CN106331750A - Self-adapting cloud game platform bandwidth optimization method based on regions of interest - Google Patents

Self-adapting cloud game platform bandwidth optimization method based on regions of interest Download PDF

Info

Publication number
CN106331750A
CN106331750A CN201610882001.2A CN201610882001A CN106331750A CN 106331750 A CN106331750 A CN 106331750A CN 201610882001 A CN201610882001 A CN 201610882001A CN 106331750 A CN106331750 A CN 106331750A
Authority
CN
China
Prior art keywords
user
game
interest
area
bandwidth
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201610882001.2A
Other languages
Chinese (zh)
Other versions
CN106331750B (en
Inventor
吴迪
柯毅豪
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
National Sun Yat Sen University
Original Assignee
National Sun Yat Sen University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by National Sun Yat Sen University filed Critical National Sun Yat Sen University
Priority to CN201610882001.2A priority Critical patent/CN106331750B/en
Publication of CN106331750A publication Critical patent/CN106331750A/en
Application granted granted Critical
Publication of CN106331750B publication Critical patent/CN106331750B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
    • H04N21/234—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
    • H04N21/2343—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/167—Position within a video image, e.g. region of interest [ROI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
    • H04N21/262—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists
    • H04N21/26208—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists the scheduling operation being performed under constraints
    • H04N21/26216—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists the scheduling operation being performed under constraints involving the channel capacity, e.g. network bandwidth
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/478—Supplemental services, e.g. displaying phone caller identification, shopping application
    • H04N21/4781—Games

Landscapes

  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Databases & Information Systems (AREA)
  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
  • Compression Or Coding Systems Of Tv Signals (AREA)
  • Information Transfer Between Computers (AREA)

Abstract

The invention discloses a self-adapting cloud game platform bandwidth optimization method based on regions of interest. The method comprises the steps that the operation cycle of a cloud game platform is cut into a plurality of time periods; at the beginning of each time period, a central control unit acquires bandwidth information of all game users; the central control unit solves a decision result on the basis of currently collected bandwidth information, wherein the decision result comprises the sizes of the regions of interest of all the game users; video coding is conducted on game pictures of all the game users on the basis of the acquired decision result. According to the method, the influences of different game types on the user experience quality are fully taken into account, and corresponding video coding parameter selection modes are proposed for the different game types; meanwhile, research results of biology, cognitive psychology and computer science on a human visual system are fully taken into account, and occupation of a cloud game to the bandwidth is reduced on the premise of influencing the user experience quality as little as possible by regulating the sizes of the regions of interest in the game pictures.

