CN115649083A - Scene recognition and power consumption strategy planning method, system and equipment based on vehicle machine - Google Patents
Scene recognition and power consumption strategy planning method, system and equipment based on vehicle machine Download PDFInfo
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Abstract
The application provides a scene recognition and power consumption strategy planning method based on a vehicle machine, which comprises the steps of analyzing an application program running on the vehicle machine, and acquiring characteristic data of the application program; acquiring corresponding application scene information based on the characteristic data of the application program; and selecting a corresponding power consumption strategy aiming at the application scene information based on a preset power consumption strategy rule, and executing the corresponding power consumption strategy. According to the method and the device, the application scene information of the vehicle machine is identified, so that corresponding power consumption strategies are executed according to different application scene information, different strategies are carried out to allocate vehicle machine resources, different dynamic resource allocation strategies applied in different running states are achieved, and the power consumption of the system vehicle machine is reduced.
Description
Technical Field
The application relates to the technical field of vehicles, in particular to a scene recognition and power consumption strategy planning method and device based on a vehicle machine, an electronic device and a computer readable storage medium.
Background
With the development of vehicle-mounted intelligent terminals of automobiles, products configured in the terminals are more and more abundant. After the specific application returns to the background, the electric quantity of the vehicle can be continuously consumed, certain influence is caused on the electric quantity power consumption of the vehicle, meanwhile, the central processing unit resource of the vehicle machine is consumed, the computing capacity of the graphic processor is seized, and the problem of vehicle jamming is caused. In the existing known method, an original android management scheme is adopted by a host factory, a new solution is not provided, and after application programs such as WeChat and buffalo are returned to the background, no management and control strategy is provided, so that the application vehicle models can continuously consume various system resources of the vehicle machine of the vehicle at the background, and the problems of scene identification and power consumption of the vehicle machine cannot be solved.
Content of application
In view of the above drawbacks of the prior art, the present application provides a method, a system, and a device for scene recognition and power consumption policy planning based on a vehicle machine, so as to solve the above technical problems.
The application provides a scene recognition and power consumption strategy planning method based on a vehicle machine, which is characterized by comprising the following steps:
analyzing an application program running on a vehicle machine, and acquiring characteristic data of the application program;
acquiring corresponding application scene information based on the characteristic data of the application program;
and selecting a corresponding power consumption strategy aiming at the application scene information based on a preset power consumption strategy rule, and executing the corresponding power consumption strategy.
In an embodiment of the application, the analyzing the application running on the vehicle machine, and the obtaining the feature data of the application includes:
acquiring a feature file of an application program based on the electronic exchanger;
and acquiring the characteristic data of the application program based on the characteristic file of the application program.
In an embodiment of the application, the obtaining the feature data of the application based on the feature file of the application includes:
acquiring method domain information of the application based on the characteristic file of the application program;
acquiring method set information based on the method domain information;
and acquiring characteristic data of the application program based on the method domain information and the method set information.
In an embodiment of the application, the analyzing the application running on the vehicle machine, and the obtaining the feature data of the application includes:
acquiring distributed link tracking information based on a preset virtual machine;
acquiring hotspot information based on the distributed link tracking information;
and acquiring characteristic data of the application program based on the hotspot information.
In an embodiment of the present application, the power consumption policy rule includes: when the application scene information is game scene information, the corresponding power consumption strategy is to improve the refresh rate of the LCD and reduce the working frequency of the GPU; when the application scene information is video scene information, the corresponding power consumption strategy is to improve the refresh rate of the LCD and reduce the working frequency of the GPU; when the application scene information is WeChat scene information, the corresponding power consumption strategy is to reduce the GPU working frequency; when the application scene information is short message scene information, the corresponding power consumption strategy is to reduce the GPU working frequency and reduce the CPU working frequency; when the application scene information is the call scene information, the corresponding power consumption strategy is to reduce the refresh rate of an LCD and reduce the working frequency of a GPU; when the application scene information is payment scene information, the corresponding power consumption strategy is to improve the LCD refresh rate and reduce the GPU working frequency.
