CN109615684A - A kind of method that decentralization renders online - Google Patents
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- CN109615684A CN109615684A CN201811514731.2A CN201811514731A CN109615684A CN 109615684 A CN109615684 A CN 109615684A CN 201811514731 A CN201811514731 A CN 201811514731A CN 109615684 A CN109615684 A CN 109615684A
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- 238000000034 method Methods 0.000 title claims abstract description 32
- 238000009877 rendering Methods 0.000 claims abstract description 102
- 239000000463 material Substances 0.000 claims abstract description 17
- 230000006399 behavior Effects 0.000 claims abstract description 15
- 230000007246 mechanism Effects 0.000 claims abstract description 5
- 238000013475 authorization Methods 0.000 claims abstract description 3
- 239000006185 dispersion Substances 0.000 claims description 10
- 238000003860 storage Methods 0.000 claims description 8
- 238000004458 analytical method Methods 0.000 claims description 5
- 238000009826 distribution Methods 0.000 claims description 5
- 238000005457 optimization Methods 0.000 claims description 4
- 238000013135 deep learning Methods 0.000 claims description 2
- 238000011156 evaluation Methods 0.000 claims description 2
- 230000003993 interaction Effects 0.000 claims 1
- 230000002045 lasting effect Effects 0.000 claims 1
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- 206010033799 Paralysis Diseases 0.000 description 2
- 230000003542 behavioural effect Effects 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000012790 confirmation Methods 0.000 description 2
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- 238000013527 convolutional neural network Methods 0.000 description 1
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Abstract
The present invention provides a kind of online rendering method of decentralization, provided method supports the rendering material quality data of decentralization, user can be used it is individual character, distributed, dynamically render material quality data；The point-to-point intelligent rendering system configuration of terminal user's energy real-time implementation, because system by feature extractions such as history, habit, style that user renders and can establish personal behavior model by the method for machine learning, the model profile is stored in user terminal, and the automated setting of rendering parameter is participated in, to provide basis for rendering automation；For this method when user's using terminal renders, it is directly to be manipulated according to rendering configurations by system that access database, which is not needed through central server,；To protect each terminal user safety, process provides corresponding decentralization security mechanisms, there is the authorization and control of different permissions, protect the personalized material and behavior model of user.
Description
Technical field
The invention belongs to information technology fields, are related to a kind of online rendering method, specifically relate to a kind of decentralization
The method rendered online.
Background technique
Online rendering, especially online real-time rendering are already to become a kind of rendering mode of prevalence at this stage, however currently
The material quality data library rendered online is all based on centralization, what material database has, what enough material of user's ability is
A kind of enclosed, centered on data center online rendering.Once central server, which is captured whole system, to paralyse,
Various data will also be revealed, while also very big to the concurrent pressure of central database.As mobile subscriber is to online real-time
The raising of the quality requirements of rendering, material resource used are often personalized, dispersion, open, it is impossible to all be deposited
Storage is in a central database.It, can be according to the individual needs of each user, flexible configuration rendering using decentralization technology
Material resource, thus will need to rendering resources decentralization.
When being rendered using centralized architecture formula, the user of different role, which needs adequately link up with center, to be handed over
Stream, and central server can generate some misunderstandings when passing on the exchange content between user, need to make directly to carry out between user
The exchange of intelligent precise and high efficiency.In order to realize personalized rendering service according to the different feature of each user, it is also desirable to clothes
The speciality of business both sides is precisely matched.Behavior modeling can be carried out to respective feature distribution formula by machine learning, carried out
When practical rendering service, system can be according to personal behavior model, and the procedure parameter configuration of adaptive completion rendering reduces rendering
The communication complexity of service.
Entire resource all uses distributed storage mode, keeps the rights and duties of whole network node identical, thus not
Central server is needed to handle node.Each terminal follows unified rule, which is based on cryptographic algorithm rather than believes
With certificate, and when data update, needs to obtain the approval of each terminal, carries out and is collected to its knowledge, enriches and is complete
It is kind, realize that hyperlink gives user after resource is matched with user.