Description

A kind of cloud game platform adaptive bandwidth optimization method based on area-of-interest
Technical field
The present invention relates to cloud game and cloud computing resources management domain, relate to a kind of cloud based on area-of-interest Gaming platform adaptive bandwidth optimization method.
Background technology
In recent years, along with popularizing of broadband technology, the fast development of GPU vitualization technology and the high speed of game industry are sent out Exhibition, increasing manufacturer starts to promote cloud game technology.
Cloud game platform is the game mode based on cloud computing, and server end collects user's input of client, trip Play logic and game picture render and all run at server end, and the game picture after server will render is encoded to video flowing User is sent to afterwards by network.User need not the expensive processor of purchasing price and video card, it is not necessary to download capability is huge Game install file, it is only necessary to have good network to connect, and the video compression ability on basis can be played.Wander about Play technology can also allow user enjoy the game that in the past can only run on a pc platform on mobile terminals.
Cloud game platform architecture is mainly made up of game user and cloud game service provider.Cloud game service provider carries Selecting for user for several game, user selects different game according to hobby.User has difference to different type of plaies Image quality requirement, the most different type of plaies is the most different to the consumption of the network bandwidth.Along with being showing improvement or progress day by day of quality of play, The resolution of game improves day by day with the fine degree of game picture, thus the video size produced after causing game picture coding Also improve constantly.The game video size improved constantly causes the cost pressure of the network bandwidth not only to cloud game provider, Also improve the use threshold of cloud game user.Therefore the fewest affect image quality on the premise of reduce cloud game to bandwidth Take, it is possible to bring doulbe-sides' victory for cloud game provider and user.
According to the achievement in research of multiple subjects such as biology, cognitive psychology and computer science, human visual system (Human Visual System, HVS) is when complicated scene, it is possible to is primarily focused on rapidly minority and significantly regards To its priority treatment on feel object.Based on this thought, area-of-interest (Region of Interest, ROI) is suggested also Gradually develop.From image or video pictures, extract area-of-interest have multiple method, such as manual appointment, utilize peripheral hardware collection to use Family point of fixation, view-based access control model attention model extract, based on methods such as special object segmentations.
After the size and location determining area-of-interest, can join by arranging the correlative coding of video encoder Number, controls the video quality that area-of-interest is inside and outside, thus controls the size of game video.Selected by suitable method Determine the size of area-of-interest and the video quality that area-of-interest is inside and outside, it is possible to achieve game video quality and trip Balance between play video desire bandwidth.
In sum, from the angle of cloud game provider, in order to reduce bandwidth cost, ensure game user simultaneously Good game experiencing, cloud game platform needs the area-of-interest size designing a kind of method to select user so that cloud game Provider can save bandwidth cost on the premise of ensureing Consumer's Experience as far as possible.
" H.J.Hong, C.F.Hsu, T.H.Tsai, C.Y.Huang, K.T.Chen and C.H.Hsu, " Enabling Adaptive Cloud Gaming in an Open-Source Cloud Gaming Platform ", IEEE Transactions on Circuits and Systems for Video Technology, Volume.25, Issue.12, Page 2078-2091,2015. " measure the relation between gaming user experience quality and game video frame per second and code check, and Propose adjustment game video frame per second with code check to adjust the adaptive optimization method of cloud game video occupied bandwidth.In this technology Adjust frame rate of game and code check and belong to global parameter regulation, do not account in game picture important area and insignificant region to The Quality of experience at family affects different factors, and the impact on user experience quality is bigger.
" E.Cuervo, A.Wolman, L.P.Cox, K.Lebeck, A.Razeen, S.Saroiu and M.Musuvathi, " Kahawai:High-Quality Mobile Gaming Using GPU Offload ", in MobiSys, 2015. " propose cloud game service end and client all has complete games and data, by collaborative work The mode made generates the technology of game picture.Client running game also generates the picture of low image quality.Server end is separately operable Two game example generate low image quality and the picture of high image quality, and calculate the difference between two pictures, then by difference picture Coded transmission is to client.It is higher that the low image quality picture that this locality is generated by client merges generation with decoded difference picture The picture of image quality.Difference picture after this technology is encoded by transmission can reduce the bandwidth demand of cloud game.In the art, Have complete games and data owing to requiring client to be also required to, cause client to be also required to complete game journey is installed Sequence, the original intention existence saving user's end spaces with cloud game conflicts.Simultaneously as client is also required to running game program, this Client cross-platform cross terminal cannot be played, also improve the hsrdware requirements of client simultaneously.
" M.S.Hossain, G.Muhammad, B.Song, M.M.Hassan, A.Alelaiwai and A.Alamri, " Audio-Visual Emotion-Aware Cloud Gaming Framework ", IEEE Transactions on Circuits and Systems for Video Technology, Volume.25, Issue.12, Page 2105-2118, 2015. " propose a kind of based on audio user and video feed can the cloud game platform framework of perception user emotion.This technology By color component and the brightness and contrast of regulation game video picture, strengthen the Quality of experience of game user.This skill The parameter (color component, brightness and contrast) of art regulation is the most notable on the impact of the Quality of experience of user.This technology cannot Realize the optimization of bandwidth.Meanwhile, the emotion fed back by the Voice & Video of user is classified and how mark ensures accuracy still There is certain problem.
" W.Cai, Z.Hong, X.Wang, H.C.B.Chan and V.C.M.Leung, " Quality of Experience Optimization for Cloud Gaming System with Ad-hoc Cloudlet Assistance ", IEEE Transactions on Circuits and Systems for Video Technology, Volume.25, Issue.12, Page 2092-2104,2015. " game user that this technology proposes within LAN passes through The mode of MANET mutually shares similar game picture, thus realizes reducing the target of cloud game user's overall bandwidth demand. The hypotheses of this technology is that the user's major part within LAN is all carrying out identical game, has between game picture simultaneously There is higher similarity, but this hypothesis is difficult in reality.It addition, equipment shares game picture by MANET Face, can increase the electric quantity consumption of mobile terminal, and this technology lacks the incentive measure that user shares computing capability, it is difficult in reality Situation is applied.