In an embodiment of the present application, the preset power consumption policy rule includes:
and presetting corresponding LCD refresh rate, GPU working frequency and CPU working frequency according to the application scene information.
The application provides a scene discernment and power consumption strategic planning system based on car machine, includes:
the analysis module is used for analyzing the application program running on the vehicle machine and acquiring the characteristic data of the application program;
the acquisition module acquires corresponding application scene information based on the characteristic data of the application program;
and the execution module selects a corresponding power consumption strategy aiming at the application scene information based on a preset power consumption strategy rule and executes the corresponding power consumption strategy.
The application provides an electronic device, including:
one or more processors;
storage means for storing one or more programs which, when executed by the one or more processors, cause the electronic device to carry out the method of any preceding claim.
The present application provides a computer readable storage medium having stored thereon computer readable instructions which, when executed by a processor of a computer, cause the computer to perform the method of any one of the above.
The present application provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium, which are read by a processor of the computer from the computer readable storage medium, the processor executing the computer instructions, causing the computer to perform the method of any of the above.
The beneficial effect of this application: the method comprises the steps of analyzing an application program running on a vehicle machine to obtain characteristic data of the application program; acquiring corresponding application scene information based on the characteristic data of the application program; the corresponding power consumption strategy is selected according to the application scene information based on a preset power consumption strategy rule, and is executed, so that the corresponding power consumption strategy can be executed by identifying the characteristics of an application program, the power consumption is reduced, the smoothness of the vehicle machine is improved, and the use experience of a user is improved.
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.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application. It is obvious that the drawings in the following description are only some embodiments of the application, and that for a person skilled in the art, other drawings can be derived from them without inventive effort. In the drawings:
FIG. 1 is a schematic diagram of a display interface of a car machine application shown in an exemplary embodiment of the present application;
fig. 2 is a schematic diagram of an implementation environment of a scene identification and power consumption policy planning method based on a vehicle machine according to an exemplary embodiment of the present application;
fig. 3 is a flowchart illustrating a scene recognition and power consumption policy planning method based on a vehicle machine according to an exemplary embodiment of the present application;
FIG. 4 is a schematic diagram of application characteristic data shown in an exemplary embodiment of the present application;
FIG. 5 is a power consumption policy diagram of application context information in an exemplary embodiment of the present application;
FIG. 6 is a flow chart of step S310 in the embodiment shown in FIG. 3 in an exemplary embodiment;
FIG. 7 is a flowchart of step S620 in the embodiment shown in FIG. 6 in an exemplary embodiment;
FIG. 8 is a flowchart of step S310 in the embodiment shown in FIG. 3 in an exemplary embodiment;
fig. 9 is a block diagram of a car-machine based scene recognition and power consumption strategy planning system according to an exemplary embodiment of the present application;
FIG. 10 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application.
Detailed Description
Other advantages and effects of the present application will become apparent to those skilled in the art from the disclosure herein, wherein the embodiments of the present application will be described in detail with reference to the accompanying drawings and preferred embodiments. The present application is capable of other and different embodiments and its several details are capable of modifications and/or changes in various respects, all without departing from the spirit of the present application. It should be understood that the preferred embodiments are for purposes of illustration only and are not intended to limit the scope of the present disclosure.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present application, and the drawings only show the components related to the present application and are not drawn according to the number, shape and size of the components in actual implementation, the type, quantity and proportion of each component in actual implementation may be changed freely, and the layout of the components may be more complicated.
In the following description, numerous details are set forth to provide a more thorough explanation of the embodiments of the present application, however, it will be apparent to one skilled in the art that the embodiments of the present application may be practiced without these specific details, and in other embodiments, well-known structures and devices are shown in block diagram form rather than in detail in order to avoid obscuring the embodiments of the present application.