Online rendering security risk under decentralization mode: as the system of a not no central server, each end
End subscriber, there is also being captured, when some terminal is captured, renders actually with regard to nothing as central server
Method completes, and using the security mechanism of decentralization, can not only protect rendering service system, can also protect the material of user individual
Prime number is accordingly and personal behavior model.Once some terminal is captured, adjacent terminal will stop having been captured all of terminal
Permission, the data storage method of each lane terminal is the encrypted fragment store mode used, even if obtaining lane database
Content also can not decrypt and piece together, the safety of whole system for the system of centralization compared with being greatly improved.
Summary of the invention
The technical problems to be solved by the present invention are: being all to disperse for resource used in above-mentioned user, in one
Heart database is unable to satisfy needed for user, by the mode that centralization renders online be converted into the mode that decentralization renders online Lai
Break the intrinsic mode centered on resource, for personalized rendering needed for different users, is realized, supports rendering emphatically
The distributed of material provides, by intelligent means come the rendering content increment to user and the control of progress.In the present invention
When for terminal user's rendering, the individual cultivation of user's rendering is supported, realization process is by machine learning to user's mistake
Deep learning is carried out toward rendering work data, extracts the behavior model that reflection user renders behavioural characteristic, and on this basis,
Required rendering parameter is initiatively adjusted in time for progress for the purpose of the demand of user.
To achieve the goals above, technical proposal that the invention solves the above-mentioned problems is that a kind of decentralization renders online
Method, each associated terminal all be interconnect, do not need central server authorization when accessing relevant materials data, be by
The transmission that new communication port realizes data is established between terminal.
It is no centralization device in method provided by the present invention, is by directly carrying out data between each terminal
Transmission.Ensure the problem of data safety of whole system using decentralization simultaneously,
In the present invention, there are different permission grant and control between each terminal, each terminal can directly authorize adjacent end
The permission at end is either awarded, thus each terminal is a center, and center truly has been not present.
In the present invention, user using terminal render when, due to user rendering content be dispersion, non-boundary,
Terminal can be to the operation that user follows the steps below:
S01: the features such as the rendering habit, content, style of different user are learnt；Depth can be carried out to the passing rendering of user
Study, the data such as history, content, habit, style and rendering configurations for rendering to it are iterated study with convolutional neural networks,
Form the personal behavior model being made of four maturity, stability, liveness and openness core dimensions；
S02: extraction, the fusion, analysis carried out to rendering configurations data, each dimension specifically include four different main spies
Sign, maturity include four experience, prestige, contribution and evaluation main features；Stability include with colour cast it is good, with light preference, adjust
Whole preference and efficiency preference, liveness include rendering frequency, interval variation trend, repetitive rate and rendering quantitative change rate, openness
Dispersion is used comprising characteristic style of works dispersion, works field dispersion, rendering parameter dispersion and material；
S03: rendering behavior map, the rendering historical custom of user, and the rendering of generation system accordingly are formed for features described above
Parameter configuration is generated the basic parameter of rendering by stability, and being decided whether by maturity and liveness need to be to rendering classification parameter
It adjusts；The adjustment magnitude of rendering parameter is determined by liveness；
S04: rendering platform is configured according to above-mentioned rendering parameter, complete rendering operation, and for initial user, system is to count
Based on average configuration parameter, three states (upper inclined, constant, lower inclined) is respectively taken by four dimensions, generates 12 kinds of allocation plans,
Sample rendering is carried out, user is issued and carries out hobby selection, based on the selection of user, then respectively take three states by four dimensions
(upper partially inclined, constant, lower) generates 12 kinds of allocation plans, carries out sample rendering, and user selects again, in triplicate after, automatically
The first rendering behavior model of formation user and first rendering configurations；
S05: evaluating rendering result quality and increment material dosage, and adjusts user and render behavior model；
S06: resource is automatically performed using model and rendering parameter configures, and real-time rendering is carried out to it, is presented to the user.
In the present invention, the rendering process includes the following steps:
S11: system recalls the initial model of user, forms initial configuration；
S12: system receives the file that user needs to render, and prepares to render according to initial configuration；
S13: real-time rendering is carried out；
S14: rendering result is submitted into user；
S15: system acquires the satisfaction of user by sample；
S16: system analyzes user satisfaction state, judges the attitude that user sets rendering parameter, and in this, as
Behavioral data is rendered to user, by study, behavior model is rendered to user and carries out continuing iterative evolution；
S17: user is dissatisfied to rendering result, and system can inquire the deviation between user's rendering result and ownership goal result,
Then system can adjust corresponding parameter, can be unsatisfied with after place modifies to initial model according to it and form configuration again, and
S12 to S16 step is repeated, the optimization of model, iteration again is carried out, until user is satisfied；
S18: user feels satisfied, and rendering is completed, and system is equivalent to carry out an iteration, and confirmation has learnt the accuracy of model.
