CN112637682A - Abnormal offline diagnosis method, device, equipment and computer readable storage medium - Google Patents
Abnormal offline diagnosis method, device, equipment and computer readable storage medium Download PDFInfo
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- CN112637682A CN112637682A CN202011490107.0A CN202011490107A CN112637682A CN 112637682 A CN112637682 A CN 112637682A CN 202011490107 A CN202011490107 A CN 202011490107A CN 112637682 A CN112637682 A CN 112637682A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/4424—Monitoring of the internal components or processes of the client device, e.g. CPU or memory load, processing speed, timer, counter or percentage of the hard disk space used
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/41—Structure of client; Structure of client peripherals
- H04N21/4104—Peripherals receiving signals from specially adapted client devices
- H04N21/4122—Peripherals receiving signals from specially adapted client devices additional display device, e.g. video projector
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/4425—Monitoring of client processing errors or hardware failure
Abstract
The invention discloses an abnormal offline diagnosis method, an abnormal offline diagnosis device and a readable storage medium, wherein when application abnormality is detected and networking cannot be performed locally, a target slave device which is connected and can be networked is found first, and recurrence abnormal information corresponding to the application abnormal information is obtained by means of the target slave device, so that the target slave device can reproduce an abnormal condition of a master device; acquiring recurrence abnormal information through the target slave equipment, searching according to the recurrence abnormal information to obtain a corresponding recurrence diagnosis result, and meanwhile, equivalently obtaining a target diagnosis result of the abnormal information applied in the master equipment, so that the abnormality occurring in the master equipment can be diagnosed in a networking way by the target slave equipment; and finally, the main equipment can obtain the networking diagnosis result in an offline environment by receiving the recurrence diagnosis result transmitted by the target slave equipment.
Description
Technical Field
The invention relates to the technical field of intelligent terminals, in particular to an abnormal offline diagnosis method, an abnormal offline diagnosis device, abnormal offline diagnosis equipment and a computer-readable storage medium.
Background
With the development of intelligent terminal technology, various devices with intelligent large screens enter thousands of households due to intelligence and convenience. When a user uses the intelligent large-screen device, the device is sometimes abnormal. When the intelligent large-screen equipment is networked, a user can help to solve the problem by means of some abnormal diagnosis software; however, sometimes, the intelligent large-screen device cannot be networked for various reasons, and at this time, the fault cannot be eliminated through online abnormality diagnosis software, so that the technical problem that the intelligent large-screen device is difficult to perform abnormality diagnosis in a network-free environment is caused.
Disclosure of Invention
The invention mainly aims to provide an abnormal offline diagnosis method, and aims to solve the technical problem that intelligent large-screen equipment is difficult to diagnose the abnormality in a network-free environment.
In order to achieve the above object, the present invention provides an offline abnormality diagnosis method, which is applied to a master device, and includes:
acquiring application exception information;
when the master device cannot be networked, determining a target slave device which can be networked from slave devices which are currently connected with the master device;
sending the application exception information to the target slave equipment so that the target slave equipment can reproduce exception and acquire reproduction exception information;
receiving a recurrence diagnosis result for the recurrence abnormality information transmitted by the target slave device as a target diagnosis result of the application abnormality information.
Optionally, the obtaining of the application exception information includes:
receiving an abnormality diagnosis instruction;
acquiring application detection information from the running condition of a foreground application of the main equipment based on the abnormity diagnosis instruction;
judging whether the application detection information meets a preset abnormal judgment condition or not;
and if so, generating the application abnormal information based on the application detection information.
Optionally, the application detection information comprises a runtime and/or resource lookup result,
the judging whether the application detection information meets the preset abnormal judgment condition comprises the following steps:
judging whether the times of detecting the running time to be abnormal in a preset time length exceeds a preset first time threshold value and/or whether the times of errors of the resource searching result exceeds a preset second time threshold value;
if the number of times of detecting that the running time is abnormal exceeds a preset first time threshold value and/or the number of times of detecting that the resource searching result is wrong exceeds a preset second time threshold value within a preset time length, judging that the application detection information meets a preset abnormal judgment condition;
and if the times of detecting that the running time is abnormal do not exceed a preset first time threshold value and the times of detecting the resource searching result is wrong do not exceed a preset second time threshold value within a preset time length, judging that the application detection information does not meet a preset abnormal judgment condition.
Optionally, there are a plurality of slave devices to which the master device is currently connected,
when the master device cannot be networked, determining a target slave device which can be networked from slave devices which are currently connected with the master device comprises the following steps:
when the master device cannot be networked, searching a plurality of locally connected slave devices, and sending networking test instructions to the plurality of locally connected slave devices;
when target feedback information for the networking test instruction fed back by the plurality of slave devices is received, the slave device with the highest feedback speed is selected as the target slave device from the plurality of slave devices feeding back the target feedback information.