Firstly, it should be noted that the power consumption strategy is a dynamic allocation mechanism, and matches system resources according to the application scene used by the user in real time, so that the waste of system background running resources can be effectively controlled, and meanwhile, the phenomena of too high vehicle power consumption, vehicle jamming and the like caused by malicious running of a vehicle machine 'rogue' background can be avoided.
Fig. 1 is a schematic diagram of a car machine application display interface according to an exemplary embodiment of the present application, where an interface that displays a current car machine running in the car machine application display interface includes: weChat, payment, game, conversation, and the like. According to the scene identification and power consumption strategy planning method based on the vehicle machine, the current application scene information is identified, the corresponding power consumption strategy is selected aiming at the application scene information based on the preset power consumption strategy rule, and the corresponding power consumption strategy is executed. For example, the current application scenario information is identified as a call application scenario, and operations of reducing the GPU working frequency and reducing the LCD refresh rate are performed for the call application scenario based on the preset power consumption policy rule.
The graphic processor (abbreviated as GPU) is a microprocessor dedicated to image and graphic related operations on a personal computer, a workstation, a game machine, and some mobile devices (e.g., tablet computers, smart phones, etc.). The GPU reduces the dependence of the graphics card on the CPU, and performs part of the original CPU work, and particularly, the core technologies adopted by the GPU in 3D graphics processing include hardware T & L (geometric transformation and illumination processing), cubic environment texture mapping and vertex mixing, texture compression and bump mapping, a dual-texture four-pixel 256-bit rendering engine, and the like, and the hardware T & L technology can be said to be a mark of the GPU.
The Central Processing Unit (CPU) is a final execution unit for information processing and program operation, and serves as an operation and control core of the computer system.
Herein, the acronym of LCD, i.e., liquid Crystal Display, means a "Liquid Crystal Display", i.e., a Liquid Crystal Display. The LED display is one of Liquid Crystal Displays (LCDs), i.e., a Liquid Crystal Display (LCD) using LEDs (light emitting diodes) as a backlight source. As can be seen, the LCD includes LEDs.
The embodiment of the application also does not limit the detailed information displayed on the vehicle application display interface, and can be set according to actual requirements.
Fig. 2 is a schematic diagram of an implementation environment of a scene identification and power consumption policy planning method based on a vehicle machine according to an exemplary embodiment of the present application. As shown in fig. 2, during the use of the vehicle 210, the current application information is displayed on the in-vehicle application display interface 2101, and the in-vehicle application performs the corresponding power consumption policy based on the current application context information by identifying the current application context information.
It can be seen that, under the condition that the vehicle is running normally, software currently used by the vehicle machine is uncertain, and if the same strategy is adopted for different software, resource waste or insufficient memory may be caused, which may cause various problems. To solve the problems, embodiments of the present application respectively provide a scene recognition and power consumption policy planning method based on a vehicle machine, a scene recognition and power consumption policy planning system based on a vehicle machine, an electronic device, a computer-readable storage medium, and a computer program product, which will be described in detail below.
Referring to fig. 3, fig. 3 is a flowchart illustrating a scene recognition and power consumption policy planning method based on a vehicle machine according to an exemplary embodiment of the present application. The method may be applied to the implementation environment shown in fig. 2, and is specifically executed by a vehicle in the implementation environment. It should be understood that the method may be applied to other exemplary implementation environments and is specifically executed by devices in other implementation environments, and the embodiment does not limit the implementation environment to which the method is applied.
As shown in fig. 3, in an exemplary embodiment, the method for scene recognition and power consumption policy planning based on a vehicle machine at least includes steps S310 to S330, which are described in detail as follows:
and S310, analyzing the application program running on the vehicle machine, and acquiring the characteristic data of the application program.