Summary of the invention
The too high problem of bandwidth occupancy existed for current cloud game platform, in order on the basis meeting gaming user experience On, reducing bandwidth cost and the network bandwidth requirements of user of cloud game operator as far as possible, the present invention proposes a kind of base Cloud game platform adaptive bandwidth optimization method in area-of-interest.
To achieve these goals, the technical scheme is that
A kind of cloud game platform adaptive bandwidth optimization method based on area-of-interest, comprises the following steps:
S1. cloud game platform cycle of operation is cut into several time periods；
S2., when each time period starts, central control unit obtains the bandwidth information of each game user；
S3. central control unit bandwidth information based on current collection solves the result of decision, and its result of decision includes each The area-of-interest size of game user；
S4. based on the result of decision obtained, the game picture of each game user is carried out Video coding；
The mode solving the acquisition result of decision in step S3 is: cloud game operator collects each by central control unit User's current bandwidth information, distributes different area-of-interest sizes to each user by greedy algorithm, it is ensured that each user Game video bandwidth less than its network bandwidth, the total bandwidth of all CUs is less than server outlet bandwidth, simultaneously The QoE index sum making entirety maximizes；
The mode carrying out Video coding in step S4 is: cloud game service business uses video encoder, according to presetting Each user area-of-interest QP difference outwardly and inwardly (QP (Quantization Parameter) is quantization step, Be H.264 in Video coding for weighing the parameter of video compress degree, value is 0-51.It is worth the biggest, then video compress degree The highest.QP difference illustrates the quantization step difference that area-of-interest is inside and outside, i.e. area-of-interest is inside and outside The difference of compression degree.QP difference is the biggest, illustrate that the picture quality difference inside and outside area-of-interest is the biggest), obtain in step S3 Area-of-interest size generates each Macro Block in picture jointly, and (Macro Block macro zone block, is in Video coding Minimum code unit, H.264 in coding, the macro zone block size of acquiescence is the rectangle of 16 pixel x16 pixels) QP value, then regard Frequently encoder interfaces carries out picture coding.
Preferably, step S3 solves the mode of the acquisition result of decision particularly as follows: assume have N number of user to be connected to cloud game Playing on server, cloud game provider provides K kind to play altogether；Make diT () is distributed the t time period by user i Area-of-interest size；For the functional relationship between user QoE and the area-of-interest size of type of play k, qi(t) be User i at the QoE of t time period, then hasΦkVideo bandwidth and region of interest for type of play k Functional relationship between the size of territory, biT () is the user i game video bandwidth t time period, then have bi(t)=Φk(di (t))；Use greedy algorithm, within each time period, calculate satisfied following optimization equation according to the bandwidth information of user The result of decision；
m a x Σ i = 1 N q i ( t ) .
Preferably, described user i is in game video bandwidth b of t time periodiT () is necessarily less than user i at t The network bandwidth B of time periodiT (), i.e. meets following formula；
b i ( t ) ≤ B i ( t ) , ∀ i .
Preferably, the user i area-of-interest size t time period have to be larger than or equal to for going game class Type, user to obtain the minimum area-of-interest size that basic Consumer's Experience should select when playing；By following formula Determine:
d i ( t ) ≥ d min ( G ( i ) ) , ∀ i
Wherein, diT () represents the area-of-interest size that user i is distributed the t time period, G (i) represents user i Selected type of play, dminIt is emerging that (G (i)) represents that user i to obtain the required minimum sense asked of most basic Consumer's Experience Interest area size；
Whole expression formula is used for guaranteeing each user i, at each time period t, its received region of interest Territory size can ensure that it obtains most basic Consumer's Experience.
The definition of area-of-interest of the present invention typically uses centered by screen center's point, by program specify corresponding length and The rectangular area of width.
Compared with prior art, the invention have the benefit that the present invention taken into full account different type of play for The impact of family Quality of experience, proposes the video coding parameter selection mode of correspondence for different type of plaies.Meanwhile, this Bright biology, cognitive psychology and the computer science achievement in research to human visual system are also taken into full account, by adjusting Area-of-interest size in game picture, on the premise of affecting user experience quality as few as possible, reduces cloud game to band Wide takies.
Accompanying drawing explanation
Fig. 1 is existing cloud game paralell composition.
Fig. 2 is the flow chart of cloud game platform adaptive bandwidth optimization method based on area-of-interest.
Detailed description of the invention
The present invention will be further described below in conjunction with the accompanying drawings, but embodiments of the present invention are not limited to this.
Cloud game platform
Cloud game platform is the game mode based on cloud computing, and server end collects user's input of client, trip Play logic and game picture render and all run at server end, and the game picture after server will render is encoded to video flowing User is sent to afterwards by network.In client, user have only to have good network connect, be equipped with input-output equipment and There is the video compression ability on basis.
Area-of-interest
When human visual system processes complex scene, its visual attention can be concentrated on the several of this scene Individual object, and these object priority are processed, to make every effort to obtain the main information in scene in the shortest time, this process is referred to as vision Noting process, the region that these objects are constituted in the scene is area-of-interest.
User experience quality
User experience quality (Quality of Experience) be user with service or apply mutual process In, user a kind of subjective feeling to service produced.In the present invention, user experience quality represents that user is to game image quality Subjective feeling.For quantitative assessment user experience quality, the present invention uses relevant objective indicator to characterize user experience quality.Pin The problems such as operation cost present in live platform is too high to playing, spectators' skewness weighing apparatus, the present invention propose a kind of based on The cloud game platform adaptive bandwidth optimization method of area-of-interest.The method is on the basis of meeting viewer experience, it is achieved that Reduce the operation cost of operator as much as possible.