Optionally, the recurring abnormality information includes first recurring information,
the sending the application exception information to the target slave device for the target slave device to reproduce the exception and acquire reproduction exception information includes:
sending the application exception information to the target slave equipment so that the target slave equipment can reproduce exception;
when the target slave device detects that the first recurrence information exists, the first recurrence information actively reported by the target slave device is obtained, wherein the first recurrence information is abnormal information which locally exists in the target slave device and is matched with the application abnormal information.
Optionally, the recurring abnormality information includes second recurring information,
after sending the application exception information to the target slave device for the target slave device to reproduce an exception, the method further includes:
when the target slave device detects that the first recurrence information does not exist, receiving a recurrence information detection result fed back by the target slave device, and sending an application downloading instruction to the target slave device based on the recurrence information detection result, so that the target slave device can access a cloud server to download and install a target application with abnormality in the application abnormality information;
and receiving second recurrence information sent by the target slave device, wherein the second recurrence information is abnormal information which is obtained after the target slave device installs the target application and is matched with the application abnormal information.
Optionally, before receiving a recurring diagnosis result for the recurring abnormal information sent by the target slave device as a target diagnosis result of the application abnormal information, the method further includes:
and sending a networking diagnosis instruction to the target slave equipment, so that the target slave equipment reports the recurrence abnormal information to a cloud server based on the networking diagnosis instruction to obtain the recurrence diagnosis result.
In order to achieve the above object, the present invention also provides an abnormality offline diagnosis apparatus, including:
the abnormal information acquisition module is used for acquiring application abnormal information;
the device connection determining module is used for determining target slave devices which can be networked from the slave devices which are currently connected with the master device when the master device cannot be networked;
the recurrence information acquisition module is used for sending the application exception information to the target slave equipment so as to enable the target slave equipment to recur the exception and acquire recurrence exception information;
an anomaly information diagnosis module for receiving a recurrence diagnosis result for the recurrence anomaly information sent by the target slave device as a target diagnosis result of the application anomaly information.
Optionally, the abnormal information acquiring module includes:
an instruction receiving unit for receiving an abnormality diagnosis instruction;
the operation monitoring unit is used for acquiring application detection information from the operation condition of foreground application of the main equipment based on the abnormity diagnosis instruction;
an abnormality determination unit configured to determine whether the application detection information satisfies a preset abnormality determination condition;
and if so, generating the application abnormity information based on the application detection information.
Optionally, the application detection information comprises a runtime and/or resource lookup result,
the abnormality determination unit is further configured to:
judging whether the times of detecting the running time to be abnormal in a preset time length exceeds a preset first time threshold value and/or whether the times of errors of the resource searching result exceeds a preset second time threshold value;
if the number of times of detecting that the running time is abnormal exceeds a preset first time threshold value and/or the number of times of detecting that the resource searching result is wrong exceeds a preset second time threshold value within a preset time length, judging that the application detection information meets a preset abnormal judgment condition;
and if the times of detecting that the running time is abnormal do not exceed a preset first time threshold value and the times of detecting the resource searching result is wrong do not exceed a preset second time threshold value within a preset time length, judging that the application detection information does not meet a preset abnormal judgment condition.
Optionally, there are a plurality of slave devices to which the master device is currently connected,
the connecting device determination module includes:
the network connection testing unit is used for searching a plurality of locally connected slave devices and sending network connection testing instructions to the plurality of locally connected slave devices when the master device cannot be connected to the network;
and the target determining unit is used for selecting the slave device with the highest feedback speed from a plurality of slave devices which feed back the target feedback information as the target slave device when the target feedback information which is fed back by the plurality of slave devices and aims at the networking test instruction is received.
Optionally, the recurring abnormality information includes first recurring information,
the recurrence information acquisition module includes:
an exception recurrence unit, configured to send the application exception information to the target slave device, so that the target slave device recurs an exception;
a first information obtaining unit, configured to obtain, when the target slave device detects that the first recurring information exists, the first recurring information actively reported by the target slave device, where the first recurring information is exception information that the target slave device locally exists and is matched with the application exception information.
Optionally, the recurring abnormality information includes second recurring information,
the recurrence information acquisition module includes:
the target application downloading unit is used for receiving a recurrence information detection result fed back by the target slave equipment when the target slave equipment detects that the first recurrence information does not exist, and sending an application downloading instruction to the target slave equipment based on the recurrence information detection result so that the target slave equipment can access a cloud server to download and install a target application with abnormality in the application abnormality information;
and a second information obtaining unit, configured to receive second recurring information sent by the target slave device, where the second recurring information is exception information that is obtained after the target slave device installs the target application and matches the application exception information.
