Link analysis method and device, electronic equipment, storage medium and vehicle

Abstract

The application relates to a link analysis method and device, electronic equipment, a storage medium and a vehicle, which comprises the following steps: detecting whether specified type abnormal log data exists in a log data set; in the case that the specified type abnormal log data exists, obtaining the equipment identifier of the vehicle corresponding to the specified type abnormal log data; querying the service link topology graph corresponding to the equipment identifier according to the equipment identifier; and analyzing and processing the nodes in each link in the service link topology graph to determine the abnormal nodes in each link. The application can help testers and developers to quickly locate the fault range and analyze the fault cause through tracking and analyzing the related service links of the vehicle and visually displaying the link topology graph, improve the troubleshooting efficiency, reduce the labor cost and save the network resources.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of Internet of Vehicles, and in particular to a link analysis method and device, an electronic device, a storage medium and a vehicle. BACKGROUND

[0002] With the rapid development of Internet of Vehicles technology, remote control of a vehicle through a mobile device and monitoring of the safety of the vehicle as a core function of Internet of Vehicles are relatively complex in terms of data flow, data analysis and control of a Telematics BOX (T-BOX).

[0003] The present application relates to the technical field of Internet of Vehicles, and in particular to a link analysis method and device, an electronic device, a storage medium and a vehicle. SUMMARY

[0004] To overcome the problems in the prior art, the present application provides a link analysis method, device, electronic device, storage medium and vehicle.

[0005] According to a first aspect of an embodiment of the present application, a link analysis method is provided, characterized in that the method comprises:

[0006] detecting whether there is specified type of abnormal log data in a log data set;

[0007] in a case where it is detected that there is the specified type of abnormal log data, obtaining a device identifier of a vehicle corresponding to the specified type of abnormal log data;

[0008] querying a service link topology graph corresponding to the device identifier according to the device identifier;

[0009] analyzing and processing nodes in each link in the service link topology graph to determine abnormal nodes in each link.

[0010] Optionally, before the step of detecting whether there is specified type of abnormal log data in the log data set, the method comprises:

[0011] performing burying point collection on business data of a vehicle according to a pre-set burying point data protocol, generating the log data based on the collected business data, and storing the log data in a burying point database.

[0012] Optionally, before the step of querying a service link topology graph corresponding to the device identifier according to the device identifier, the method further comprises:

[0013] querying nodes in a search engine corresponding to the embedded database, to obtain all nodes corresponding to the log data, relationship information between the nodes, and the number of the log data;

[0014] generating a service link topology graph according to the all nodes, the relationship information between the nodes, and the number of the log data.

[0015] Optionally, before the step of querying the service link topology graph corresponding to the device identifier according to the device identifier, the method further comprises:

[0016] acquiring keyword data from the abnormal log data according to a preset rule;

[0017] querying nodes in a search engine corresponding to the embedded database according to the keyword data, to obtain all nodes corresponding to the keyword data, relationship information between the nodes, and the number of log data associated with the keyword data;

[0018] generating a service link topology graph according to the all nodes corresponding to the keyword data, the relationship information between the nodes, and the number of log data associated with the keyword data.

[0019] According to a second aspect of the embodiments of the present application, a link analysis device is provided, and the device comprises:

[0020] a detection module configured to detect whether there is abnormal log data of a specified type in a log data set;

[0021] a first acquisition module configured to, in a case where it is detected that there is the abnormal log data of the specified type, acquire a device identifier of a vehicle corresponding to the abnormal log data of the specified type;

[0022] a query module configured to query a service link topology graph corresponding to the device identifier according to the device identifier;

[0023] an analysis module configured to analyze and process each link node in the service link topology graph, to determine abnormal nodes in each of the links.

[0024] Optionally, the device further comprises:

[0025] a first generation module configured to perform embedded collection on business data of a vehicle according to a preset embedded data protocol, and generate the log data based on the collected business data, wherein the log data is stored in the embedded database.

[0026] Optionally, the device further comprises:

[0027] The node query module is configured to perform node query in a search engine corresponding to the implant database, to obtain all nodes corresponding to the log data, relationship information between the nodes, and the number of the log data.