Firstly, it should be noted that the vehicle corresponding to the vehicle device refers to a vehicle where the vehicle device is located, the vehicle device refers to a vehicle-mounted infotainment product installed inside a car for short, and the vehicle device is required to be capable of realizing information communication between a person and a car, and between a car and the outside (car and car) in terms of function. Most of the car machines are installed in the center console, some car machines are connected with the screen, and some car machines are separated from the screen. With the development of science and technology, car navigation has been developed from early CD and DVD navigation to intellectualization and informatization. The functions of the existing vehicle machine are that the functions of 3G and Telematics are provided in addition to the functions of traditional radio, music video playing and navigation, the CAN-BUS technology of the automobile CAN be combined, the information communication between people and the automobile and between the automobile and the outside is realized, and the functions related to user experience, service and safety are enhanced. Telematics is a compound word of Telecommunications and information science (information) for long-distance communication, and may be literally defined as a service system providing information through a computer system built in a vehicle such as an automobile, an aviation, a ship, a train, etc., a wireless communication technology, a satellite navigation device, and an internet technology exchanging information such as text, voice, etc. In short, the vehicle is connected to the internet through a wireless network, and various information necessary for driving and life is provided for the vehicle owner.
Specifically, the application program refers to a program that can be installed and run on the car machine, and includes but is not limited to: game programs, video programs, weChat programs, short message programs, call programs, payment programs, and the like.
It is also to be understood that the characteristic data of an application refers to data that is capable of identifying the application. The characteristic data of the application program includes, but is not limited to, application name data, application file data, application index data, application startup data, and the like.
Step S320, acquiring corresponding application scenario information based on the feature data of the application program.
Specifically, according to the feature data of the application program, the corresponding application scenario information is determined from the feature data of the application program. The application scene information refers to information such as an application scene and a current running state. Specifically, the scene of the application can be identified by the application name data. For example, the application name data corresponding to each application is different, such as: all programs such as WeChat, payment, call, video, games and the like have corresponding application names, and then the application programs can be identified based on the application names so as to determine corresponding application scenes. For example, the game program corresponds to a game application scene, the video program corresponds to a video application scene, the wechat program corresponds to a wechat application scene, the message program corresponds to a message application scene, the call program corresponds to a call application scene, and the payment program corresponds to a payment application scene.
Specifically, the current running state refers to the current state of the application including: foreground running, background hanging, etc. The identification may be by application launch data. The application launch data includes, but is not limited to: activity data, specifically, activity is an interface for interaction with a user, and provides a window for the user to complete related operations. Activity lifecycles include, but are not limited to: creation, foreground running, stopping, destruction, background suspension, etc. Thus, the current state of the application can be judged by the lifecycle of Activity.
Step S330, selecting a corresponding power consumption strategy aiming at the application scene information based on a preset power consumption strategy rule, and executing the corresponding power consumption strategy.
Specifically, the preset power consumption policy rule refers to setting up a corresponding power consumption policy for different application scenarios, and executing the corresponding power consumption policy based on the corresponding application scenarios.
Specifically, as shown in fig. 4, the following application programs are listed: corresponding application program characteristic data are extracted in scenes such as WeChat, payment, call, video, games and the like and are added into a control strategy, different strategies are carried out to allocate vehicle machine resources according to whether the application runs in the foreground or hangs in the background, different dynamic resource allocation strategies applied in different running states are achieved, and power consumption of the system vehicle machine is reduced.
Specifically, the preset power consumption policy rule includes: and presetting corresponding LCD refresh rate, GPU working frequency and CPU working frequency according to the application scene information.
Specifically, as shown in fig. 5, the following application programs are listed: when the application scene information is game scene information, the corresponding power consumption strategy is to improve the refresh rate of the LCD and reduce the working frequency of the GPU; when the application scene information is video scene information, the corresponding power consumption strategy is to improve the refresh rate of the LCD and reduce the working frequency of the GPU; when the application scene information is WeChat scene information, the corresponding power consumption strategy is to reduce the GPU working frequency; when the application scene information is short message scene information, the corresponding power consumption strategy is to reduce the GPU working frequency and reduce the CPU working frequency; when the application scene information is the call scene information, the corresponding power consumption strategy is to reduce the refresh rate of an LCD and reduce the working frequency of a GPU; when the application scene information is payment scene information, the corresponding power consumption strategy is to improve the LCD refresh rate and reduce the GPU working frequency. After the application scene information is acquired, in the application running process, a specific application scene is determined according to the application scene information, and scene power consumption control is performed according to the power consumption strategy, so that the screen refresh rate, the graphics processor resource, the central processor resource and the like of the system are controlled.
