CN109933186A - A kind of mobile web browser energy consumption optimization method adjusted based on screen intensity - Google Patents
A kind of mobile web browser energy consumption optimization method adjusted based on screen intensity Download PDFInfo
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- CN109933186A CN109933186A CN201910060210.2A CN201910060210A CN109933186A CN 109933186 A CN109933186 A CN 109933186A CN 201910060210 A CN201910060210 A CN 201910060210A CN 109933186 A CN109933186 A CN 109933186A
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
A kind of mobile web browser energy consumption optimization method adjusted based on screen intensity, 1) according to the interface of the open source projects Chromium of Webkit application, for acquiring data and implementing prioritization scheme, Web browser is tested as this experiment after compiling, 2) quantization is made to impression screen intensity factor, 3) the embedded background system interface in mobile terminal is realized, 4) it is modeled for all factors influential on Dynamic gene after handling collected different user data, realize SVM classifier, cross-training is carried out to classifier using the training data of storage in the database, Optimized model is finally embedded in mobile terminal, 5) screen intensity vision compensation scheme adjusted is designed, it is then displayed at after being handled according to the data in screen intensity Dynamic gene b and frame buffer display content On the screen of mobile terminal, the energy consumption under default screen brightness regulation mode and the energy consumption using optimization method are compared, largest optimization rate is up to 30%.
Description
Technical field
The invention belongs to field of mobile computing, and in particular to a kind of mobile web page browsing adjusted based on screen intensity
Device energy consumption optimization method.
Background technique
As science and technology continues to introduce new, Intelligent mobile equipment has had reached universal degree, at the same time, various shiftings
Moved end application urgently consumes the electricity of mobile terminal.Further investigation reveals that user more than 52% is daily using being based on
The Web browser of Webkit, in addition to this there are many more the applications based on Webki.It is measured through experiment, the power consumption of screen intensity
A part of highly significant is accounted in mobile phone use process, and existing technology is not directed to this portion based on large user group
The good solution for dividing application to reduce mobile terminal energy consumption by adjusting screen intensity.
Summary of the invention
In order to overcome the above-mentioned deficiencies of the prior art, the object of the present invention is to provide a kind of shiftings adjusted based on screen intensity
Dynamic web browser energy consumption optimization method, the optimization method on the basis of screen intensity that system is adjusted according to intensity of illumination,
Screen intensity is suitably reduced in conjunction with user experience, to achieve the purpose that energy optimization.Consider different web pages content to user experience
Influence with svm classifier method establish a universal model for different user, by acquiring different user, different moments, no
With the system under browsing content according to the screen intensity of light intensity regulating, screen content and corresponding user's acceptable screen
Brightness train classification models.When user is using application-browsing content based on Webkit, analyze in advance after Webkit rendering
In frame buffer will content complexity in next content frame that screen is shown and the current screen brightness that is determined by intensity of illumination,
According to trained embedded model dynamic adjustment screen intensity, while brightness benefit is carried out to the content in GPUBuffer caching
It is shown again after repaying, guarantees lower screen intensity energy consumption while visual demand when meeting user's browsing, from software and hardware
Rank reduces mobile Web application energy consumption.