[0028] The second generation module is configured to generate a service link topology graph according to the all nodes, the relationship information between the nodes, and the number of the log data.

[0029] According to a third aspect of an embodiment of the present application, an electronic device is provided, comprising:

[0030] a processor;

[0031] a memory for storing instructions executable by the processor;

[0032] The processor is configured to execute the instructions to implement the link analysis method according to the first aspect.

[0033] According to a fourth aspect of an embodiment of the present application, a computer readable storage medium is provided, when instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to perform the link analysis method according to the first aspect of the present application.

[0034] According to a fifth aspect of an embodiment of the present application, a vehicle is provided, comprising the link analysis device according to the second aspect of the present application.

[0035] The technical solution provided by the embodiments of the present application can have the following beneficial effects:

[0036] The present application can detect whether there is specified type of abnormal log data in the log data set; in the case where it is detected that there is specified type of abnormal log data, the device identifier of the vehicle corresponding to the specified type of abnormal log data is acquired; the service link topology graph corresponding to the device identifier is queried according to the device identifier; the nodes in each link in the service link topology graph are analyzed and processed to determine the abnormal nodes in each link. That is, according to the abnormal log data in the log data set, the device identifier of the vehicle corresponding to the abnormal log data is acquired, the nodes in each link in the service link topology graph determined according to the device identifier are analyzed and processed to find the abnormal nodes, and link tracking analysis is realized. Since the visual service link topology graph can be provided to the operation and maintenance personnel, the problem that in the prior art, complex links and technical systems cannot be quickly tracked and troubleshot is solved, through the technical solution provided by the embodiments of the present application, the related business link of the vehicle can be tracked and analyzed, and the link topology graph can be visually displayed, which helps the test and development personnel to quickly locate the fault range and analyze the fault cause, improves the troubleshooting efficiency, reduces the labor cost, and saves network resources.

[0037] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application, as claimed. BRIEF DESCRIPTION OF DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and serve to explain the principles of the application, in which, like reference numerals designate corresponding parts throughout the several views.

[0039] Figure 1 is a flowchart of a link analysis method according to an exemplary embodiment;

[0040] Figure 2 is a block diagram of a link analysis apparatus according to an exemplary embodiment;

[0041] Figure 3 is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0042] The exemplary embodiments will now be described in detail with reference to the accompanying drawings. The following description is made with reference to the accompanying drawings, in which like reference numerals in different drawings designate identical or similar constituents, and the following description does not represent all of the aspects of the present application. Rather, the following description merely presents some aspects of the present application, by way of example only, with unawareness that the scope of the aspects of the present application as claimed herein are not limited thereto.

[0043] A first embodiment of the present application relates to a link analysis method, Figure 1 is a flowchart of a link analysis method according to an exemplary embodiment, as Figure 1 shown, including the steps of:

[0044] In step 101, it is detected whether there is abnormal log data of a specified type in the set of log data.

[0045] In this embodiment, the log data records vehicle status, vehicle status commands, and other core business logs. Specifically, it could be, for example, when a remote control command is sent to the vehicle's T-BOX via a mobile app, this process includes sending an activation SMS, encoding and decoding the control command, and judging the command sending result, etc. At this time, it is necessary to record the relevant commands. Alternatively, the vehicle's T-BOX can upload vehicle status information to the vehicle network platform. The T-BOX, acting as a wireless gateway, provides a remote communication interface to the vehicle through 4G remote wireless communication, GPS satellite positioning, accelerometer sensing, and CAN communication. It provides services including driving data collection, driving trajectory recording, vehicle fault monitoring, remote vehicle query and control (locking / unlocking, air conditioning control, window control, engine torque limiting, engine start / stop), driving behavior analysis, and 4G wireless hotspot sharing. The log data set includes all log data, as well as abnormal log data.

[0046] In this embodiment of the application, the system detects whether there is abnormal log data in the log data set. Specifically, it can automatically detect whether there is abnormal log data in the log data set at a preset time interval. The preset time interval can be set based on the actual situation. For example, it can be defined as checking once every 5 minutes according to the requirements, or checking once every certain number of data. For example, the system can automatically detect whether there is abnormal log data every time the data tracking database is updated by 50 log data. This application does not make any specific limitations on this.