The present invention has taken into full account the impact for user experience quality of the different type of play, the present invention is directed to different trips The cloud game video coding parameter selection algorithm that play type selecting is corresponding, to reach cloud game platform based on area-of-interest certainly Adapt to the purpose of bandwidth optimization.Meanwhile, the present invention has also taken into full account that biology, cognitive psychology and computer science are to the mankind The achievement in research of visual system, by adjusting area-of-interest size in game picture, is affecting Consumer's Experience as few as possible On the premise of quality, reduce cloud game and bandwidth is taken.
The basic fundamental of the present invention includes: user's QoE model, video bandwidth model, cloud game video coding parameter select Algorithm.
User's QoE model
In cloud game platform, user QoE reflects the game user satisfaction for game services.User QoE is Weigh one of important indicator of cloud game platform property.
First, the present invention is directed to the different type of plaies that different game users selects, define relevant to type of play QoE index, and define the basic area-of-interest size requirements of dissimilar game.Basic area-of-interest size requirements Referring to for going game type, game user, when playing, will obtain what basic Consumer's Experience should select Minimum area-of-interest size.
d i ( t ) ≥ d m i n ( G ( i ) ) , ∀ i
Wherein, diT () represents the area-of-interest size that user i is distributed the t time period, G (i) represents user i Selected type of play, dmin(G (i)) represents that user i to obtain the region of interest of the required request of most basic Consumer's Experience Territory size.Whole expression formula is used for guaranteeing that, to each game user i, in each time period t, its received game regards Frequently area-of-interest size can ensure that it obtains most basic Consumer's Experience.
It is directly related that the present invention defines the area-of-interest size that user QoE receives with user, is specifically defined as:
Wherein,For the functional relationship between user QoE and the area-of-interest size of type of play k.
Video bandwidth model
In cloud game platform, the bandwidth shared by game video and area-of-interest size in video pictures and feel emerging Interest intra-zone is relevant with outside video quality parameter.Determining the video quality parameter that area-of-interest is inside and outside Afterwards, the bandwidth shared by game video is directly related with area-of-interest size.The present invention defines biT () is that user i is at t Amount of bandwidth shared by the individual time period, is specifically defined as:
bi(t)=Φk(di(t))
Wherein, ΦkFor the functional relationship between video bandwidth and the area-of-interest size of type of play k.
Cloud game video coding parameter selection algorithm
Below in conjunction with flow chart 2 and embodiment to cloud game platform adaptive bandwidth optimization side based on area-of-interest Method is described further.
Fig. 2 is the flow chart of " cloud game platform adaptive bandwidth optimization method based on area-of-interest ", concrete steps As follows:
(S101) cloud game platform cycle of operation is cut into several time periods.
(S102) when each time period starts, central control unit obtains the bandwidth information of each game user.
(S103) central control unit bandwidth information based on current collection solves the result of decision, and its result of decision includes often The area-of-interest size of individual game user.
(S104) according to the result of decision of step (S103), the game picture of each game user is carried out Video coding.
In a detailed description of the invention, in step (S102), the information of current collection includes the information such as user bandwidth.
In a detailed description of the invention, the present invention uses greedy algorithm to solve about area-of-interest size and video tape The optimization problem constituted between width, user QoE, obtains the result of decision of each user's area-of-interest size.
It is defined as follows optimization problem:
m a x Σ i = 1 N q i ( t )
This optimization problem represents that the QoE sum of the N name user on cloud game service device should maximize.
This optimization problem should also conform to following constraints:
1, the user i game video bandwidth t time period is necessarily less than equal to user i at the net of t time period Network bandwidth BiT (), i.e. meets following formula:
b i ( t ) ≤ B i ( t ) , ∀ i
2, the game video bandwidth sum of all users is necessarily less than the outlet bandwidth C provided equal to server, the most satisfied Following formula:
Σ i = 1 N b i ( t ) ≤ C
3, the user i area-of-interest size t time period have to be larger than the base of the game selected equal to this user This area-of-interest size, i.e. meets following formula:
d i ( t ) ≥ d m i n ( G ( i ) ) , ∀ i
The present invention proposes a kind of cloud game video coding parameter selection algorithm.Cloud game video coding parameter is used to select The result of decision in Algorithm for Solving step (S103), the false code of this algorithmic procedure is as follows.
The present invention proposes a kind of cloud game platform adaptive bandwidth optimization method based on area-of-interest, and the present invention is detailed Carefully describe cloud game video coding parameter selection algorithm.The present invention can have multiple method in the specific implementation, including but not It is confined to:
1, prediction algorithm is used to obtain the network bandwidth of user；
2, do fine tune for game user QoE model, such as add the inside and outside video of area-of-interest and compile Code mass parameter, as QoE model parameter, adds user's viewing distance as QoE model parameter etc..
3, different objective indicators implementing as user's QoE model is used, such as SSIM, PSNR etc..
In the present invention, the structure of each module and connected mode all can be varied from, in technical solution of the present invention On the basis of, all improvement structure of indivedual algoritic modules carried out according to the principle of the invention and equivalents, the most should not get rid of Outside protection scope of the present invention.
Crucial mathematical model and method in the working-flow that the present invention proposes have: user's QoE model, video bandwidth Model and cloud game video coding parameter system of selection.User's QoE model tormulation game user satisfaction for game services Degree, is the basis of the present invention.The cloud game video coding parameter system of selection that the present invention proposes can be according to limited user network The information such as network bandwidth, dynamically make user's game picture area-of-interest size decision-making, on the basis of ensureing user QoE, Optimize bandwidth cost and the network bandwidth requirements of cloud game user of cloud game operator.The cloud game video that the present invention proposes Coding parameter selection algorithm is the core content of the present invention.
The embodiment of invention described above, is not intended that limiting the scope of the present invention.Any at this Amendment, equivalent and improvement etc. done within bright spiritual principles, should be included in the claim protection of the present invention Within the scope of.