Optionally, the offline abnormality diagnosis apparatus further includes:
the recurrence networking diagnosis module is used for sending a networking diagnosis instruction to the target slave device so that the target slave device reports the recurrence abnormal information to a cloud server based on the networking diagnosis instruction to obtain the recurrence diagnosis result.
Further, to achieve the above object, the present invention also provides an abnormality offline diagnosis apparatus, comprising: the system comprises a memory, a processor and an abnormal offline diagnosis program which is stored on the memory and can run on the processor, wherein when the abnormal offline diagnosis program is executed by the processor, the steps of the method are realized.
In addition, to achieve the above object, the present invention further provides a computer readable storage medium having an abnormal offline diagnosis program stored thereon, which, when being executed by a processor, implements the steps of the method as described above.
The invention provides an abnormal offline diagnosis method, an abnormal offline diagnosis device, abnormal offline diagnosis equipment and a computer-readable storage medium. The method comprises the steps that when application abnormity is detected and networking cannot be carried out locally, a target slave device which is connected and can be connected with a network is found first, and recurrence abnormity information corresponding to the application abnormity information is obtained by means of the target slave device, so that the target slave device can reproduce an abnormity condition of a master device; acquiring recurrence abnormal information through the target slave equipment, searching according to the recurrence abnormal information to obtain a corresponding recurrence diagnosis result, and meanwhile, equivalently obtaining a target diagnosis result of the abnormal information applied in the master equipment, so that the abnormality occurring in the master equipment can be diagnosed in a networking way by the target slave equipment; and finally, the main equipment can obtain a networking diagnosis result in an offline environment by receiving the recurrence diagnosis result transmitted by the target slave equipment, so that the technical problem that the intelligent large-screen equipment is difficult to diagnose the abnormality in a network-free environment is solved.
Drawings
FIG. 1 is a schematic diagram of an abnormal offline diagnosis device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of an abnormal offline diagnosis method according to the present invention;
fig. 3 is a functional block diagram of the abnormal offline diagnosis apparatus according to the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in fig. 1, fig. 1 is a schematic structural diagram of an abnormal offline diagnosis device in a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the abnormality offline diagnosis apparatus may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The optional user interface 1003 may include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory). The memory 1005 may alternatively be a memory device separate from the processor 1001 described above.
Those skilled in the art will appreciate that the configuration of the abnormal offline diagnosis apparatus shown in fig. 1 does not constitute a limitation of the abnormal offline diagnosis apparatus, and may include more or less components than those shown, or combine some components, or arrange different components.
As shown in fig. 1, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and an abnormality offline diagnosis program.
In the abnormal offline diagnosis device shown in fig. 1, the network interface 1004 is mainly used for connecting to a background server and performing data communication with the background server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to call the exception offline diagnostic program stored in the memory 1005 and perform the following operations:
acquiring application exception information;
when the master device cannot be networked, determining a target slave device which can be networked from slave devices which are currently connected with the master device;
sending the application exception information to the target slave equipment so that the target slave equipment can reproduce exception and acquire reproduction exception information;
receiving a recurrence diagnosis result for the recurrence abnormality information transmitted by the target slave device as a target diagnosis result of the application abnormality information.
Further, the acquiring application exception information includes:
receiving an abnormality diagnosis instruction;
acquiring application detection information from the running condition of a foreground application of the main equipment based on the abnormity diagnosis instruction;
judging whether the application detection information meets a preset abnormal judgment condition or not;
and if so, generating the application abnormal information based on the application detection information.
Further, the application detection information comprises a runtime and/or resource search result,
the judging whether the application detection information meets the preset abnormal judgment condition comprises the following steps:
judging whether the times of detecting the running time to be abnormal in a preset time length exceeds a preset first time threshold value and/or whether the times of errors of the resource searching result exceeds a preset second time threshold value;
if the number of times of detecting that the running time is abnormal exceeds a preset first time threshold value and/or the number of times of detecting that the resource searching result is wrong exceeds a preset second time threshold value within a preset time length, judging that the application detection information meets a preset abnormal judgment condition;
and if the times of detecting that the running time is abnormal do not exceed a preset first time threshold value and the times of detecting the resource searching result is wrong do not exceed a preset second time threshold value within a preset time length, judging that the application detection information does not meet a preset abnormal judgment condition.
Further, a plurality of slave devices are present to which the master device is currently connected,
when the master device cannot be networked, determining a target slave device which can be networked from slave devices which are currently connected with the master device comprises the following steps:
when the master device cannot be networked, searching a plurality of locally connected slave devices, and sending networking test instructions to the plurality of locally connected slave devices;
when target feedback information for the networking test instruction fed back by the plurality of slave devices is received, the slave device with the highest feedback speed is selected as the target slave device from the plurality of slave devices feeding back the target feedback information.