Fig. 6 is a flow chart of step S310 in the embodiment shown in fig. 3 in an exemplary embodiment. As shown in fig. 6, the analyzing the application running on the in-vehicle device and the obtaining the feature data of the application may include steps S610 to S620, which are described in detail as follows:
step S610, acquiring a feature file of the application program based on the electronic switch.
Specifically, the electronic switch includes: the dex tool is used for extracting a file in a dex format, the dex file is an executable file of an android system and contains all operation instructions and runtime data of an application program, and the dex file comprises: a file header, an index area, a data area, etc. And the dex file comprises a feature file of the application program.
Step S620, obtaining feature data of the application program based on the feature file of the application program.
Specifically, the feature data of the application refers to data that can identify the application. The characteristic data of the application program includes, but is not limited to, application name data, application file data, application index data, application start data, and the like.
Fig. 7 is a flow chart of step S620 in the embodiment shown in fig. 6 in an exemplary embodiment. As shown in fig. 7, the obtaining of the feature data of the application program based on the feature file of the application program may include steps S710 to S730, which are described in detail as follows:
step S710, obtaining method domain information of the application based on the feature file of the application program.
Specifically, in the integration process, a dex tool is required to be passed in advance, the dex tool is used for obtaining a tool which is an executable file of the virtual machine, the feature file is directly extracted, the method domain information of the application is obtained through the feature file of the application, so that a method set is extracted, and the specific application is identified through the method set and the method domain. The method domain information refers to type information, constants, static variables and code cache information compiled by a just-in-time compiler, which are used for storing the type information loaded by the virtual machine. The method domain information includes application name data, application file data, application index data, application startup data, and the like.
Step S720, acquiring method set information based on the method domain information.
Specifically, the method set information refers to a method set that can be called by a certain application. For example, type A implements the a1 method, B inherits from A, B implements the B1 method, C inherits from B, and C implements the C1 method. Then the method set of A is the method set that A can call, the method set of A is a1, the method set of B is a1, B1, and the method set of C is a1, B1, C1. The calling method of the application program can be obtained according to the method domain information, so that the obtained calling method set is the method set, and the method set information is obtained.
Step S730, obtaining feature data of the application program based on the method domain information and the method set information.
Specifically, the feature data of the application refers to data that can identify the application. The characteristic data of the application program includes, but is not limited to, application name data, application file data, application index data, application start data, and the like. And feature data of the application can be acquired from the method domain information and the method set information.
Fig. 8 is a flowchart illustrating a scene recognition and power consumption policy planning method based on a vehicle machine according to another exemplary embodiment of the present application. As shown in fig. 7, the method further includes steps S710 to S730 based on the embodiment shown in fig. 3, and the following details are introduced:
step S710, acquiring a second estimated time for the navigation object to reach the navigation end point from the navigation passing point.
It should be noted that, in the solution provided in this embodiment, the navigation point string of the navigation path includes a navigation passing point, where the navigation passing point refers to an intermediate point between the navigation start point and the navigation end point on the navigation path, and may be understood as a position where the navigation passing point is located when the navigation object reaches the navigation end point.
Fig. 8 is a flow chart of step S310 in the embodiment shown in fig. 3 in an exemplary embodiment. As shown in fig. 7, the analyzing the application running on the in-vehicle device and the obtaining the feature data of the application may include steps S810 to S830, which are described in detail as follows: .
