, the application is ordered according to the network request times and then a network request time distribution report of each application is generated to be pushed to the developer.
S4, after receiving the frequent network request early warning push, the developer starts intervention to perform problem analysis, repair, optimization and the like. After receiving the report push of the network request times distribution, the developer analyzes whether the report has the application of the network request times optimization, and then makes corresponding strategy adjustment.
In this embodiment, therefore, the traffic is not monitored, but the number of network requests in the accumulated RRC is monitored instead, specifically, when each RRC release is monitored, the application of the network request is performed in the RRC, for example, in the RRC process, three applications A, B, C are involved, the accumulated number of network requests of the applications A, B, C is 998, 999 and 1000 respectively, the number of abnormal network requests is greater than 100, that is, the application A, B, C is determined to be a problem application in the RRC process in the past, the network requests of 998, 999 and 1000 respectively are performed, then the network requests are performed, since A, B, C applications are performed, the accumulated number of network requests of the applications A, B, C is increased by 1 respectively, which indicates that in the RRC connection, the accumulated number of network requests of A, B, C is now 999, 1000 and 1001 respectively, and the maximum abnormal number of network requests is 100, and now because the accumulated number of network requests of C is greater than 1000, the number of abnormal network requests is greater than 100, that is, the application C is determined to be a problem application, the application C is optimized, the application is then the application is optimized, and the application is optimized is the application is the developer, and the data is frequently analyzed, and the developer is frequently is analyzed.
Finally, through two reports, the method and the system not only tell the developer that the application is problematic, but also tell the developer that the application is problematic, and tell the developer what the normal condition or the average level of people is, so that the method and the system have guiding significance on the optimization activities of the developer.
The method for acquiring how many applications trigger the network request in the RRC every time when the RRC is released counts how many applications trigger the network request every day, and monitors the network request times of each application. The method has the advantages of reducing the analysis difficulty, reducing the labor cost, shortening the problem repairing period, and particularly having obvious effect on products with larger user base numbers. And inserting the counted network request times and data information into a database. And when 7 points are on the morning every day or the first time of starting up, the data is reported to the server background under the condition that the network is available again, so that the data loss is avoided. The background server judges that the mark is frequent network requests according to the number of the application network requests of each device, which is greater than a preset value (such as 1000), judges whether the number of the abnormal network requests marked as abnormal on the same day of the application is greater than a preset value (such as ten percent of the active amount on the same day of the application), generates an application frequent network request report and pushes the report to a developer to early warn the application frequent network requests. The efficiency of the power consumption problem analysis is improved, the problem solving period is shortened, and the phenomenon of large-scale power consumption is avoided, so that the public praise and the user experience of the product are influenced. The background service generates an application network request frequency distribution report according to the network request frequency ordering so as to monitor the network request process. The optimization of the application network request times is facilitated, so that the power saving and product endurance can be improved, the product quality can be improved, and the user experience can be improved.
The invention is realized by the foregoing embodiments:
(1) Through analyzing the network request times of the application, then finding out the problem application with abnormal power consumption on the network request, and then informing a developer of the problem application to process and repair the problem application, the technical problems of low efficiency and difficult analysis and positioning of the problem existing in the prior art are overcome, and the finding speed of the problem application with abnormal power consumption on the network request is improved.
(2) The data is uploaded periodically, and meanwhile, data cleaning and zero returning of the accumulated network request times are carried out, so that the data volume uploaded each time is greatly reduced, timely useless data processing is realized, and resources consumed by data storage are reduced.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A monitoring system for frequent network requests of intelligent device equipment, comprising:
the RCC statistics module is used for counting the application triggering the network request in the RCC at this time and generating an RRC statistics result when RRC is released every time;
the data statistics module is used for adding one to the accumulated network request times of the application triggering the network request in the RCC according to the RRC statistics result;
and the problem application output module is used for marking the application as a problem application when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times, and pushing the problem application and the network request data thereof to the appointed external equipment.
2. The monitoring system for frequent network requests of intelligent equipment according to claim 1, wherein the problem application output module is deployed at a cloud end;
the cloud computing system further comprises an interval generation module which is used for periodically transmitting the accumulated network request times of all the applications to the cloud computing system, and resetting all the accumulated network request times to be zero.
3. The monitoring system for frequent network requests of intelligent device according to claim 2, wherein the period of the interval generation module is one day.
4. A monitoring system according to any of claims 1-3, wherein a problem application report generating module is configured to generate an analysis report of the problem application according to the network request data of the problem application, and push the analysis report to a specified external device.
5. A monitoring system according to any one of claims 1-3, further comprising a network request distribution report module configured to generate a network request distribution report according to network request data of all the applications, and push the network request distribution report to a specified external device.
6. The method for monitoring the frequent network requests of the intelligent equipment is characterized by comprising the following steps of:
when RRC is released each time, counting the application triggering the network request in the RCC and generating an RRC counting result;
adding one to the accumulated network request times of the application triggering the network request in the RCC according to the RRC statistics result;
when the accumulated network request times of any application are larger than the preset maximum request times and the abnormal network request times of the application are larger than the preset maximum abnormal times, marking the application as a problem application;
and pushing the problem application and the network request data to the appointed external equipment.
7. The method for monitoring frequent network requests of intelligent device according to claim 6, wherein adding one to the accumulated number of network requests of the application triggering the network requests in the RCC includes:
and when the specified period point is reached, transmitting the accumulated network request times of all the applications to the cloud end, and resetting all the accumulated network request times to be zero.
8. The method for monitoring frequent network requests of intelligent equipment according to claim 7, wherein the period of the designated period point is one day.
9. The method for monitoring frequent network requests of an intelligent device according to any one of claims 6-8, further comprising: and generating an analysis report of the problem application according to the network request data of the problem application, and pushing the analysis report to the appointed external equipment.
10. The method for monitoring frequent network requests of an intelligent device according to any one of claims 6-8, further comprising: and generating a network request distribution report according to all the network request data of the application, and pushing the network request distribution report to the appointed external equipment.
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