[0047] It should be noted that the log data in this embodiment has three log levels, specifically: the first level can be represented as "INFO," indicating that everything is running as expected; the second level can be represented as "WARNING," indicating that it does not affect business operations or the business chain, but requires long-term monitoring of similar issues, such as problems in the data parsing process that do not affect command issuance; the third level can be represented as "ERROR," indicating that it affects the business process and customer usage, such as the inability to issue remote control commands. The above representation of log levels is merely a demonstration format for the convenience of those skilled in the art, and this application does not impose any specific limitations on it. Therefore, by automatically detecting whether there is abnormal log data of a preset level in the log data set at preset time intervals, that is, if there is abnormal log data of the second and third levels in the log data set, it means that there is a problem affecting the business chain or a problem that is about to occur affecting the business chain. At this time, it is necessary to further analyze the nodes and data of the entire chain in the execution process of the vehicle in the whole system to determine whether the vehicle is executing the business logic normally.

[0048] Further, it needs to be explained that before detecting whether the specified type of abnormal log data exists in the log data set, the business data of the vehicle needs to be collected by burying points, which specifically includes the following contents:

[0049] The business data of the vehicle is collected by burying points according to the pre-set burying point data protocol, and the log data is generated based on the collected business data, and the log data is stored in the burying point database.

[0050] It needs to be explained that the burying point database is a burying point database composed of log data of key business data collected by adding burying point business logic in the whole vehicle condition and vehicle control business process of the vehicle. The log data is an event record generated by the communication equipment when it is running, and each row of log can record the date, time, historical data and related operations. The business data of the vehicle includes data information corresponding to remote control and vehicle condition reporting and other businesses. In addition, it can also be any data related to the vehicle, which is not limited in the present application. In the whole Internet of Vehicles platform system, four logics of adding burying point information collection, burying point information storage, information retrieval and problem analysis are added, so as to troubleshoot the faults of each link through the Internet of Vehicles platform system, and improve the troubleshooting ability of vehicle remote control fault and vehicle condition fault. In the burying point information storage link, the database can use mongodb, mysql, ES, etc., which is not limited in the present application. Based on the burying point data protocol, the burying point component collects burying point data, which can record the burying point data in the form of log to the file, and then store the log data in the burying point database.

[0051] Therefore, the present application pre-sets the burying point data protocol, wherein the burying point data protocol includes the dimensions of pre-set device identification, encrypted device identification, burying point data source, burying point data target, burying point data protocol type, event identification, instruction ID, business log, log level, wherein the burying point data source indicates the source of the identification data, for example, the burying point data comes from TBOX, Kafak, redis, etc.; the burying point data target indicates the target of the data, for example, the target of the burying point data is Tbox gateway, data analysis service, etc.; the protocol type indicates the type of the data protocol; the event identification indicates the data flow direction, for example, the data flow direction is uplink, downlink or unknown; the instruction ID indicates a business instruction, for example, a remote control business instruction; the business log is a record of vehicle condition, vehicle condition instruction and other business core log, which is used for analysis and processing; and the log level is divided into three levels.

[0052] To facilitate troubleshooting for vehicle network platform maintenance personnel, after collecting vehicle business data according to a pre-set data collection protocol and generating log data based on the collected business data, a corresponding service link topology diagram needs to be generated from the log data. This topology diagram, as a visual representation of the links, can intuitively show maintenance personnel faulty or abnormal nodes, making it easier for them to pinpoint the time, scope, and impact of problems. It's important to note that a link is essentially a physical path from one node to an adjacent node, without any other exchange nodes in between. During data communication, the path between two computers is often composed of many linked links. In this embodiment, for example, when performing vehicle services such as remote control or vehicle status reporting, there are many physical links (links between software modules or services) involved in the data interaction itself. Specifically, based on the dimension fields corresponding to the business data contained in the log data, such as the data source and data target in the business data, a link topology diagram is generated. Then, through the service link topology diagram, the nodes and data of the entire link in the execution process of the target vehicle in the entire system are analyzed, ultimately determining whether the target vehicle is executing the business logic normally.