Step S810, obtaining distributed link tracking information based on a preset virtual machine. Specifically, the distributed link trace information is obtained through the Dalvik virtual machine. The Dalvik virtual machine runs Dalvik bytecodes, which are converted from java bytecodes and packed into a dex executable file, and executes the bytecodes by interpreting the dex file. The Dalvik virtual machine is based on a register architecture, data access is achieved through indirect or direct transfer of registers, the access mode is much faster than that of a stack-based mode, and the volume of a Dalvik executable file is smaller. The Dalvik virtual machine is a virtual machine of an android program and is the operation basis of a Java program in the android. The instruction set is based on a register architecture and executes a dex byte code with a specific file format to finish important functions of object life cycle management, stack management, thread management, security exception management, garbage collection and the like. The core content of the system is an implementation library which is generally implemented by C language. Depending on a part of functional thread mechanism and memory management mechanism of the Linux kernel, the memory can be used efficiently, and the high performance is expressed on a low-speed CPU. Each android application corresponds to an independent Dalvik virtual machine instance at the bottom layer, and the code of the android application is executed under the interpretation of the virtual machine. Specifically, the distributed link trace information includes trace information; trace is a computer term and trace and Ttrack are HTTP ways to debug web server connections.
Step S820, obtaining hotspot information based on the distributed link tracking information.
Specifically, JIT has two code compilation modes: a Method mode and a trace mode. Compiling is performed in units of functions and trace, respectively. In a trace manner, the code of a function is divided into a plurality of execution paths, and the execution paths are divided into a hot path and a cold path according to the execution frequency. the trace mode can quickly acquire a hot path, and compile codes in shorter time and less memory. And the hot path is the hot spot information. The hotspot information comprises characteristic data of the application program.
Step S830, obtaining feature data of the application program based on the hotspot information.
Specifically, the method domain of the application is obtained, and the corresponding application is identified according to the obtained related information. By the method, the specific application scene information of the prefabricated third-party application and the specific application scene information of the third-party application can be obtained, and the preset power consumption strategy rule is matched according to the application scene information.
As shown in fig. 9, the exemplary scene recognition and power consumption policy planning system based on the vehicle machine includes:
the analysis module 910 analyzes an application program running on the car machine, and obtains feature data of the application program.
The obtaining module 920 obtains corresponding application scenario information based on the feature data of the application program.
The executing module 930 selects a corresponding power consumption policy for the application context information based on a preset power consumption policy rule, and executes the corresponding power consumption policy.
In an embodiment of the application, the analyzing module 910 analyzes an application running on a vehicle, and acquiring feature data of the application includes:
acquiring a feature file of an application program based on the electronic exchanger;
and acquiring the characteristic data of the application program based on the characteristic file of the application program.
In an embodiment of the application, the obtaining the feature data of the application based on the feature file of the application includes:
acquiring method domain information of the application based on the characteristic file of the application program;
acquiring method set information based on the method domain information;
and acquiring characteristic data of the application program based on the method domain information and the method set information.
In an embodiment of the application, the analyzing module 910 analyzes an application running on a vehicle, and acquiring feature data of the application includes:
acquiring distributed link tracking information based on a preset virtual machine;
acquiring hotspot information based on the distributed link tracking information;
and acquiring characteristic data of the application program based on the hotspot information.
In an embodiment of the present application, the power consumption policy rule includes: when the application scene information is game scene information, the corresponding power consumption strategy is to improve the refresh rate of the LCD and reduce the working frequency of the GPU; when the application scene information is video scene information, the corresponding power consumption strategy is to improve the refresh rate of the LCD and reduce the working frequency of the GPU; when the application scene information is WeChat scene information, the corresponding power consumption strategy is to reduce the GPU working frequency; when the application scene information is short message scene information, the corresponding power consumption strategy is to reduce the GPU working frequency and reduce the CPU working frequency; when the application scene information is the call scene information, the corresponding power consumption strategy is to reduce the refresh rate of an LCD and reduce the working frequency of a GPU; when the application scene information is payment scene information, the corresponding power consumption strategy is to improve the LCD refresh rate and reduce the GPU working frequency.