To achieve the goals above, the technical solution adopted by the present invention is that:
A kind of mobile web browser energy consumption optimization method adjusted based on screen intensity, comprising the following steps:
1) according to the interface of the open source projects Chromium based on Webkit application of Google, function includes to read
Frame buffer data in GPUBuffer modifies frame buffer content according to the brightness regulation factor, for acquiring data and implementing optimization
Scheme tests Web browser as this experiment after compiling；
The open source projects Chromium be based on Webkit kernel, support hardware-accelerated rendering, have browser and from
Frame buffer content function is read in GPUBuffer, and the function of write-in GPUBuffer passes through in data acquisition
Chromium for GPU hardware accelerate rendering building openGL context, read GPUBuffer in content, the content with
The rgb space of each pixel of screen is deposited,.It, equally will be by the pixel of luminance compensation when using Optimizing Mode
GPUBuffer is written by rgb space in value；
2) experimental verification screen intensity, which changes the principal element for influencing user experience, browsing content and environment illumination intensity,
And environment illumination intensity directly affects the underlying screen brightness of system adjusting, and makes quantization to these factors；
The principal element of the influence screen adjustment selects and quantization, and the underlying screen that light intensity determines that system is adjusted is bright
The screen intensity that the screen intensity and system that degree suitably reduces screen intensity again on this basis, therefore adjusts are adjusted is presented
Positively related relationship, screen intensity are indicated in cell phone with screen intensity grade point, are chosen Android phone and are carried out in fact
It tests, it is bright to calculate screen to application grade point between 1-15 by screen intensity grade point level in Android Galaxy S4
Spend factor b, b=level/15；
On the one hand, content complexity influences user experience to influence the adjusting of screen intensity to browsing content, and content is got over
Complexity, demand of the user to screen intensity are higher.Here, with the entropy of pixel gray value come description content complexity；Another party
Face, browsing content also influences light and compensates later reducing power, therefore influences the adjustable lower limit of screen intensity.It unites by experiment
Meter if there is the brightness value of pixel for being more than 12% can not be reduced, then will affect after screen content is compensated by light
The usage experience of user, therefore, threshold value of the setting 12% as screen light compensation adjustment, when pixel ratio is more than threshold value,
The screen intensity regulatory factor obtained according to the proportional linearity up-regulation classifier exceeded
Realize the embedded background system interface in mobile terminal, when function includes: automatic collection model training data and uses
Model prediction data, and screen intensity is adjusted to implement prioritization scheme；
Background system interface described in step 3), model when function includes: automatic collection model training data and uses
Prediction data, and screen intensity is adjusted to implement prioritization scheme.When user is browsed using the application based on Webkit, after
For platform system by automatic collection model training data, data include: different user, different moments, the system held in different viewing
Screen intensity, screen browsing content and corresponding user's acceptable screen intensity regulatory factor；
When optimizing application model is browsed, background system will be acquired user data when using every 5s, number
According to including: the user, at current time, the current system screen intensity factor, the browsing content being currently stored in GPU caching makees
It is characterized value input Optimized model；
It is modeled for all factors influential on Dynamic gene and collected different user data is handled
Afterwards, according to the characteristic Design of data sample and SVM classifier is realized, using the training data of storage in the database to classifier
Cross-training is carried out, Optimized model is finally embedded in mobile terminal；
Step 4) is using the collected training data of step 3 as the input value of SVM Optimized model, to establish a Universal Die
Type, we are used as training data after calculating average value to the data of different user, carry out after the parameter using python setting SVM
According to the ratio cross-training of 5:1 and classifier is generated using data set
Screen intensity vision compensation scheme adjusted is designed, according in screen intensity Dynamic gene b and frame buffer
Data are then displayed on the screen of mobile terminal after handling display content；
Vision compensation scheme described in step 5).Data in frame buffer are relatively original after prioritization scheme brightness adjustment
System call interception value can become darker in brightness, in order to make up this species diversity to meet user experience, therefore using will be former
RGB image is converted into YUV image, is then compensated according to formula Yl=b*min (Y/b, 255) ≈ Y to luminance y value.
The beneficial effects of the present invention are:
In use, screen power consumption is a very significant part to mobile terminal, while clear using movement
During device of looking at browses webpage, user is different the screen intensity acceptance level of different viewing content, but now
System screen brightness regulation mechanism only consider light intensity, be not bound with user experience to adjust screen intensity, cause energy
Measure the waste of resource.In view of the above-mentioned problems, design optimization method, guarantee while visual demand when meeting user's browsing lower
Screen intensity energy consumption, from software and hardware rank reduce mobile Web application energy consumption.The classifier accuracy rate that training generates is up to
98%.
After tested, for user using 2 kinds of different mobile phones under varying environment illumination, and when browsing different content, comparison is silent
Recognize the energy consumption under screen intensity shaping modes and the energy consumption using optimization method, optimization all has certain optimization ability, maximum energy
Consumption optimization rate is up to 30%.
Detailed description of the invention
Fig. 1 is the work flow diagram of the method for the present invention.
Specific embodiment
The present invention is further discussed below below in conjunction with attached drawing, but the present invention is not limited to following embodiment.