[0053] In step 102, if abnormal log data of a specified type is detected, the device identifier of the vehicle corresponding to the abnormal log data of the specified type is obtained.

[0054] It should be noted that each vehicle has a unique device identifier, similar to a person's ID card, representing the vehicle's identification information. In this application embodiment, the device identifier is the unique identifier representing the vehicle's TBOX, which can be a Vehicle Identification Number (VIN) or a device number. The VIN consists of 17 characters and is the vehicle's ID number, containing information such as the vehicle's manufacturer, year, model, body style and code, engine code, and assembly location. Further anonymization processing is performed on the device identifier; for example, the last four digits of the VIN are retained, with the rest represented by "*". To ensure data security, the device identifier is also subjected to MD5 hashing to prevent reverse engineering. Data encryption is performed for the user's vehicle information. From a security perspective, encryption is performed in the database. When searching, the user can enter the VIN, which is compared in the database. The plaintext input by the business personnel is converted to ciphertext in the background, protecting user data privacy. This application can use any encryption method for data encryption and decryption; no specific limitation is made.

[0055] Therefore, by searching through the vehicle's device identifier, one can locate the vehicle, and determine when and what it did. Conversely, if abnormal log data is detected, the corresponding vehicle's device identifier can also be obtained through the abnormal log data.

[0056] In step 103, the service link topology map corresponding to the device identifier is queried based on the device identifier.

[0057] After determining the device identifier corresponding to the abnormal log data, the corresponding service link topology can be queried based on the device identifier. In addition, to facilitate maintenance personnel in troubleshooting fault information, besides visually displaying the service link topology, this application can further provide a problem analysis platform for data analysis. This problem analysis platform is built on a data tracking database and can accurately locate relevant vehicle information based on the device identifier or any predefined dimension field in the data tracking protocol. Furthermore, this problem analysis platform can display the log topology, i.e., the service link topology. For example, the service link topology can be viewed based on the vehicle VIN code (device identifier), and it can be further expanded to multi-dimensional search, such as querying based on the device identifier or event identifier.

[0058] It should be noted that, in this embodiment of the application, the service link topology map needs to be obtained before obtaining the service link topology map corresponding to the device identifier based on the device identifier. Specifically, this includes:

[0059] Perform a node query in the search engine corresponding to the data tracking database to obtain all nodes corresponding to the log data, the relationship information between the nodes, and the number of log data; generate a service link topology diagram based on the number of nodes and log data.

[0060] It should be noted that in the embodiments of the present application, the log data is obtained from the log data set, and the search engine corresponding to the point-in-time database is a service search engine, i.e., a search server, for example, an elasticsearch search server. Based on the aggregation function existing in the search engine itself, all nodes in the service link of the business data and the number of each node corresponding to the nodes can be queried. It should be noted that the node represents a specific service in the present application, the number of the node corresponds to the number of the log data in the present application, and the relationship information between the nodes represents the source and destination of the business data. The source and destination of the business data can be obtained to know how each node in the service link is connected. For example, the terminal is TBOX, the service is gateway, the middleware is kafka, at 5.1 o'clock on the day, TBOX is connected to the gateway, the gateway transmits data to the kafka, the data parsing service obtains data from the kafka, and stores the data into the mysql database. In the whole data flow process, a total of five nodes are passed through. Specifically, the A node represents TBOX, the B node represents gateway, the C node represents kafka, the D node represents data parsing service, and the E node represents mysql. Assuming that a certain data must pass through the five nodes, according to the relationship information between the nodes (the source and destination of the data in each node), it can be concluded that the service link of the data is A-B-C-D-E. For the log data, A-B prints a log in the gateway, and then prints a B-C log. After D receives the data, it prints a C-D log, and so on. The topology graph, also called a topology structure graph, is a network structure graph composed of computers, network devices and other devices. The topology graph can quantitatively convey information through graphics, and the quantity comparison is very intuitive. It is an effective form of quantitative graph. Therefore, based on the nodes confirmed in the service link, the relationship information between the nodes and the number of the log data, the front-end developer can present the service link topology graph in a visual form based on the principle of the topology graph. Through the visual link topology graph, the business personnel can quickly locate the problem when querying the fault.