In an embodiment of the present application, the preset power consumption policy rule includes:
and presetting corresponding LCD refresh rate, GPU working frequency and CPU working frequency according to the application scene information.
In the exemplary car-based scene recognition and power consumption strategy planning device, the remaining time of the navigation object reaching the navigation end point from the real-time position is obtained according to the distance difference between the real-time position and the end position of the road section where the real-time position is located, so that accurate road condition information is difficult to obtain from the navigation server under the condition of weak network or no network, the real-time remaining time can be simulated to refresh the road condition information at a minute level through the embodiment, and the road condition information displayed in the navigation interface is also more accurate.
It should be noted that the scene identification and power consumption policy planning system based on the vehicle machine and the scene identification and power consumption policy planning method based on the vehicle machine provided by the foregoing embodiments belong to the same concept, and specific ways of executing operations by each module and unit have been described in detail in the method embodiments, and are not described herein again. In practical applications, the scene recognition and power consumption policy planning apparatus based on the vehicle device provided in the above embodiment may distribute the functions through different function modules as needed, that is, divide an internal structure of the apparatus into different function modules to complete all or part of the functions described above, which is not limited herein.
An embodiment of the present application further provides an electronic device, including: one or more processors; the storage device is configured to store one or more programs, and when the one or more programs are executed by the one or more processors, the electronic device is enabled to implement the scene identification and power consumption policy planning method based on the car machine provided in each of the above embodiments.
FIG. 10 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application. It should be noted that the computer system 1000 of the electronic device shown in fig. 10 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 10, the computer system 1000 includes a Central Processing Unit (CPU) 1001 that can perform various appropriate actions and processes, such as performing the methods described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 1002 or a program loaded from a storage portion 1008 into a Random Access Memory (RAM) 1003. In the RAM 1003, various programs and data necessary for system operation are also stored. The CPU 1001, ROM 1002, and RAM 1003 are connected to each other via a bus 1004. An Input/Output (I/O) interface 1005 is also connected to the bus 1004.
The following components are connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage portion 1008 including a hard disk and the like; and a communication section 1009 including a Network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The driver 1010 is also connected to the I/O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1010 as necessary, so that a computer program read out therefrom is mounted into the storage section 1008 as necessary.
In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication part 1009 and/or installed from the removable medium 1011. When the computer program is executed by a Central Processing Unit (CPU) 1001, various functions defined in the system of the present application are executed.
It should be noted that the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may comprise a propagated data signal with a computer-readable computer program embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware, and the described units may also be disposed in a processor. Wherein the names of the elements do not in some way constitute a limitation on the elements themselves.
Another aspect of the present application also provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor of a computer, causes the computer to execute the scene recognition and power consumption policy planning method based on a vehicle machine. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist separately without being incorporated in the electronic device.
Another aspect of the application also provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instruction from the computer-readable storage medium, and executes the computer instruction, so that the computer device executes the scene identification and power consumption policy planning method based on the vehicle machine provided in the above embodiments.
The above-described embodiments are merely illustrative of the principles and utilities of the present application and are not intended to limit the application. Any person skilled in the art can modify or change the above-described embodiments without departing from the spirit and scope of the present application. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical concepts disclosed in the present application shall be covered by the claims of the present application.
Claims (10)
1. A scene identification and power consumption strategy planning method based on a vehicle machine is characterized by comprising the following steps:
analyzing an application program running on a vehicle machine, and acquiring characteristic data of the application program;
acquiring corresponding application scene information based on the characteristic data of the application program;
and selecting a corresponding power consumption strategy aiming at the application scene information based on a preset power consumption strategy rule, and executing the corresponding power consumption strategy.
2. The vehicle-mounted device-based scene recognition and power consumption strategy planning method according to claim 1, wherein the analyzing an application program running on a vehicle-mounted device, and the obtaining feature data of the application program comprises:
acquiring a feature file of an application program based on the electronic exchanger;
and acquiring the characteristic data of the application program based on the characteristic file of the application program.