Further, the recurrence exception information includes first recurrence information,
the sending the application exception information to the target slave device for the target slave device to reproduce the exception and acquire reproduction exception information includes:
sending the application exception information to the target slave equipment so that the target slave equipment can reproduce exception;
when the target slave device detects that the first recurrence information exists, the first recurrence information actively reported by the target slave device is obtained, wherein the first recurrence information is abnormal information which locally exists in the target slave device and is matched with the application abnormal information.
Further, the recurrence exception information includes second recurrence information,
after sending the application exception information to the target slave device for the target slave device to reproduce the exception, the processor 1001 may be configured to call an exception offline diagnosis program stored in the memory 1005, and perform the following operations:
when the target slave device detects that the first recurrence information does not exist, receiving a recurrence information detection result fed back by the target slave device, and sending an application downloading instruction to the target slave device based on the recurrence information detection result, so that the target slave device can access a cloud server to download and install a target application with abnormality in the application abnormality information;
and receiving second recurrence information sent by the target slave device, wherein the second recurrence information is abnormal information which is obtained after the target slave device installs the target application and is matched with the application abnormal information.
Further, before receiving a recurrence diagnosis result for the recurrence abnormality information sent by the target slave device as a target diagnosis result of the application abnormality information, the processor 1001 may be configured to call an abnormality offline diagnosis program stored in the memory 1005, and perform the following operations:
and sending a networking diagnosis instruction to the target slave equipment, so that the target slave equipment reports the recurrence abnormal information to a cloud server based on the networking diagnosis instruction to obtain the recurrence diagnosis result.
Based on the hardware structure, various embodiments of the method for offline diagnosis of abnormalities are provided.
With the development of intelligent terminal technology, various devices with intelligent large screens enter thousands of households due to intelligence and convenience. When a user uses the intelligent large-screen device, the device is sometimes abnormal. When the intelligent large-screen equipment is networked, a user can help to solve the problem by means of some abnormal diagnosis software; however, sometimes, the intelligent large-screen device cannot be networked for various reasons, and at this time, the fault cannot be eliminated through online abnormality diagnosis software, so that the technical problem that the intelligent large-screen device is difficult to perform abnormality diagnosis in a network-free environment is caused.
In order to solve the technical problems, the invention provides an abnormal offline diagnosis method, namely, when application abnormality is detected and local networking cannot be performed, a target slave device which is connected and can be networked is found first, and recurrence abnormal information corresponding to the application abnormal information is obtained by the target slave device, so that the target slave device can reproduce an abnormal condition of a master device; acquiring recurrence abnormal information through the target slave equipment, searching according to the recurrence abnormal information to obtain a corresponding recurrence diagnosis result, and meanwhile, equivalently obtaining a target diagnosis result of the abnormal information applied in the master equipment, so that the abnormality occurring in the master equipment can be diagnosed in a networking way by the target slave equipment; and finally, the main equipment can obtain a networking diagnosis result in an offline environment by receiving the recurrence diagnosis result transmitted by the target slave equipment, so that the technical problem that the intelligent large-screen equipment is difficult to diagnose the abnormality in a network-free environment is solved.
Referring to fig. 2, fig. 2 is a flowchart illustrating a first embodiment of the offline abnormality diagnosis method.
A first embodiment of the present invention provides an offline abnormality diagnosis method applied to a master device, including:
step S10, acquiring application abnormal information;
step S20, when the master device can not be networked, determining a target slave device which can be networked from the slave devices which are currently connected with the master device;
in this embodiment, the method is applied to the master device. The main device can be any intelligent terminal device which can be connected with other network-connectable devices by adopting a non-external network, such as an intelligent television, an intelligent refrigerator and the like. Correspondingly, the slave device may be any intelligent terminal, such as a mobile phone, a tablet, a personal computer, etc., which can be connected with the master device. The application exception information is exception information of an application installed in the master device, and specifically may include an application package name, a version number, exception occurrence time, times, exception description, and the like, where the exception occurs. The target slave device is a slave device which can be connected with an external network in the slave devices connected with the master device. Since the number of slave devices connected to the master device may be one or more, the target slave device may be directly determined or one or more selected from a plurality of slave devices. The selection criteria may be set based on factors such as networking transmission rate, networking quality, internal remaining storage capacity, etc.