[0061] In another embodiment, obtaining the service link topology graph further includes: obtaining keyword data from the abnormal log data according to a preset rule; performing node query in the search engine corresponding to the point-in-time database according to the keyword data to obtain all nodes corresponding to the keyword data, relationship information between the nodes and the number of log data associated with the keyword data; and generating the service link topology graph according to the all nodes corresponding to the keyword data, the relationship information between the nodes and the number of log data associated with the keyword data.

[0062] It should be noted that in the embodiments of the present application, in addition to querying the node related information through the database engine to generate the topology graph, further, the topology graph can be acquired according to the keyword data. In addition to being acquired from the abnormal log according to the preset rule, the keyword data can also be acquired according to the information fed back by the user, for example, when the user actively reports a fault through the vehicle network platform, at this time, the high-frequency words in the fault reporting information can be acquired, for example, connection timeout, parsing error, system exception, etc., the keyword data can also be determined according to the frequency of occurrence of the business related words from the business data, or the keyword data is determined based on the frequency of occurrence of a certain dimension in the business data in a certain time, which is not limited in the present application.

[0063] The topology graph is acquired through the keyword. Specifically, for example, the content corresponding to a certain log data is: "connection timeout when sending the SMS verification code to the CMP system", next time, if "verification code" or "connection timeout" is searched through the database engine, the log data or other log data related to the keyword can be matched through the fuzzy search of the database engine, therefore, the number of log data can be counted, and then all the nodes in the service link of the business data can be queried based on the aggregation function existing in the search engine, then the nodes corresponding to each keyword can also be queried, for example, "connection timeout" is searched, within a preset time range, all the nodes related to the keyword data can be queried, and then the visual service link topology graph can be generated through the front end according to the nodes, the relationship information between the nodes and the number of log data.

[0064] In step 104, the nodes in each link in the service link topology graph are analyzed and processed to determine the abnormal nodes in each link.

[0065] It should be noted that the link is essentially a physical line from one node to an adjacent node without any other switching nodes in between. When data communication is performed, the path between two computers is often composed of many links. In the embodiments of the present application, for example, when the vehicle business such as remote control or vehicle condition reporting is completed, there are many physical links (links between software modules or services) for data interaction. Therefore, after the service link topology graph is acquired, the nodes in each link in the service link topology graph can be analyzed and processed to determine the abnormal nodes, and the visual topology graph combining logic and physics can more intuitively and clearly see the connection between each node and interface in the link, reflecting the structural relationship of the device entity.

[0066] It should be noted that after obtaining the service link topology diagram, analysis and processing are required to identify abnormal nodes. Specifically, business personnel can analyze the situation as follows: For example, in a routine investigation, when a vehicle user reports a problem with a particular vehicle, they can perform a routine search in the tracking database's search engine (e.g., Elasticsearch) using the keywords provided by the user. Business personnel can then quickly view the link status of each node through the service connection topology diagram. Alternatively, the system can automatically report abnormal information. In this embodiment, the entire link result for a routine business link is preset according to certain rules. For example, in the vehicle remote control service, from the issuance of the remote control command to the feedback of the command execution status... This link requires five nodes: F, D, S, W, and T. Therefore, the detection program will automatically detect a certain amount of data in the log data set at preset times or intervals. At a certain point in time, if the remote control command passes through a node whose link is different from the preset link, an anomaly will be triggered. Based on the reported anomaly information, the service link topology corresponding to the vehicle is determined, and the abnormal nodes in the link are automatically identified according to the preset link. Alternatively, the system can send a warning to the operations personnel, indicating which nodes in the link currently have level 3 anomalies, i.e., "ERROR" information, such as "ERROR exists at node S, data not received from a certain node". Business personnel can view these ERROR messages individually for further detailed investigation.