Claims (4)

1. a cloud game platform adaptive bandwidth optimization method based on area-of-interest, it is characterised in that include following step Rapid:
S1. cloud game platform cycle of operation is cut into several time periods；
S2., when each time period starts, central control unit obtains the bandwidth information of each game user；
S3. central control unit bandwidth information based on current collection solves the result of decision, and its result of decision includes each game The area-of-interest size of user；
S4. based on the result of decision obtained, the game picture of each game user is carried out Video coding；
The mode solving the acquisition result of decision in step S3 is: each user collects by central control unit in cloud game operator Current bandwidth information, distributes different area-of-interest sizes to each user by greedy algorithm, it is ensured that the trip of each user Play video bandwidth is less than server outlet bandwidth less than its network bandwidth, the total bandwidth of all CUs, makes whole simultaneously The QoE index sum of body maximizes；
The mode carrying out Video coding in step S4 is: cloud game service business uses video encoder, according to set in advance respectively The area-of-interest size obtained in the area-of-interest of user QP difference outwardly and inwardly, with step S3 generates picture jointly In the QP value of each Macro Block, then video encoder interface carries out picture coding.
Method the most according to claim 1, it is characterised in that the mode solving the acquisition result of decision in step S3 is concrete For: assuming that having N number of user to be connected on cloud game service device plays, cloud game provider provides K kind to play altogether；Make di T area-of-interest size that () is distributed the t time period by user i；For the user QoE of type of play k with interested Functional relationship between area size, qiT () is the user i QoE t time period, then haveΦkFor Functional relationship between video bandwidth and the area-of-interest size of type of play k, biT () is that user i is t time period Game video bandwidth, then have bi(t)=Φk(di(t))；Using greedy algorithm, the bandwidth information of foundation user is in each time The result of decision of satisfied following optimization equation is calculated in Duan；
max Σ i = 1 N q i ( t ) .
Method the most according to claim 2, it is characterised in that described user i is in the game video bandwidth of t time period biT () is necessarily less than the user i network bandwidth B t time periodiT (), i.e. meets following formula；
b i ( t ) ≤ B i ( t ) , ∀ i .
Method the most according to claim 3, it is characterised in that user i must in the area-of-interest size of t time period Must be more than or equal to for going game type, user to obtain what basic Consumer's Experience should select when playing Minimum area-of-interest size；Determined by following formula:
d i ( t ) ≥ d min ( G ( i ) ) , ∀ i
Wherein, diT () represents the area-of-interest size that user i is distributed the t time period, G (i) represents selected by user i Type of play, dmin(G (i)) represents that user i to obtain the minimum area-of-interest of the required request of most basic Consumer's Experience Size；
Whole expression formula is used for guaranteeing that, to each user i, in each time period t, its received area-of-interest is big The little Consumer's Experience that can ensure that its acquisition is most basic.
CN201610882001.2A 2016-10-08 2016-10-08 A kind of cloud game platform adaptive bandwidth optimization method based on area-of-interest Active CN106331750B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201610882001.2A CN106331750B (en) 2016-10-08 2016-10-08 A kind of cloud game platform adaptive bandwidth optimization method based on area-of-interest