When detecting that the local application is abnormal, the main device acquires application abnormal information and tries to diagnose the abnormality in a networking manner. When the master device detects that the master device cannot be networked, the master device acquires the slave devices which can be networked in the slave devices connected with the master device as target slave devices. Specifically, the master device is taken as an example of the smart phone. After the intelligent television is started, a user clicks a corresponding key to trigger a physical examination instruction for the application of the intelligent television system. After receiving the instruction, the intelligent television starts physical examination on the system application and obtains a physical examination result. The intelligent television judges the physical examination result, and tries networking operation of the intelligent television when judging that the application in the system application is abnormal. And when the intelligent terminal confirms that the intelligent terminal cannot be networked for carrying out abnormity diagnosis, determining target equipment capable of being networked from the locally connected slave equipment.
Step S30, sending the application exception information to the target slave device, so that the target slave device reproduces an exception and acquires reproduction exception information;
in this embodiment, the recurring abnormal information is the abnormal information in which both the application where the abnormality is located and the abnormality type are consistent with the application abnormal information, and may specifically include an application package name, a version number, an abnormality occurrence time, a frequency, an abnormality description, and the like where the abnormality occurs. The effect of the recurring abnormal operation is to completely reproduce the same application abnormal situation in the target slave device as the master device. The reproduction mode mainly comprises two modes, one mode is that the target slave device directly reproduces locally when the target slave device is provided with the application which is the same as the application with the abnormality in the master device, and the other mode is that the target slave device downloads the corresponding application from the cloud end before reproducing when the same application does not exist.
And the master device sends the application exception information to the currently determined target slave device. After receiving the application abnormal information, the target slave device performs abnormal reproduction in one of two modes of local direct reproduction or reproduction after downloading corresponding application at the cloud according to the application abnormal information to obtain reproduction abnormal information consistent with the application abnormal information. Specifically, the master device is still taken as an example of the smart phone. And the intelligent television sends application exception information containing the installation package name and the version number of the application with the exception to the target slave equipment. And after receiving the application abnormal information, the target slave device searches whether the same application with the same version number is installed or not in the local root directory according to the application package name and the version number in the application abnormal information. If the target slave device detects that the same application with the same version is installed locally, the application is operated to reproduce the same abnormal condition as the master device and obtain the reproduced abnormal information; if the target slave device detects that the same application with the same version number does not exist in the dark yellow, the same application with the same version number needs to be installed in a network, and then the application is operated to obtain the recurrence abnormal information.
Step S40, receiving a recurrence diagnosis result for the recurrence abnormality information sent by the target slave device as a target diagnosis result of the application abnormality information.
In this embodiment, the recurrent diagnostic result is a diagnostic result obtained after the target slave device performs online diagnosis on the recurrent abnormal information. The target diagnosis result is an abnormality diagnosis result for the application abnormality information that the master device desires to acquire.
And after acquiring the recurrence diagnosis result, the target slave equipment sends the recurrence diagnosis result to the master equipment. After receiving the recurrence diagnosis result, the master device can determine that the recurrence diagnosis result is equal to the networking diagnosis result of the application abnormal information. Specifically, taking the master device as an intelligent electronic device as an example, the target slave device uploads recurrent abnormal information obtained by abnormal recurrence to an external network, performs abnormal diagnosis on the recurrent abnormal information by using some abnormal diagnosis software of the external network, and obtains a diagnosis result. And after acquiring the recurrence diagnosis result, the target slave device feeds the recurrence diagnosis result back to the intelligent television terminal. And the smart television receives a recurrence diagnosis result sent by the target slave equipment, wherein the recurrence diagnosis result is equal to a target diagnosis result aiming at the application abnormal information. And the intelligent television end can repair the application abnormity according to the recurrence diagnosis result.
In the embodiment, application exception information is acquired; when the master device cannot be networked, determining a target slave device which can be networked from slave devices which are currently connected with the master device; sending the application exception information to the target slave equipment so that the target slave equipment can reproduce exception and acquire reproduction exception information; receiving a recurrence diagnosis result for the recurrence abnormality information transmitted by the target slave device as a target diagnosis result of the application abnormality information. Through the mode, when the application abnormity is detected and the local networking cannot be performed, the connected target slave equipment capable of being networked is found first, and the recurrence abnormity information corresponding to the application abnormity information is obtained by the target slave equipment, so that the target slave equipment can reproduce the abnormity condition of the master equipment; acquiring recurrence abnormal information through the target slave equipment, searching according to the recurrence abnormal information to obtain a corresponding recurrence diagnosis result, and meanwhile, equivalently obtaining a target diagnosis result of the abnormal information applied in the master equipment, so that the abnormality occurring in the master equipment can be diagnosed in a networking way by the target slave equipment; and finally, the main equipment can obtain a networking diagnosis result in an offline environment by receiving the recurrence diagnosis result transmitted by the target slave equipment, so that the technical problem that the intelligent large-screen equipment is difficult to diagnose the abnormality in a network-free environment is solved.