[0067] This application can detect the existence of a specified type of abnormal log data in a log dataset; if the specified type of abnormal log data is detected, obtain the device identifier of the vehicle corresponding to the specified type of abnormal log data; query the service link topology diagram corresponding to the device identifier based on the device identifier; and analyze and process the nodes in each link of the service link topology diagram to determine the abnormal nodes in each link. In other words, it obtains the device identifier of the vehicle corresponding to the abnormal log data by detecting abnormal log data in the log dataset, and analyzes and processes the nodes in each link of the service link topology diagram determined by the device identifier to find abnormal nodes, thus achieving link tracing analysis. Since it can provide maintenance personnel with a visualized service link topology diagram, it solves the problem of not being able to quickly trace and troubleshoot in the face of complex links and technical systems in existing technologies. The technical solution provided by the embodiments of this application can help testers and developers quickly locate the scope of faults and analyze the causes of faults by tracing and analyzing the relevant business links of vehicles and visually displaying the link topology diagram, thereby improving troubleshooting efficiency, reducing manpower costs, and saving network resources.

[0068] It should be noted that all embodiments in this example are only for the purpose of enabling those skilled in the art to better understand the technical solutions in this example, and are not intended to limit the structure of the link topology diagram in this example.

[0069] A second embodiment of the present application relates to a link analysis device, as shown in Figure 2 Figure 2 is a device block diagram of link analysis according to an exemplary embodiment, which comprises the following modules:

[0070] The detection module 201 is configured to detect whether there is abnormal log data of a specified type in the log data set;

[0071] The first acquisition module 202 is configured to acquire the device identifier of the vehicle corresponding to the abnormal log data of the specified type when it is detected that there is abnormal log data of the specified type;

[0072] The query module 203 is configured to query the service link topology graph corresponding to the device identifier according to the device identifier;

[0073] The analysis module 204 is configured to analyze and process each link node in the service link topology graph, and determine the abnormal node in each link.

[0074] Optionally, the device further comprises:

[0075] The first generation module is configured to perform point embedding collection on the business data of the vehicle according to a pre-set point embedding data protocol, generate the log data based on the collected business data, and store the log data in the point embedding database.

[0076] Optionally, the device further comprises:

[0077] The node query module is configured to perform node query in the search engine corresponding to the point embedding database to obtain all nodes corresponding to the log data, relationship information between the nodes, and the number of log data;

[0078] The second generation module is configured to generate a service link topology graph according to the all nodes, the relationship information between the nodes, and the number of log data.

[0079] Optionally, the device further comprises:

[0080] The second acquisition module is configured to acquire keyword data from the abnormal log data according to a pre-set rule;

[0081] The keyword detection module is configured to perform node query in the search engine corresponding to the point embedding database according to the keyword data to obtain all nodes corresponding to the keyword data, relationship information between the nodes, and the number of log data associated with the keyword data;

[0082] ​The third generation module is configured to generate a service link topology graph according to all nodes corresponding to the keyword data, relationship information between the nodes, and a quantity of log data associated with the keyword data.

[0083] The application can detect whether there is specified type of abnormal log data in the log data set, acquire the device identifier of the vehicle corresponding to the specified type of abnormal log data in the case of detecting that there is specified type of abnormal log data, query the service link topology graph corresponding to the device identifier according to the device identifier, and analyze and process the nodes in each link in the service link topology graph to determine the abnormal nodes in each link. That is, the device identifier of the vehicle corresponding to the abnormal log data in the log data set is acquired according to the abnormal log data in the log data set, the nodes in each link in the service link topology graph determined according to the device identifier are analyzed and processed to find the abnormal nodes, and the link tracking analysis is realized. Since the visual service link topology graph can be provided to the operation and maintenance personnel, the problem that the existing technology cannot quickly track and troubleshoot in the face of complex links and technical systems is solved, the technical solution provided by the embodiments of the application can track and analyze the related business links of the vehicle, and the link topology graph can be visually displayed, which helps the test and development personnel to quickly locate the fault range and analyze the fault reason, improves the troubleshooting efficiency, reduces the labor cost, and saves the network resources.

[0084] As to the apparatus in the above-described embodiments, specific manners in which various modules perform operations have been described in details in the embodiments of the method, and thus will not be described in details here.

[0085] The third embodiment of the application relates to a vehicle comprising the link analysis apparatus in the second embodiment of the application.

[0086] Figure 3 is a block diagram of an electronic device 1400 according to an exemplary embodiment. The electronic device 1400 can be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0087] Referring to Figure 3 , the electronic device 1400 can include one or more of the following components: a processing component 1402, a memory 1404, a power supply component 1406, a multimedia component 1408, an audio component 1410, an input / output (I / O) interface 1412, a sensor component 1414, and a communication component 1416.