A kind of mobile web browser energy consumption optimization method adjusted based on screen intensity, comprising the following steps:
1) according to the interface of the open source projects Chromium based on Webkit application of Google, function includes to read
Frame buffer data in GPUBuffer modifies frame buffer content according to the brightness regulation factor, for acquiring data and implementing optimization
Scheme tests Web browser as this experiment after compiling；
The open source projects Chromium be based on Webkit kernel, support hardware-accelerated rendering, have browser and from
Frame buffer content function is read in GPUBuffer, and the function of write-in GPUBuffer passes through in data acquisition
Chromium for GPU hardware accelerate rendering building openGL context, read GPUBuffer in content, the content with
The rgb space of each pixel of screen is deposited,.It, equally will be by the pixel of luminance compensation when using Optimizing Mode
GPUBuffer is written by rgb space in value；
2) experimental verification screen intensity, which changes the principal element for influencing user experience, browsing content and environment illumination intensity,
And environment illumination intensity directly affects the underlying screen brightness of system adjusting, and makes quantization to these factors；
The principal element of the influence screen adjustment selects and quantization, and the underlying screen that light intensity determines that system is adjusted is bright
The screen intensity that the screen intensity and system that degree suitably reduces screen intensity again on this basis, therefore adjusts are adjusted is presented
Positively related relationship, screen intensity are indicated in cell phone with screen intensity grade point；
Browsing content content complexity influences user experience to influence the adjusting of screen intensity, and content is more complicated, user
Demand to screen intensity is higher, therefore, with the entropy of pixel gray value come description content complexity；Browsing content also influences light
Later reducing power is compensated, therefore influences the adjustable lower limit of screen intensity, after screen content is compensated by light, if
The brightness value for having more than 12% pixel can not be reduced, then will affect the usage experience of user, therefore, 12% conduct be arranged
The threshold value of screen light compensation adjustment is obtained when pixel ratio is more than threshold value according to the proportional linearity up-regulation classifier exceeded
Screen intensity regulatory factor；
3) the embedded background system interface in mobile terminal is realized, background system interface function includes: automatic collection model training
Model prediction data when data and use, and screen intensity is adjusted to implement prioritization scheme；User, which uses, is based on Webkit
Application when being browsed, background system is by automatic collection model training data, model training data: different user, when different
It carves, the system screen brightness held in different viewing, screen browsing content and corresponding user's acceptable screen intensity
Regulatory factor；When optimizing application model is browsed, background system will be acquired user data when using every 5s, be adopted
The data of collection include: the user, and at current time, the current system screen intensity factor is currently stored in the browsing in GPU caching
Hold, inputs Optimized model as characteristic value；
4) it is modeled for all factors influential on regulatory factor at collected different user data
After reason, according to the characteristic Design of data sample and SVM classifier is realized, using the training data of storage in the database to classification
Device carries out cross-training, and Optimized model is finally embedded in mobile terminal；Input of the collected training data as SVM Optimized model
Value is used as training data after calculating average value to the data of different user, is arranged using python to establish a universal model
It carries out utilizing data set according to the ratio cross-training of 5:1 after the parameter of SVM and generates classifier；
5) screen intensity vision compensation scheme adjusted is designed, according in screen intensity Dynamic gene b and frame buffer
Data to display content handle after be then displayed on the screen of mobile terminal；The vision compensation scheme, in frame buffer
Data relatively original system call interception value after prioritization scheme brightness adjustment can become darker in brightness, using by former RGB
Image is converted into YUV image, is then compensated according to formula Yl=b*min (Y/b, 255) ≈ Y to luminance y value.
Embodiment.
1) 20 volunteers are invited to browse webpage using the browser of exploitation, by calling back office interface to acquire user's training
Data, in different moments, when being held in user's browsing different viewing, first in record system screen brightness and current screen browsing
Hold, while reducing screen intensity and corresponding progress light compensation on this basis, records user's acceptable screen intensity and adjust
The factor.In this, as a complete training data.Data when for 20 user's browsings more than 500 webpages, and to not
Data with user calculate average value.
2) it obtains being more than 5000 data cross-training SVM classifiers after basis is processed, and is embedded in mobile terminal.