3. The vehicle-mounted machine-based scene recognition and power consumption strategy planning method according to claim 2, wherein the obtaining of the feature data of the application program based on the feature file of the application program comprises:
acquiring method domain information of the application based on the characteristic file of the application program;
acquiring method set information based on the method domain information;
and acquiring characteristic data of the application program based on the method domain information and the method set information.
4. The vehicle-mounted device-based scene recognition and power consumption strategy planning method according to claim 1, wherein the analyzing an application program running on a vehicle-mounted device, and the obtaining feature data of the application program comprises:
acquiring distributed link tracking information based on a preset virtual machine;
acquiring hotspot information based on the distributed link tracking information;
and acquiring characteristic data of the application program based on the hotspot information.
5. The vehicle-mounted machine-based scene identification and power consumption strategy planning method according to claim 1, wherein the power consumption strategy rules comprise: when the application scene information is game scene information, the corresponding power consumption strategy is to improve the refresh rate of the LCD and reduce the working frequency of the GPU; when the application scene information is video scene information, the corresponding power consumption strategy is to improve the refresh rate of the LCD and reduce the working frequency of the GPU; when the application scene information is WeChat scene information, the corresponding power consumption strategy is to reduce the GPU working frequency; when the application scene information is short message scene information, the corresponding power consumption strategy is to reduce the GPU working frequency and reduce the CPU working frequency; when the application scene information is the call scene information, the corresponding power consumption strategy is to reduce the refresh rate of an LCD and reduce the working frequency of a GPU; when the application scene information is payment scene information, the corresponding power consumption strategy is to improve the LCD refresh rate and reduce the GPU working frequency.
6. The vehicle-mounted machine-based scene identification and power consumption strategy planning method according to claim 1, wherein the preset power consumption strategy rule comprises:
and presetting corresponding LCD refresh rate, GPU working frequency and CPU working frequency according to the application scene information.
7. The utility model provides a scene discernment and power consumption strategy planning system based on car machine which characterized in that, the system includes:
the analysis module is used for analyzing the application program running on the vehicle machine and acquiring the characteristic data of the application program;
the acquisition module acquires corresponding application scene information based on the characteristic data of the application program;
and the execution module selects a corresponding power consumption strategy aiming at the application scene information based on a preset power consumption strategy rule and executes the corresponding power consumption strategy.
8. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs which, when executed by the one or more processors, cause the electronic device to carry out the method of any one of claims 1 to 6.
9. A computer-readable storage medium having stored thereon computer-readable instructions which, when executed by a processor of a computer, cause the computer to perform the method of any one of claims 1 to 6.
10. A computer program product or computer program, characterized in that the computer program product or computer program comprises computer instructions, the computer instructions being stored in a computer-readable storage medium, which computer instructions are read by a processor of a computer from the computer-readable storage medium, which computer instructions are executed by the processor, causing the computer to carry out the method of any one of claims 1 to 6.
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| CN103984538A (en) * | 2014-03-27 | 2014-08-13 | 华为技术有限公司 | Application scenario identification method, power consumption management method, devices and terminal equipment |
| CN107577533A (en) * | 2017-08-31 | 2018-01-12 | 广东欧珀移动通信有限公司 | Resource allocation method and Related product |
| CN114443256A (en) * | 2022-04-07 | 2022-05-06 | 荣耀终端有限公司 | Resource scheduling method and electronic equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103984538A (en) * | 2014-03-27 | 2014-08-13 | 华为技术有限公司 | Application scenario identification method, power consumption management method, devices and terminal equipment |
| CN107577533A (en) * | 2017-08-31 | 2018-01-12 | 广东欧珀移动通信有限公司 | Resource allocation method and Related product |
| CN114443256A (en) * | 2022-04-07 | 2022-05-06 | 荣耀终端有限公司 | Resource scheduling method and electronic equipment |
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