Further, a second embodiment of the offline abnormality diagnosis method according to the present invention is proposed based on the first embodiment shown in fig. 2, and in this embodiment, step S10 includes:
receiving an abnormality diagnosis instruction;
acquiring application detection information from the running condition of a foreground application of the main equipment based on the abnormity diagnosis instruction;
judging whether the application detection information meets a preset abnormal judgment condition or not;
and if so, generating the application abnormal information based on the application detection information.
In this embodiment, the abnormality diagnosis instruction may be an instruction for performing physical examination diagnosis on one of the system applications of the master device, or may be an instruction for performing physical examination diagnosis on a plurality of or even all system applications of the master device. The instruction can be initiated by the user to the main device, and can also be initiated by the main device according to a preset program. The preset abnormality determination condition may be set based on various types of abnormality, for example, a corresponding determination index may be set for information such as a running time, a resource search result, and a vulnerability detection result in application detection information in a certain unit time.
Specifically, if the main device is a smart television. The user opens the intelligent television, clicks the corresponding key to start the application physical examination function, and performs physical examination on all system applications. After physical examination is finished, the smart television end can capture the running status of each application, such as the running time, whether the application resource is found to be the correct result, and the like, and use the running status as the application detection information. And the intelligent television end analyzes the running state and judges whether the running state meets a preset abnormal judgment condition or not. If the intelligent television end judges that the application detection information meets the preset abnormity judgment condition, the application abnormity occurs in the intelligent television end, and the reason for abnormity analysis needs to be further diagnosed to eliminate and solve the abnormity; if the intelligent television end judges that the application detection information does not meet the preset abnormity judgment condition, the application physical examination does not detect abnormity.
Further, the application detection information comprises a runtime and/or resource search result,
the judging whether the application detection information meets the preset abnormal judgment condition comprises the following steps:
judging whether the times of detecting the running time to be abnormal in a preset time length exceeds a preset first time threshold value and/or whether the times of errors of the resource searching result exceeds a preset second time threshold value;
if the number of times of detecting that the running time is abnormal exceeds a preset first time threshold value and/or the number of times of detecting that the resource searching result is wrong exceeds a preset second time threshold value within a preset time length, judging that the application detection information meets a preset abnormal judgment condition;
and if the times of detecting that the running time is abnormal do not exceed a preset first time threshold value and the times of detecting the resource searching result is wrong do not exceed a preset second time threshold value within a preset time length, judging that the application detection information does not meet a preset abnormal judgment condition.
In this embodiment, the preset duration and the preset first and second times thresholds may be flexibly set according to actual requirements, which is not specifically limited in this embodiment. The same detection duration can be set for the running time and the resource search result, and different detection durations can also be set, and the times threshold value is the same, and the first time threshold value and the second time threshold value can be set to be the same or different.
For example, if the preset duration is 100ms, the preset first time threshold is two times, and the preset second time threshold is three times. The intelligent television end analyzes the current application physical examination result, judges that the running time of a certain application is abnormal for 3 times within 100ms, and judges that the abnormal condition that resources cannot be found within 100ms is abnormal for 4 times, and then can judge that the application is abnormal and acquire application information of the application, such as application package name, version number and the like.
Further, a plurality of slave devices are present to which the master device is currently connected,
step S20 includes:
when the master device cannot be networked, searching a plurality of locally connected slave devices, and sending networking test instructions to the plurality of locally connected slave devices;
when target feedback information for the networking test instruction fed back by the plurality of slave devices is received, the slave device with the highest feedback speed is selected as the target slave device from the plurality of slave devices feeding back the target feedback information.
In this embodiment, the master device first needs to try to connect to the external network, and when determining that it is currently unable to connect to the external network, acquires information of the locally connected slave device. If the number of the currently connected slave devices is 1, the master device further determines whether the slave devices can be networked. If the master device detects that the slave device can be networked, the master device can be used as a target slave device; if the number of the slave devices which are connected currently is multiple, further determining which of the multiple slave devices can be networked currently, and if the multiple slave devices which can be networked exist, selecting the slave device with the highest feedback speed from the multiple slave devices which can be networked as the target slave device. According to actual requirements, one of the fastest network speed and the largest memory remaining space can be selected as the target slave device; or a plurality of slave devices which can be networked and the like are taken as target slave devices to obtain a plurality of repeated diagnosis results.
In this embodiment, whether the application is abnormal or not is further identified through the running time, the resource search result, the preset time period and the time threshold value, so that the abnormality identification process is simple and easy to implement; the connected slave devices are searched when the fact that the slave devices cannot be networked is detected, and the target slave devices which can be networked are determined from the slave devices, so that the abnormality can be diagnosed through the target slave devices in a networked mode.