3) in use, background system collects a user data every 5s from browser and system, inputs mould
Type obtains model and is output to screen intensity regulatory factor b.
4) luminance compensation is done according to the content that current frame buffer of the b to collection is shown, while is calculated over light compensation
The pixel ratio of range, threshold value if more than just do a linear calculating to the part for being more than, and adjust screen intensity tune
Factor b is saved, finally gradually adjustment brightness is bright to being calculated by b again after frame buffer is written in the content that light compensates
Angle value.
Claims (1)
1. a kind of mobile web browser energy consumption optimization method adjusted based on screen intensity, which is characterized in that including following step
It is rapid:
1) according to the interface of the open source projects Chromium based on Webkit application of Google, function includes to read GPUBuffer
In frame buffer data, according to the brightness regulation factor modify frame buffer content, for acquire data and implement prioritization scheme, compiling
Web browser is tested as this experiment afterwards；
The open source projects Chromium be based on Webkit kernel, support hardware-accelerated rendering, have browser and from
Frame buffer content function is read in GPUBuffer, and the function of write-in GPUBuffer passes through in data acquisition
Chromium for GPU hardware accelerate rendering building openGL context, read GPUBuffer in content, the content with
The rgb space of each pixel of screen is deposited.It, equally will be by the value of the pixel of luminance compensation when using Optimizing Mode
GPUBuffer is written by rgb space；
2) experimental verification screen intensity, which changes the principal element for influencing user experience, a browsing content and environment illumination intensity, and ring
Border intensity of illumination directly affects the underlying screen brightness of system adjusting, and makes quantization to these factors；
The principal element of the influence screen adjustment selects and quantization, and light intensity determines the underlying screen brightness that system is adjusted,
Positive is presented in the screen intensity that the screen intensity and system for suitably reducing screen intensity again on this basis, therefore adjusting are adjusted
The relationship of pass, screen intensity are indicated in cell phone with screen intensity grade point；
Browsing content content complexity influences user experience to influence the adjusting of screen intensity, and content is more complicated, and user is to screen
The demand of curtain brightness is higher, therefore, with the entropy of pixel gray value come description content complexity；Browsing content also influences light compensation
Later reducing power, therefore the adjustable lower limit of screen intensity is influenced, after screen content is compensated by light, if there is super
The brightness value for crossing 12% pixel can not be reduced, then will affect the usage experience of user, and therefore, setting 12% is used as screen
The threshold value of light compensation adjustment raises the screen that classifier obtains according to the proportional linearity exceeded when pixel ratio is more than threshold value
The curtain brightness regulation factor；
3) the embedded background system interface in mobile terminal is realized, background system interface function includes: automatic collection model training data
With model prediction data when using, and adjust screen intensity to implement prioritization scheme；User uses answering based on Webkit
When with being browsed, background system is by automatic collection model training data, model training data: different user, different moments, no
With the system screen brightness under browsing content, screen browsing content and corresponding user's acceptable screen intensity adjust because
Son；When optimizing application model is browsed, background system will be acquired user data when using every 5s, the number of acquisition
According to including: the user, at current time, the current system screen intensity factor, the browsing content being currently stored in GPU caching makees
It is characterized value input Optimized model；
4) it is modeled for all factors influential on regulatory factor after handling collected different user data,
According to the characteristic Design of data sample and realize SVM classifier, using storage training data in the database to classifier into
Row cross-training, is finally embedded in mobile terminal for Optimized model；Input value of the collected training data as SVM Optimized model,
To establish a universal model, it is used as training data after calculating average value to the data of different user, SVM is set using python
Parameter after carry out using data set according to 5:1 ratio cross-training and generate classifier；
5) screen intensity vision compensation scheme adjusted is designed, according to the number in screen intensity Dynamic gene b and frame buffer
According to display content handle after be then displayed on the screen of mobile terminal；The vision compensation scheme, the data in frame buffer
Relatively original system call interception value can become darker in brightness after prioritization scheme brightness adjustment, using by former RGB image
It is converted into YUV image, then luminance y value is compensated according to formula Yl=b*min (Y/b, 255) ≈ Y.
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