[0088] The processing component 1402 generally controls the overall operation of the device 1400, such as the operation of the display, telephony calls, data communications, camera operations, and recording operations. The processing component 1402 can include one or more processors 1420 to execute instructions and to complete all or part of steps of the above-described methods. In addition, the processing component 1402 can include one or more modules to facilitate interaction with off-chip components. For example, the processing component 1402 can include a multimedia module to facilitate the interaction between the multimedia component 1408 and the processing component 1402.

[0089] The memory 1404 is configured to store various types of data to support operations of the device 1400. Examples of these data include instructions for any applications or methods operating on the device 1400, contact data, phonebook data, messages, pictures, videos, and so on. The memory 1404 can be implemented by any type of volatile or non-volatile storage devices or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk, or optical disk.

[0090] The power component 1406 supplies various components of the electronic device 1400 with power. The power component 1406 can include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 1400.

[0091] The multimedia component 1408 includes a screen providing an output interface between the electronic device 1400 and a user. In some embodiments, the screen can include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes the touch panel, the screen can be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense a touch, a slide, and a gesture on the touch panel. The touch sensors can not only sense a boundary of a touching or sliding action, but also detect duration and pressure related to the touching or sliding action. In some embodiments, the multimedia component 1408 includes a front camera and / or a rear camera. When the electronic device 1400 is in an operation mode, such as a photographing mode or a video mode, the front camera and / or the rear camera can receive external multimedia data. Each of the front and rear cameras can be a fixed optical lens system or have a focal length and optical zoom capability.

[0092] The audio component 1410 is configured to output and / or input audio signals. For example, the audio component 1410 includes a microphone (MIC) that is configured to receive an external audio signal when the electronic device 1200 is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode. The received audio signal can be further stored in the memory 1404 or transmitted via the communication component 1416. In some embodiments, the audio component 1410 also includes a speaker for outputting audio signals.

[0093] The input / output interface 1412 provides an interface between the processing component 1402 and peripheral interface modules, which can be a keypad, a click wheel, buttons, and the like. The buttons can include, but are not limited to, a home button, a volume button, a start button, and a lock button.

[0094] The sensor component 1414 includes one or more sensors for providing various state assessments for the electronic device 1400. For example, the sensor component 1414 can detect an open / closed state of the electronic device 1400, relative positioning of components, such as a display and a keypad of the electronic device 1400, a change in position of the electronic device 1400 or a component of the electronic device 1400, presence or absence of user contact with the electronic device 1400, an orientation or acceleration / deceleration of the electronic device 1400, and a temperature change of the electronic device 1400. The sensor component 1414 can include a proximity sensor configured to detect presence of a nearby object without any physical touch. The sensor component 1414 can further include a light sensor, such as a CMOS or CCD image sensor, for use in an imaging application. In some embodiments, the sensor component 1414 can further include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0095] The communication component 1416 is configured to facilitate wired or wireless communication between the electronic device 1400 and other devices. The electronic device 1400 can access a wireless network based on a communication standard, such as WiFi, a operator network (e.g., 2G, 3G, 4G, or 5G), or a combination thereof. In an example embodiment, the communication component 1416 receives broadcast signals or broadcast-related information from an external broadcasting management system via a broadcast channel. In an example embodiment, the communication component 1416 further includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technology.

[0096] In an exemplary embodiment, the electronic device 1400 can be implemented with one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, micro-controllers, microprocessors, or other electronic components, for performing the above-described methods.

[0097] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions, such as the memory 1404 including instructions, is also provided, which can be executed by the processor 1420 of the electronic device 1400 to complete the above-described methods. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disc, and an optical data storage device, etc.

[0098] Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the present application cover any and all variations of the application that come within the scope of the claims and their equivalents. It is intended that the specification and examples be considered exemplary only, with the true scope and spirit of the application being indicated by the following claims.