In the present invention, the point-to-point direct transmission between each port is realized by decentralization.
The method that a kind of decentralization of the invention renders online, have the special feature that is with beneficial effect:
It 1, is all dispersion for resource needed for user in the present invention, a central database is unable to satisfy needed for user, by
The mode that centralization renders online is converted into the mode that decentralization renders online to break intrinsic resource center to meet use
Needed for family, and it is directed to different users, realizes personalized rendering mode, by the means of intelligence come the rendering content to user
The control of increment and progress.When user's using terminal renders, which will be carried out with the content needed for active user
Data analysis is intelligent to form a data model, then realizes rendering in real time to this user；
2, when system is rendered in the present invention, the user model that direct selecting system has succeeded in school forms initial configuration, root
It is rendered in real time according to file needed for user, its result is submitted into user later, by the information of user feedback by user's mould
Type optimizes；
3, adjacent terminal will be seen that and sound an alarm when some terminal is captured paralysis in the present invention, due between each terminal
It is all intercommunication, the higher terminal of permission stops all permissions for the terminal captured, is equivalent to this end captured
End will be deactivated, thus whole system will be very safe；
4, the storing mode of the storage file (including user's rending model and personalized material) of each terminal in the present invention is
Encrypted fragment mode stores, and when system uses model, can spell from the data of each distributed storage and verify and gather out
Required model.May insure can not also to decrypt when even if some terminal is captured, is acquired to the data of the terminal in this way with
And piece together out content in database.
Detailed description of the invention
Fig. 1 is present system learning process figure.
Fig. 2 is present invention rendering flow chart.
Fig. 3 is the acquisition figure of user model of the present invention.
Specific embodiment
The contents of the present invention are further detailed with reference to the accompanying drawing.
The process that the systematic learning in the present invention is expressed in Fig. 1, since user is in the content that using terminal renders
It is dispersion, non-boundary:
S01；Terminal learns the features such as the rendering habit, content, style of different user, forms a data set；
S02: extraction, fusion, the analysis of rendering data collection are carried out；
S03: collecting for feature, be abundant and perfect, forms behavior map, the rendering history of user；
S04: modeling analysis and optimization are carried out to user using platform；
S05: the increment of rendering content is provided to user based on the analysis results and control is carried out to its progress；
S06；Resource distribution is carried out using model, and real-time rendering is carried out to it, is presented to the user.
Rendering process of the invention is expressed in Fig. 2, user searches for the material for oneself thinking rendering by operating terminal
Matter content:
S11: system recalls the initial model of user, forms initial configuration；
S12: system receives the file that user needs to render, and prepares to render according to initial configuration；
S13: real-time rendering is carried out；
S14: rendering result is submitted into user；
S15: the satisfaction of system acquisition user；
S16: system analyzes user satisfaction, judges whether user is satisfied with the result of rendering；
S17: user is dissatisfied to rendering result, and system can inquire the deviation between user's rendering result and ownership goal result,
Then system can adjust corresponding parameter, can be unsatisfied with after place modifies to initial model according to it and form configuration again, and
S12 to S16 step is repeated, the optimization of model, iteration again is carried out, until user is satisfied；
S18: user feels satisfied, and rendering is completed, and system is equivalent to carry out an iteration, and confirmation has learnt the accuracy of model.
In addition, this system while rendering, realizes the mechanism that rendering speed and resource consumption speed match: if wash with watercolours
It is identical as resource consumption speed to contaminate speed, system will realize synchronous rendering in real time；If rendering speed is greater than resource consumption
The part for having rendered completion can be submitted to user and carry out satisfaction presentation by speed, system；If the speed of rendering is less than resource
The speed of consumption, whole system, which will render waiting period, to be terminated.