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201610882001.2A CN106331750B (en) 2016-10-08 2016-10-08 A kind of cloud game platform adaptive bandwidth optimization method based on area-of-interest

Publications (2)

Publication Number Publication Date
CN106331750A true CN106331750A (en) 2017-01-11
CN106331750B CN106331750B (en) 2019-04-30

Family

ID=57821511

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201610882001.2A Active CN106331750B (en) 2016-10-08 2016-10-08 A kind of cloud game platform adaptive bandwidth optimization method based on area-of-interest

Country Status (1)

Country Link
CN (1) CN106331750B (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108769192A (en) * 2018-05-29 2018-11-06 努比亚技术有限公司 A kind of game bandwidth regulation and control method, equipment and computer readable storage medium
CN110087081A (en) * 2019-05-05 2019-08-02 腾讯科技（深圳）有限公司 Method for video coding, device, server and storage medium
CN110996125A (en) * 2019-11-18 2020-04-10 腾讯科技（深圳）有限公司 Video stream generation method and device, electronic equipment and storage medium
CN112118212A (en) * 2019-06-21 2020-12-22 广州虎牙科技有限公司 Video data output method and system based on cloud platform and cloud platform
WO2023045649A1 (en) * 2021-09-26 2023-03-30 腾讯科技（深圳）有限公司 Video frame playing method and apparatus, and device, storage medium and program product

Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101262604A (en) * 2008-04-23 2008-09-10 哈尔滨工程大学 A telescopic video coding method for optimized transmission of interested area
CN101420618A (en) * 2008-12-02 2009-04-29 西安交通大学 Adaptive telescopic video encoding and decoding construction design method based on interest zone
CN101945275A (en) * 2010-08-18 2011-01-12 镇江唐桥微电子有限公司 Video coding method based on region of interest (ROI)
US20120028712A1 (en) * 2010-07-30 2012-02-02 Britesmart Llc Distributed cloud gaming method and system where interactivity and resources are securely shared among multiple users and networks
CN103428174A (en) * 2012-05-17 2013-12-04 云联（北京）信息技术有限公司 Interactive motion sensing game implementation method based on cloud computation
US20130324263A1 (en) * 2011-04-28 2013-12-05 Yavuz Ahiska Adaptive application selection in cloud gaming
CN103763307A (en) * 2013-12-30 2014-04-30 华中科技大学 Bandwidth optimization method and system
US20140281023A1 (en) * 2013-03-18 2014-09-18 Nvidia Corporation Quality of service management server and method of managing quality of service
US20140286438A1 (en) * 2013-03-19 2014-09-25 Nvidia Corporation Quality of service management server and method of managing streaming bit rate
US20140286440A1 (en) * 2013-03-19 2014-09-25 Nvidia Corporation Quality of service management system and method of forward error correction
CN104092711A (en) * 2013-04-01 2014-10-08 云联（北京）信息技术有限公司 Cloud game realizing method and system
US20140349763A1 (en) * 2013-05-22 2014-11-27 Dell Products, Lp System and Method for Providing Performance in a Personal Gaming Cloud
CN104363277A (en) * 2014-11-13 2015-02-18 上海交通大学 Allocation management system and management method for bandwidth resources in cloud game distributed system
CN104598292A (en) * 2014-12-15 2015-05-06 中山大学 Adaptive streaming adaptation and resource optimization method applied to cloud-game system