Further, based on the first embodiment shown in fig. 2, a third embodiment of the offline abnormality diagnosis method according to the present invention is provided. In this embodiment, the reproduction abnormality information includes first reproduction information, and step S30 includes:
sending the application exception information to the target slave equipment so that the target slave equipment can reproduce exception;
when the target slave device detects that the first recurrence information exists, the first recurrence information actively reported by the target slave device is obtained, wherein the first recurrence information is abnormal information which locally exists in the target slave device and is matched with the application abnormal information.
In this embodiment, the master device sends the currently acquired application exception information to the target slave device, and the target slave device determines whether an application with the same name and the same version number exists locally in the target slave device by using a table lookup manner according to the application package name and the version number in the application exception information. If the abnormal application exists, the fact that the same application as the application with the abnormality of the main equipment exists in the target equipment is indicated. The target slave device runs the application to replicate the application exception. And the target slave equipment judges whether the abnormal information which is the same as the abnormal information of the main equipment exists locally or not according to the operation result, namely the first recurrence information. If yes, reporting to the main equipment.
Further, the recurrence exception information includes second recurrence information,
after sending the application exception information to the target slave device for the target slave device to reproduce an exception, the method further includes:
when the target slave device detects that the first recurrence information does not exist, receiving a recurrence information detection result fed back by the target slave device, and sending an application downloading instruction to the target slave device based on the recurrence information detection result, so that the target slave device can access a cloud server to download and install a target application with abnormality in the application abnormality information;
and receiving second recurrence information sent by the target slave device, wherein the second recurrence information is abnormal information which is obtained after the target slave device installs the target application and is matched with the application abnormal information.
In this embodiment, if the target slave device does not have the same abnormal condition as the master device after running the application, that is, the first recurring information does not appear, a negative search result is fed back to notify the master device. The master device sends an application downloading instruction to the target slave device to instruct the target slave device to download the application which is consistent with the abnormal application package name and version number in a networking mode. And the target requests the cloud server to download the application from the side according to the name and the version number of the application package, and starts to run the application after downloading and installation. The subsequent steps are the same as the above, and the target slave device runs the application to reproduce the application exception. And the target slave equipment judges whether the abnormal information which is the same as the abnormal information of the main equipment exists locally or not according to the operation result, namely the second recurrence information. If yes, reporting to the main equipment; if not, a negative search result is fed back to inform the main equipment that the reproduction abnormal information is not obtained through two modes.
Further, before step S40, the method further includes:
and sending a networking diagnosis instruction to the target slave equipment, so that the target slave equipment reports the recurrence abnormal information to a cloud server based on the networking diagnosis instruction to obtain the recurrence diagnosis result.
In this embodiment, after obtaining the recurring abnormal information, the target slave device reports to the master device, and the master device sends a networking diagnosis instruction to the target slave device to instruct the target slave device to report the recurring abnormal information to the cloud server. The cloud server can diagnose the target slave device through relevant software and feed back a generated diagnosis result to the target slave device.
In the embodiment, whether the target slave device has the same abnormal application as the master device is further judged, and different abnormal recurrence ways are respectively set according to the existence and the nonexistence of the target slave device, so that the intelligence of the recurrence of the abnormal is improved; the target slave device is instructed to report the reproduced abnormal information to the cloud server, so that the cloud server substantially diagnoses the application abnormal information of the master device.
The invention also provides an abnormal off-line diagnosis device.
The abnormality offline diagnosis apparatus includes:
an abnormal information obtaining module 10, configured to obtain application abnormal information;
a connected device determining module 20, configured to determine, when the master device cannot be networked, a target slave device that can be networked from slave devices that are currently connected to the master device;
the recurrence information obtaining module 30 is configured to send the application exception information to the target slave device, so that the target slave device recurs an exception and obtains recurrence exception information;
an abnormal information diagnosis module 40, configured to receive a recurrence diagnosis result for the recurrence abnormal information sent by the target slave device as a target diagnosis result of the application abnormal information.
The invention also provides an abnormal off-line diagnosis device.
The abnormal offline diagnosis device comprises a processor, a memory and an abnormal offline diagnosis program which is stored on the memory and can run on the processor, wherein when the abnormal offline diagnosis program is executed by the processor, the steps of the abnormal offline diagnosis method are realized.
The method implemented when the abnormal offline diagnostic program is executed may refer to each embodiment of the abnormal offline diagnostic method of the present invention, and details thereof are not repeated herein.
The invention also provides a computer readable storage medium.
The computer readable storage medium of the present invention stores thereon an abnormal offline diagnosis program, which when executed by a processor implements the steps of the abnormal offline diagnosis method as described above.