[0099] It should be noted that the above-mentioned embodiments illustrate rather than limit the application, and that one skilled in the art will be able to design many alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word 'comprising' does not exclude the presence of elements or steps other than those listed in a claim. The word 'a' or 'an' preceding an element does not exclude the presence of a plurality of such elements. The application can be implemented by means of both hardware and software, and any combination thereof. In a unit claim, several devices can be listed with a conjunction like 'and'. None of these conjunctive words expresses any limitation of a dependent claim to the devices introduced by that conjunction. The use of the word 'at least' followed by a list of one or more members does not exclude the addition of one or more other members to the list. The application is not limited to the exact construction and arrangement of the parts shown in the figures and described in the specification, and can be implemented in various modifications and variations without departing from the scope of the application. The scope of the application is limited only by the claims that follow.

Claims

1. A link analysis method characterized by, The method includes: The system detects whether there is any abnormal log data of a specified type in the log data set. The log data is a log recording vehicle status and vehicle status commands. The log data is stored in a data tracking database. The data tracking database is a database composed of log data corresponding to key business data collected by adding data tracking business logic to the entire vehicle status and vehicle control business process. The business data includes data information corresponding to remote control and vehicle status reporting business. If the specified type of abnormal log data is detected, obtain the device identifier of the vehicle corresponding to the specified type of abnormal log data; Query the service link topology map corresponding to the device identifier based on the device identifier; The nodes in each link of the service link topology are analyzed and processed to identify abnormal nodes in each link. Before the step of querying the service link topology map corresponding to the device identifier based on the device identifier, the method further includes: Perform a node query in the search engine corresponding to the data point database to obtain all nodes corresponding to the log data, the relationship information between the nodes, and the quantity of the log data. A service link topology diagram is generated based on all the nodes, the relationship information between the nodes, and the amount of log data.

2. The method of claim 1, wherein, Before the step of detecting whether there is abnormal log data of a specified type in the log data set, the method includes: According to a pre-set data collection protocol, the vehicle's business data is collected through data collection points. Based on the collected business data, the log data is generated and stored in the data collection point database.

3. The method of claim 1, wherein, Before the step of querying the service link topology map corresponding to the device identifier based on the device identifier, the method further includes: Keyword data is obtained from the abnormal log data according to preset rules; Based on the keyword data, a node query is performed in the search engine corresponding to the tracking database to obtain all nodes corresponding to the keyword data, the relationship information between the nodes, and the number of log data associated with the keyword data. A service link topology diagram is generated based on all nodes corresponding to the keyword data, the relationship information between the nodes, and the number of log data associated with the keyword data.

4. A link analysis apparatus characterized by comprising: The device includes: The detection module is used to detect whether there is abnormal log data of a specified type in the log data set; wherein, the log data is a log recording vehicle status and vehicle status instructions, the log data is stored in the tracking database, the tracking database is a database composed of tracking business logic added to the entire vehicle status and vehicle control business process corresponding to the vehicle, and log data corresponding to key business data is collected, the business data includes data information corresponding to remote control and vehicle status reporting business; The first acquisition module is used to acquire the device identifier of the vehicle corresponding to the specified type of abnormal log data when the existence of the specified type of abnormal log data is detected. The query module is used to query the service link topology map corresponding to the device identifier based on the device identifier; The analysis module is used to analyze and process each link node in the service link topology diagram to identify abnormal nodes in each link. The node query module is used to perform node queries in the search engine corresponding to the data tracking database to obtain all nodes corresponding to the log data, the relationship information between the nodes, and the quantity of the log data. The second generation module is used to generate a service link topology diagram based on all the nodes, the relationship information between the nodes, and the amount of log data.

5. The apparatus of claim 4, wherein, The device further includes: The first generation module is used to collect business data of the vehicle according to a pre-set data collection protocol, generate the log data based on the collected business data, and store the log data in the data collection database.

6. An electronic device, comprising: include: processor; Memory used to store processor-executable instructions; The processor is configured to execute the instructions to implement the link analysis method as described in any one of claims 1 to 3.

7. A computer-readable storage medium, wherein when instructions in the storage medium are executed by a processor of a mobile terminal, the mobile terminal is enabled to perform the link analysis method as described in any one of claims 1 to 3.

8. A vehicle characterized by comprising: Includes the link analysis device according to claim 4 or 5.

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