Process when model needed for present system obtains user is expressed in Fig. 3:
S21: the model of all users in this system be all using distributed storage, system at random by these model cuttings and with
Machine is serialized and is stored in each database, and simultaneity factor also stores a part, prevents from distorting；
S22: when system needs to call user model, system can send a request to each database, by all of required model
Part extracts, and prepares the verifying of next step；
S23: system is verified using authentication mechanism, and the department pattern of the serializing in S21 step is first carried out unserializing,
Carry out confidence level Verification again, such as: A1 is verified, by the characteristic of A1 be sent to adjacent A2 and A3 carry out verifying and
Feedback, if A1 is verified by A2 and A3, can belong to the department pattern for the model of being obtained, and right to one A1 of system feedback
A1 carry out next step A4 and A5 verifying, and so on, when A1 be verified reach half when will by verifying, no person is not
It can pass through.Due to each part of module be it is interconnected, other each portions are equally applicable to the method for the verifying of A1
Sub-module；
S24: after being completed to the verifying of each part of module, the module that these modules are stored up with Installed System Memory is pieced together；
S25: after model pieces together completion, system can get required model；
S26: after model has used, system can store the random distribution of model again, be stored in prevent some module same
It is tampered when a place.
In addition to above-mentioned implementation method, the present invention can also have an other embodiments, it is all using same replacement either etc.
Effect transformation formed technical solution, belong to the present invention claims protection scope in.
Claims (6)
1. a kind of method that decentralization renders online, it is characterised in that: each terminal is interconnected, and each end
It does not need directly to be manipulated by central server by each terminal when the access database of end, there is different power between each terminal
The authorization and control of limit.
2. the method that a kind of decentralization according to claim 1 renders online, it is characterised in that: provided by the present invention
Method is no centralization device, and it is all using distributed storage that each rendering resources, which are all dispersions,.
3. the method that a kind of decentralization according to claim 2 renders online, it is characterised in that: user is in using terminal
When rendering, since the material of user's rendering can be dispersion, system can be to the operation that user follows the steps below:
S01:, rendering content passing to the rendering of different user and configuration parameter carry out deep learning, form habit, interior
The personal behavior model that the features such as appearance, style are constituted can enrich and improve user by lasting rendering operation and rendering history
Rendering behavior map, to keep the continuous evolution of corresponding model；
S02: the setting of rendering parameter can be carried out for user by above-mentioned model system；
S03: collecting for original user feature, is carried out using the process of sample interaction, forms original user behavior model；
S04: system is according to the evaluation to user's rendering result, the significant data of self modeling study；
S05: is provided by the increment of rendering material and to be also used as to rendering progress satisfaction by user based on the analysis results and is built
Mould learning data；
S06: resource distribution is carried out using model, and real-time rendering is carried out to it, is presented to the user.
4. the method that a kind of decentralization according to claim 2 renders online, it is characterised in that: rendering stream of the invention
Journey includes the following steps:
S11: system recalls the initial model of user, forms initial configuration；
S12: system receives the file that user needs to render, and prepares to render according to initial configuration；
S13: real-time rendering is carried out；
S14: rendering result is submitted into user；
S15: the satisfaction of system acquisition user；
S16: system analyzes user satisfaction, judges whether user is satisfied with the result of rendering；
S17: user is dissatisfied to rendering result, and system can inquire the deviation between user's rendering result and ownership goal result,
Then system can adjust corresponding parameter, can be unsatisfied with after place modifies to initial model according to it and form configuration again, and
S12 to S16 step is repeated, the optimization of model, iteration again is carried out, until user is satisfied；
S18: user feels satisfied, and rendering is completed, and is remembered to user model.
5. the method that a kind of decentralization according to claim 2 renders online, it is characterised in that: pass through decentralization system
System can realize that the intelligent rendering system of real-time point-to-point is configured to terminal user.
6. the method that a kind of decentralization according to claim 3 renders online, it is characterised in that: system is obtaining user
It needs to follow the steps below when required model:
S21: the model of each user is carried out distributed storage by system；
S22: call request can be sent when system wants calling model；
S23: system is verified using department pattern of the authentication mechanism to distributed storage；
S24: after all department patterns, which are verified, to be completed, system will piece together it；
S25: after piecing together completion, system gets the model of user；
S26: after model has been applicable in, system can store the random distribution of model again, be stored in together to prevent some module
One place is tampered.
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