The method implemented when the abnormal offline diagnostic program is executed may refer to various embodiments of the abnormal offline diagnostic method of the present invention, and will not be described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for causing an offline abnormality diagnosis apparatus to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An abnormal offline diagnosis method, applied to a master device, the method comprising:
acquiring application exception information;
when the master device cannot be networked, determining a target slave device which can be networked from slave devices which are currently connected with the master device;
sending the application exception information to the target slave equipment so that the target slave equipment can reproduce exception and acquire reproduction exception information;
receiving a recurrence diagnosis result for the recurrence abnormality information transmitted by the target slave device as a target diagnosis result of the application abnormality information.
2. The method of claim 1, wherein the obtaining application exception information comprises:
receiving an abnormality diagnosis instruction;
acquiring application detection information from the running condition of a foreground application of the main equipment based on the abnormity diagnosis instruction;
judging whether the application detection information meets a preset abnormal judgment condition or not;
and if so, generating the application abnormal information based on the application detection information.
3. The method of claim 2, wherein the application detection information comprises runtime and/or resource lookup results,
the judging whether the application detection information meets the preset abnormal judgment condition comprises the following steps:
judging whether the times of detecting the running time to be abnormal in a preset time length exceeds a preset first time threshold value and/or whether the times of errors of the resource searching result exceeds a preset second time threshold value;
if the number of times of detecting that the running time is abnormal exceeds a preset first time threshold value and/or the number of times of detecting that the resource searching result is wrong exceeds a preset second time threshold value within a preset time length, judging that the application detection information meets a preset abnormal judgment condition;
and if the times of detecting that the running time is abnormal do not exceed a preset first time threshold value and the times of detecting the resource searching result is wrong do not exceed a preset second time threshold value within a preset time length, judging that the application detection information does not meet a preset abnormal judgment condition.
4. The method of claim 1, wherein there are a plurality of slave devices to which the master device is currently connected,
when the master device cannot be networked, determining a target slave device which can be networked from slave devices which are currently connected with the master device comprises the following steps:
when the master device cannot be networked, searching a plurality of locally connected slave devices, and sending networking test instructions to the plurality of locally connected slave devices;
when target feedback information for the networking test instruction fed back by the plurality of slave devices is received, the slave device with the highest feedback speed is selected as the target slave device from the plurality of slave devices feeding back the target feedback information.
5. The method of claim 1, wherein the recurring exception information comprises first recurring information,
the sending the application exception information to the target slave device for the target slave device to reproduce the exception and acquire reproduction exception information includes:
sending the application exception information to the target slave equipment so that the target slave equipment can reproduce exception;
when the target slave device detects that the first recurrence information exists, the first recurrence information actively reported by the target slave device is obtained, wherein the first recurrence information is abnormal information which locally exists in the target slave device and is matched with the application abnormal information.
6. The method of claim 5, wherein the recurring exception information includes second recurring information,
after sending the application exception information to the target slave device for the target slave device to reproduce an exception, the method further includes:
when the target slave device detects that the first recurrence information does not exist, receiving a recurrence information detection result fed back by the target slave device, and sending an application downloading instruction to the target slave device based on the recurrence information detection result, so that the target slave device can access a cloud server to download and install a target application with abnormality in the application abnormality information;
and receiving second recurrence information sent by the target slave device, wherein the second recurrence information is abnormal information which is obtained after the target slave device installs the target application and is matched with the application abnormal information.
7. The method of any one of claims 1-6, wherein the receiving, as the target diagnostic result of the application anomaly information, a recurring diagnostic result for the recurring anomaly information sent by the target slave device further comprises:
and sending a networking diagnosis instruction to the target slave equipment, so that the target slave equipment reports the recurrence abnormal information to a cloud server based on the networking diagnosis instruction to obtain the recurrence diagnosis result.
8. An abnormality offline diagnosis apparatus, comprising:
the abnormal information acquisition module is used for acquiring application abnormal information;
the device connection determining module is used for determining target slave devices which can be networked from the slave devices which are currently connected with the master device when the master device cannot be networked;
the recurrence information acquisition module is used for sending the application exception information to the target slave equipment so as to enable the target slave equipment to recur the exception and acquire recurrence exception information;
an anomaly information diagnosis module for receiving a recurrence diagnosis result for the recurrence anomaly information sent by the target slave device as a target diagnosis result of the application anomaly information.
9. An abnormality offline diagnosis apparatus characterized by comprising: a memory, a processor, and an exception offline diagnostic program stored on the memory and executable on the processor, the exception offline diagnostic program when executed by the processor implementing the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium, having stored thereon an abnormal offline diagnostic program, which when executed by a processor, implements the steps of the method of any one of claims 1 to 7.
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