Patent Citations (14)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101262604A (en) * 2008-04-23 2008-09-10 哈尔滨工程大学 A telescopic video coding method for optimized transmission of interested area
CN101420618A (en) * 2008-12-02 2009-04-29 西安交通大学 Adaptive telescopic video encoding and decoding construction design method based on interest zone
US20120028712A1 (en) * 2010-07-30 2012-02-02 Britesmart Llc Distributed cloud gaming method and system where interactivity and resources are securely shared among multiple users and networks
CN101945275A (en) * 2010-08-18 2011-01-12 镇江唐桥微电子有限公司 Video coding method based on region of interest (ROI)
US20130324263A1 (en) * 2011-04-28 2013-12-05 Yavuz Ahiska Adaptive application selection in cloud gaming
CN103428174A (en) * 2012-05-17 2013-12-04 云联（北京）信息技术有限公司 Interactive motion sensing game implementation method based on cloud computation
US20140281023A1 (en) * 2013-03-18 2014-09-18 Nvidia Corporation Quality of service management server and method of managing quality of service
US20140286440A1 (en) * 2013-03-19 2014-09-25 Nvidia Corporation Quality of service management system and method of forward error correction
US20140286438A1 (en) * 2013-03-19 2014-09-25 Nvidia Corporation Quality of service management server and method of managing streaming bit rate
CN104092711A (en) * 2013-04-01 2014-10-08 云联（北京）信息技术有限公司 Cloud game realizing method and system
US20140349763A1 (en) * 2013-05-22 2014-11-27 Dell Products, Lp System and Method for Providing Performance in a Personal Gaming Cloud
CN103763307A (en) * 2013-12-30 2014-04-30 华中科技大学 Bandwidth optimization method and system
CN104363277A (en) * 2014-11-13 2015-02-18 上海交通大学 Allocation management system and management method for bandwidth resources in cloud game distributed system
CN104598292A (en) * 2014-12-15 2015-05-06 中山大学 Adaptive streaming adaptation and resource optimization method applied to cloud-game system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
张晓莉: "基于QoE的无线网络优化与设计", 《中国优秀硕士学位论文-信息科技辑》 *
李开龙: "光纤到户网络中基于用户体验度的带宽分配方法研究", 《中国优秀硕士学位论文-信息科技辑》 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108769192A (en) * 2018-05-29 2018-11-06 努比亚技术有限公司 A kind of game bandwidth regulation and control method, equipment and computer readable storage medium
CN110087081A (en) * 2019-05-05 2019-08-02 腾讯科技（深圳）有限公司 Method for video coding, device, server and storage medium
CN112118212A (en) * 2019-06-21 2020-12-22 广州虎牙科技有限公司 Video data output method and system based on cloud platform and cloud platform
CN112118212B (en) * 2019-06-21 2021-09-24 广州虎牙科技有限公司 Video data output method and system based on cloud platform and cloud platform
CN110996125A (en) * 2019-11-18 2020-04-10 腾讯科技（深圳）有限公司 Video stream generation method and device, electronic equipment and storage medium
CN110996125B (en) * 2019-11-18 2021-08-17 腾讯科技（深圳）有限公司 Video stream generation method and device, electronic equipment and storage medium
WO2023045649A1 (en) * 2021-09-26 2023-03-30 腾讯科技（深圳）有限公司 Video frame playing method and apparatus, and device, storage medium and program product
CN115883853A (en) * 2021-09-26 2023-03-31 腾讯科技（深圳）有限公司 Video frame playing method, device, equipment and storage medium
CN115883853B (en) * 2021-09-26 2024-04-05 腾讯科技（深圳）有限公司 Video frame playing method, device, equipment and storage medium

Also Published As

Publication number Publication date
CN106331750B (en) 2019-04-30

Similar Documents

Publication Publication Date Title
CN106331750B (en) A kind of cloud game platform adaptive bandwidth optimization method based on area-of-interest
Sinno et al. Large-scale study of perceptual video quality
He et al. Rubiks: Practical 360-degree streaming for smartphones
Xie et al. 360ProbDASH: Improving QoE of 360 video streaming using tile-based HTTP adaptive streaming
US11475539B2 (en) Electronic apparatus, system and controlling method thereof
CN103024445B (en) The video transcoding method in high in the clouds and Cloud Server
CN106504278A (en) HDR tone maps
Zadtootaghaj et al. Quality estimation models for gaming video streaming services using perceptual video quality dimensions
WO2006126974A1 (en) Optimal video adaptation for resource constrained mobile devices based on subjective utility models
Li et al. A cost-constrained video quality satisfaction study on mobile devices
CN102802054B (en) Control method during a kind of multi-stream video is live and device
CN102724557B (en) Coding control method and device in a kind of multi-stream video live streaming
Huang et al. Utility-oriented resource allocation for 360-degree video transmission over heterogeneous networks
Menkovski et al. Adaptive psychometric scaling for video quality assessment
Jo et al. Efficient Computation Offloading in Mobile Cloud Computing for Video Streaming Over 5G.
Sun et al. Video rate control strategies for cloud gaming
Liu et al. Video quality assessment using space–time slice mappings
WO2021169392A1 (en) Video data processing method and apparatus, device, and readable storage medium
US20230319292A1 (en) Reinforcement learning based rate control
Ahmadi et al. Efficient bitrate reduction using a game attention model in cloud gaming
CN114363703B (en) Video processing method, device and system
Yarnagula et al. QoE for mobile clients with segment-aware rate adaptation algorithm (SARA) for DASH video streaming
Jiang et al. HD3: Distributed dueling DQN with discrete-continuous hybrid action spaces for live video streaming
Zhang et al. Quality-of-Experience Evaluation for Digital Twins in 6G Network Environments
Bradai et al. Efficient content delivery scheme for layered video streaming in large-scale networks

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant