CN105979274B - The distributed caching laying method of dynamic self-adapting video stream media - Google Patents
The distributed caching laying method of dynamic self-adapting video stream media Download PDFInfo
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- 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
- H04N21/21—Server components or server architectures
- H04N21/218—Source of audio or video content, e.g. local disk arrays
- H04N21/2181—Source of audio or video content, e.g. local disk arrays comprising remotely distributed storage units, e.g. when movies are replicated over a plurality of video servers
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- 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
- H04N19/103—Selection of coding mode or of prediction mode
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- 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
- H04N19/146—Data rate or code amount at the encoder output
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- H04N19/30—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using hierarchical techniques, e.g. scalability
- H04N19/395—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using hierarchical techniques, e.g. scalability involving distributed video coding [DVC], e.g. Wyner-Ziv video coding or Slepian-Wolf video coding
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- 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
- H04N21/234363—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 by altering the spatial resolution, e.g. for clients with a lower screen resolution
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- 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
- H04N21/266—Channel or content management, e.g. generation and management of keys and entitlement messages in a conditional access system, merging a VOD unicast channel into a multicast channel
- H04N21/2662—Controlling the complexity of the video stream, e.g. by scaling the resolution or bitrate of the video stream based on the client capabilities
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- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/60—Network structure or processes for video distribution between server and client or between remote clients; Control signalling between clients, server and network components; Transmission of management data between server and client, e.g. sending from server to client commands for recording incoming content stream; Communication details between server and client
- H04N21/63—Control signaling related to video distribution between client, server and network components; Network processes for video distribution between server and clients or between remote clients, e.g. transmitting basic layer and enhancement layers over different transmission paths, setting up a peer-to-peer communication via Internet between remote STB's; Communication protocols; Addressing
- H04N21/647—Control signaling between network components and server or clients; Network processes for video distribution between server and clients, e.g. controlling the quality of the video stream, by dropping packets, protecting content from unauthorised alteration within the network, monitoring of network load, bridging between two different networks, e.g. between IP and wireless
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Abstract
The present invention provides a kind of distributed caching laying methods for dynamic self-adapting video stream media, each Video coding is the version of multiple and different code rates by dynamic self-adapting streaming media coding technology at the method combination primary server, code rate-distortion performance difference between variant video content is combined, the buffer memory capacity of Edge Server limits, the network connection situation and video on demand probability distribution of different user, the video version subset of caching needed for determining each Edge Server using distributed cache optimization laying method, the final maximization realized user and download viewing video total quality by Edge Server.The present invention improves the utilization rate of Edge Server buffered video content, alleviates the video stream media service load at primary server, provides more preferably Video service quality for user.
Description
Technical Field
The invention relates to a method in the technical field of data communication, in particular to a distributed cache placement method suitable for dynamic self-adaptive video streaming media.
Background
With the rapid increase of mobile data traffic and the increasing popularity of intelligent terminal devices, wireless video streaming media technology represented by mobile video services has been increasingly widely applied in recent years. At the same time, mobile users exhibit more complex heterogeneous characteristics in terms of mobile device terminals used, on-demand content, and network connectivity. The dynamic self-adaptive streaming media technology can provide different versions of the same video content for users so as to improve the video watching satisfaction of the users in a heterogeneous network. Each video version is coded at a given code rate and/or resolution, so that each user can determine to download the most suitable video version according to the video-on-demand requirement and the network condition of the user.
On the other hand, network video traffic exhibits a highly time varying characteristic, embodied in network congestion during peak periods and network under-utilization during valley periods. To alleviate the situation of video traffic congestion during peak periods, caching at the edge server can utilize the storage capacity of the edge server to pre-cache specific video content during off-peak periods, thereby serving to smooth the time-varying characteristics of video traffic and reduce network congestion and transmission delay. The edge server is closer to the mobile user than the main server, so the caching at the edge server can also greatly alleviate the video service load at the main server and transmit the video content to the mobile user with lower delay through the local high-speed link between the edge server and the user.
From the search of the prior art, y.jin et al published An article entitled "optimal transcoding and caching for media cloud adaptive streaming in media cloud" in IEEE Transactions on circuits and Systems for Video Technology, dec.2015, pp.1914-1925 (proceedings of circuit and Systems for Video Technology by the institute of electrical and electronics engineers, 2015 12, 1914 and 1925, which introduced a caching mechanism into a dynamic adaptive Video streaming media and studied the problem of optimal transcoding and caching resource allocation in the media cloud to minimize the overall operation cost of Video transmission. However, the article is mainly based on a scenario assumption that a mobile user connects to a single edge server, and an improvement space is left for further cooperation among edge servers to improve caching performance.
It is found through search that K.Shanmugam et al published an article entitled "Wireless content delivery through distributed caching helpers" on IEEE Transactions on information theory, Dec.2013, pp.8402-8413 (the institute of Electrical and electronics Engineers information theory, 12.2013, page 8402-8413), which studied the video content caching problem of distributed edge servers in the network for a scenario where a single mobile user can simultaneously connect to multiple edge servers. Through cooperation among the edge servers, video service load is transferred from the main server segment to the edge servers, and therefore average video downloading delay of users is minimized. However, the video content related to the article only has a single bitrate version, and cannot adapt to the differentiated bandwidth situation and the on-demand requirement of users in a heterogeneous network.
In addition, the above work only considers the performance of the edge server cache in terms of operation cost or bit rate, treats all videos as the same data file, and ignores different content information of different videos (for example, different video contents have different bit rate-distortion performance), thereby causing the overall performance of the system to be reduced when the video streaming media is cached to a certain extent.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a distributed cache placement method suitable for dynamic self-adaptive video streaming media.
In order to realize the purpose, the invention adopts the technical scheme that: and by combining a dynamic self-adaptive streaming media coding technology at the main server, coding each video into a plurality of versions with different code rates, and simultaneously considering the difference of code rate-distortion performance among different video contents, the limitation of the cache capacity of the edge server, the network connection conditions of different users and the video on demand probability distribution, determining the video version subset required to be cached by each edge server by adopting a distributed cache optimization placement method, and finally realizing the maximization of the overall quality of the video downloaded and watched by the user through the edge server. The invention improves the utilization rate of the edge server for caching the video content, lightens the video streaming media service load at the main server and provides better video service quality for users.
The invention provides a distributed cache placement method suitable for dynamic self-adaptive video streaming media, which comprises the following steps:
firstly, at a main server, coding each video into a plurality of video versions with different code rates by using a dynamic self-adaptive streaming media coding technology, and obtaining the difference of code rate-distortion performance among different video contents;
secondly, caching the video version with a specific code rate in advance according to the cache capacity limit of the edge server at the edge server so as to serve the video on demand request of a user through a local high-speed link;
thirdly, at the user, according to the on-demand requirements of different users and differentiated network conditions, selecting and downloading a video version with the highest code rate from an edge server adjacent to the user;
and step four, based on the previous three steps, adopting parameters: and establishing an optimization problem suitable for distributed cache placement of the dynamic self-adaptive video streaming media by using a complete set consisting of different versions of the video obtained by coding at the main server, the cache capacity limit of the edge server, the network connection condition of the user and the video on demand probability distribution, and obtaining an optimal video version subset cached by each edge server in the second step by using a rapid and efficient distributed cache content placement method, wherein the optimal video version subset restricts the code rate of the video version with the highest code rate which can be downloaded by each user in the third step.
Preferably, in the first step, the main server can encode any one video file into a plurality of video versions with different encoding rates by using a dynamic adaptive streaming media encoding technology. The video files show different code rate-distortion performance due to different contents.
Preferably, in the second step, the edge server can pre-cache the video version with a specific bitrate, and the total size of the video version cached by the edge server is limited by the physical cache capacity of the edge server. The edge server is closer to the user than the main server, so that a high-speed local link can be established with the user through high-density spatial multiplexing of wireless resources, and the video-on-demand request of the user can be responded and served more quickly.
Preferably, in the third step, the user can make a video-on-demand request to the adjacent edge server, and select to download the video version with high bitrate from the adjacent edge server. The criteria for determining the downloading of the video version with the highest bitrate are as follows: firstly, inquiring whether the highest code rate version of the requested video is cached in an edge server set adjacent to a user in advance, if so, selecting an edge server with the highest downloading bandwidth from all edge servers caching the highest code rate video version to download the video version; if the video does not exist, inquiring the version of the video with the second high code rate; and so on until finding a certain bitrate version of the video requested by the user in the set of adjacent edge servers; if the user cannot find any bitrate version of the video cached at any adjacent edge server, the user will choose to download the video from the main server.
Preferably, in the fourth step, the optimization problem applicable to the distributed cache placement of the dynamic adaptive video streaming media is obtained by using a network utility maximization modeling method, in combination with a corpus consisting of different versions of the video encoded at the main server, the cache capacity limit of the edge server, and the network connection condition and the video on demand probability distribution of the user.
Preferably, in the fourth step, when determining a specific cached video version subset for each edge server, the distributed cached content placement method uses a high-cost benefit greedy algorithm with polynomial time complexity and high approximate optimization performance, and finally, realizes the optimized placement of the distributed cached content of each edge server quickly and efficiently.
More preferably, in the fourth step, the method for placing distributed cache contents specifically comprises the following steps:
(a) initialization: setting an initial local optimal solution set as an empty set, an initial search set as a full set consisting of different versions of the video, and the initial step number as 1;
(b) an iterative search step: according to an existing local optimal solution set, searching an element which enables the ratio of marginal increment to code rate cost to be maximum in a residual search set, wherein the residual search set is a complement of the local optimal solution to the search set, and one element in the residual search set corresponds to a certain code rate version of a certain video cached on a certain edge server;
(c) an updating step: if the element searched in the adding step (b) can still meet the cache capacity constraint of each edge server, adding the element to the local optimal solution set, and keeping the search set unchanged; if the addition of the element cannot meet the cache capacity constraint of each edge server, the local optimal solution set is kept unchanged, and the element is removed from the search set;
(d) a judging step: if the rest search set is not an empty set, adding the search steps together and returning to the iterative search step; otherwise, stopping iteration and outputting the current local optimal solution set as an optimal result.
Compared with the prior art, the invention has the following beneficial effects:
the invention provides a completely distributed cache placement method for adapting to the needs of dynamic self-adaptive streaming media technology, improves the utilization rate of the cache video content of the edge server, lightens the video streaming media service load at the main server and provides better video service quality for users.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a flow chart of a method according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a distributed cache network according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a process for a user to determine to download a video version with a maximum bitrate from a neighboring edge server according to an embodiment of the present invention;
FIG. 4 is a flowchart of a distributed cache placement method according to an embodiment of the present invention;
FIG. 5 is a diagram illustrating a network configuration according to an embodiment of the present invention;
FIG. 6 is a diagram illustrating video bitrate distortion performance according to an embodiment of the invention;
FIG. 7 is a diagram illustrating distributed cache placement performance according to an embodiment of the invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications can be made by persons skilled in the art without departing from the spirit of the invention. All falling within the scope of the present invention.
Referring to fig. 1, a flow of a distributed cache placement method suitable for a dynamic adaptive video streaming media is specifically implemented by the following steps:
1. dynamic adaptive streaming media coding at a host server
As shown in fig. 2, an example analysis is performed on the distributed cache network, and it is assumed that F video files (F is any positive integer greater than 2) are stored at the main server and are recorded as a video file setThe playing time length of each video file is T. Any one video file is coded by using dynamic self-adaptive streaming media coding technologyThe coding is the video edition with M different code rates (M is any positive integer larger than 2), and is recorded as the video edition setWherein the mth video version fmThe coding rate is recorded as RfmAnd the sets are arranged in descending order according to the coding rate, i.e.Thus, a complete set containing all versions of all F video files can be recorded asOn the other hand, the main server grasps the rate-distortion performance information of all video files, i.e., Dmax-Df(R) represents a video filef video distortion corresponding to coding rate R, wherein DmaxAnd Df(R) represents the maximum distortion constant when the video cannot be decoded and the amount of video distortion reduction after successfully decoding the rate R version of the video file f, respectively.
2. Distributed caching at edge servers
FIG. 2 also shows S edge servers distributed in the network, denoted as a set of edge serversThese edge servers can pre-cache video versions with a particular bitrate, since they are closer to the user than the main server, and can thus more quickly respond to and serve the user's video-on-demand request by establishing a high-speed local link with the user through high-density spatial multiplexing of radio resources. For each edge serverIn other words, the number of video versions that it can pre-fetch and cache from the host server is limited by its physical storage capacity BsThe limit of (2). Defining a set of basesRepresenting a corpus of all possible cached video versions at the edge server s, with elementsIndicating that edge server s caches the mth bitrate version of video file f.
3. Video request and download at a user
Fig. 2 also shows U users randomly distributed in the network, denoted as the set of users U ═ 1, 2. The user may make a video-on-demand request to an adjacent edge server and choose to download a version of the video with the highest bitrate (i.e., best quality) from the adjacent edge server. For each userIn other words, the set of edge servers connected to it by wireless links is denoted asAnd will aggregateIn descending order of the download bandwidth of the wireless link with the user u, so thatThe edge server, which represents the download band size of the wireless link with user u, is wide ranked in the ith position.
Fig. 3 shows a flow diagram for a user determining a download video version from a nearby edge server. As shown in FIG. 3, when a user u requests a video file f on demand, the user u first queries the highest bitrate version f of the video1Whether to pre-cache in its neighboring set of edge serversIf yes, selecting the edge server with the highest download bandwidth from all edge servers caching the video version to download the video version; if not, f is the version of the video with the second high code rate2Inquiring; and so on until inUntil a bitrate version of the video is found. If user u isIf any edge server in (1) cannot find any bitrate version of the video cached, it will choose to download the video from the main server.
4. Establishing optimization problem of distributed cache placement suitable for dynamic self-adaptive video streaming media, and providing rapid and efficient distributed cache content placement method
The optimization problem for establishing distributed cache placement for dynamically adaptive video streaming is as follows (where the meaning of each parameter can be obtained in context):
the objective optimization problem is as follows:
constraint conditions are as follows:
wherein the optimization variables are:representing a collection of video versions cached on respective edge servers. In particular, a certain elementThe mth bitrate version representing video file f is cached on the edge server s.
The optimization target is as follows: maximizing the sum of the expected video distortion reduction for all usersWherein,is the basis set of the optimization problem,then it means that the probability that the known user u requests the video file f is Pu，fBased on the downloading process shown in FIG. 3, through the edge server setIn response to all video-on-demand requests from user u and transmitting the desired video version to user u to achieve the desired amount of video distortion reduction, i.e.
Indicator function in the above equationHas a value ofIs 1 atIs 0, whereinThe edge server, which represents the size of the download bandwidth of the wireless link with user u wide-ranked at j-th position, caches the mth bitrate version of video file f.
The constraint conditions are as follows: edge server physical cache constraints, i.e. requiring any one edge serverThe sum of the sizes of all the video versions of the upper buffer does not exceed the physical storage capacity B thereofs。
As shown in fig. 4, a high-cost greedy algorithm with polynomial time complexity and high approximate optimization performance is provided, and finally, the optimal placement of distributed cache contents of each edge server is quickly and efficiently realized. The distributed cache placement method is implemented as follows (wherein the meaning of each parameter can be obtained in context):
(a) initialization: setting an initial set of locally optimal solutionsInitial search set v0V, the initial number of steps t is 1.
(b) Iterative search step (t ═ 1, 2, 3.):
according to the existing local optimal solution setIn the remaining search set(i.e. theFor Vt-1Complement of) In finding so as to increment marginAnd bit rate costElement having the largest ratio ofNamely, it is
In the above formula, elementsMth bitrate version, element representing caching of video file f on edge server sRepresenting the edges searched in the t-th search stepThe element with the largest ratio of inter-increment to rate cost corresponds to the edge server stUpper buffer video file ftM oftThe version of the code rate of each code rate,represents the coding rate of the mth rate version of the video file f, and T represents the time length of the video file.
(c) An updating step:
if adding elementsStill satisfy the cache capacity constraint of each edge server, i.e.
Then the element is replacedAdded to the locally optimal solution set and the search set is kept unchanged, i.e. orderedAnd vt＝vt-1(ii) a If the addition of the element fails to satisfy the cache capacity constraint of each edge server, the locally optimal solution set remains unchanged and the element is removed from the search set, i.e., orderedAnd
in the above formula, the first and second carbon atoms are,representing edge servers stThe physical storage capacity of the storage device (c),referred to at edge server stA certain video version cached on the upper layer, specifically representing the mth bitrate version of the video file f,representing all possible servers at the edge stA full set of cached video versions.
(d) A judging step:
if remaining search setIf not, making t equal to t +1 and returning to the iterative search step; otherwise, stopping iteration and outputting the current local optimal solution set as an optimal result.
FIG. 5 shows a specific example of a distributed cache network, comprising three edge servers S1、S2And S3And 20 mobile users. The line in the figure indicates that there is a wireless link between the edge server and the user and the bandwidth size of the wireless link is inversely proportional to the length of the line.
Fig. 6 shows rate-distortion performance curves for three specific video files (Crowd Run, vector, and sunflow) at the host server, where the spatial resolutions of the three videos are all 1080p (1920 × 1080) and the encoding frame rates are all 30 frames per second.
FIG. 7 shows that under different edge server number settings, the distributed cache content placement method of the present invention has better cache performance than the Femto cache method mentioned in the background art, where the maximum video distortion is Dmax＝500。
The invention aims to adapt to the requirements of multi-code rate version transmission of dynamic self-adaptive video streaming media and differentiated bandwidth conditions and on-demand requirements of users in heterogeneous networks, establishes the optimal placement problem of distributed caches based on the edge server, correspondingly provides a high-efficiency and rapid optimal placement method of the distributed caches, and realizes the maximization of the overall quality of videos downloaded and watched by the users through the edge server. The invention improves the utilization rate of the edge server for caching the video content, lightens the video streaming media service load at the main server and provides better video service quality for users.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes and modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention.
Claims (7)
1. A distributed cache placement method suitable for dynamic adaptive video streaming media is characterized by comprising the following steps:
firstly, at a main server, coding each video into a plurality of video versions with different code rates by using a dynamic self-adaptive streaming media coding technology, and obtaining the difference of code rate-distortion performance among different video contents;
secondly, caching the video version with a specific code rate in advance according to the cache capacity limit of the edge server at the edge server so as to serve the video on demand request of a user through a local high-speed link;
thirdly, at the user, according to the on-demand requirements of different users and differentiated network conditions, selecting and downloading a video version with the highest code rate from an edge server adjacent to the user;
and step four, based on the previous three steps, adopting parameters: the method comprises the steps that a complete set consisting of different versions of videos obtained by coding at a main server, the cache capacity limit of edge servers, the network connection condition of users and video on demand probability distribution are established, an optimization problem suitable for distributed cache placement of dynamic self-adaptive video streaming media is established, an optimal video version subset cached by each edge server in the second step is obtained by adopting a high-cost benefit greedy algorithm with polynomial time complexity and high approximate optimization performance, and the optimal video version subset restricts the code rate of the video version with the highest code rate which can be downloaded by each user in the third step.
2. The distributed cache placement method for dynamically adaptive video streaming according to claim 1, wherein in the second step, the edge server is closer to the user than the main server, so that a high-speed local link can be established with the user by high-density spatial multiplexing of wireless resources, thereby more quickly responding to and serving the user's video-on-demand request.
3. The distributed cache placement method for dynamically adaptive video streaming according to claim 1, wherein in the third step, the user can make a video on demand request to the adjacent edge server and choose to download the video version with the highest bitrate from the adjacent edge server.
4. The distributed cache placement method for dynamically adaptive video streaming according to claim 1, wherein in the third step, the criterion for determining to download the video version with the highest bitrate is: firstly, inquiring whether the highest code rate version of the requested video is cached in an edge server set adjacent to a user in advance, if so, selecting an edge server with the highest downloading bandwidth from all edge servers caching the highest code rate video version to download the video version; if the video does not exist, inquiring the version of the video with the second high code rate; and so on until finding a certain bitrate version of the video requested by the user in the set of adjacent edge servers; if the user cannot find any bitrate version of the video cached at any adjacent edge server, the user will choose to download the video from the main server.
5. The distributed cache placement method for dynamically adaptive video streaming according to any of claims 1-4, wherein in the fourth step, the optimization problem for distributed cache placement for dynamically adaptive video streaming is obtained by combining the corpus consisting of different versions of video encoded at the main server, the cache capacity limit of the edge server, and the network connection condition and video on demand probability distribution of the user, and using a network utility maximization modeling method.
6. The method according to claim 5, wherein in the fourth step, the optimization problem of the distributed buffer placement for the dynamic adaptive video streaming media is established as follows:
the objective optimization problem is as follows:
constraint conditions are as follows:
wherein the optimization variables are:representing a collection of cached video versions on respective edge servers, one elementThe mth code rate version representing the video file f is cached on the edge server s; edge server aggregationUser collectionEach userF. M is any positive integer greater than 2;representing the coding rate of the mth rate version of the video file f, and T representing the time length of the video file;
defining a set of basesRepresenting a corpus of all possible cached video versions at the edge server s, with elementsRepresenting the mth code rate version of the video file f cached by the edge server s;
the optimization target is as follows: maximizing the sum of the expected video distortion reduction for all usersWherein,is the basis set of the optimization problem,then it means that the probability that the known user u requests the video file f is Pu，fThrough edge server aggregationIn response to all video-on-demand requests from user u and transmitting the desired video version to user u to achieve the desired amount of video distortion reduction, i.e.
Indicator function in the above equationHas a value ofIs 1 atIs 0, whereinThe edge server that indicates the download bandwidth size of the wireless link with user u ranked at j has cached the mth bitrate version of video file f,indicates that the bitrate at which the video file f is successfully decoded isA video distortion reduction amount after the version of (1);
the constraint conditions are as follows: edge server physical cache constraints, i.e. requiring the size of all video versions cached on any edge server S ∈ SThe sum of the small sum does not exceed the physical storage capacity Bs。
7. The distributed cache placement method for dynamic adaptive video streaming media according to claim 1, wherein in the fourth step, the distributed cache content placement method specifically performs the following steps:
(a) initialization: setting an initial local optimal solution set as an empty set, an initial search set as a full set consisting of different versions of the video, and the initial step number as 1;
(b) an iterative search step: according to an existing local optimal solution set, searching an element which enables the ratio of marginal increment to code rate cost to be maximum in a residual search set, wherein the residual search set is a complement of the local optimal solution to the search set, and one element in the residual search set corresponds to a certain code rate version of a certain video cached on a certain edge server;
(c) an updating step: if the element searched in the adding step (b) can still meet the cache capacity constraint of each edge server, adding the element to the local optimal solution set, and keeping the search set unchanged; if the addition of the element cannot meet the cache capacity constraint of each edge server, the local optimal solution set is kept unchanged, and the element is removed from the search set;
(d) a judging step: if the rest search set is not an empty set, adding the search steps together and returning to the iterative search step; otherwise, stopping iteration and outputting the current local optimal solution set as an optimal result.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106713956B (en) * | 2016-11-16 | 2020-09-15 | 上海交通大学 | Code rate control and version selection method and system for dynamic self-adaptive video streaming media |
| CN107295070B (en) * | 2017-05-31 | 2019-10-29 | 上海交通大学 | The distributed coding caching laying method and system of file size isomery |
| CN107241577B (en) * | 2017-07-03 | 2019-08-13 | 华中科技大学 | A kind of processing system for video based on collaborative group mechanism |
| CN108777809B (en) * | 2018-04-11 | 2020-08-21 | 中国科学院信息工程研究所 | Panoramic video fragment mobile network caching method and system and panoramic video downloading method |
| CN108810468B (en) * | 2018-06-11 | 2020-06-16 | 哈尔滨工程大学 | Video transmission device and method for optimizing display effect |
| CN108833996B (en) * | 2018-07-03 | 2020-07-10 | 湖北大学 | Service node selection, update and code rate self-adaption method in distributed DASH system |
| CN109451517B (en) * | 2018-12-27 | 2020-06-12 | 同济大学 | Cache placement optimization method based on mobile edge cache network |
| CN110248210B (en) * | 2019-05-29 | 2020-06-30 | 上海交通大学 | Video transmission optimization method |
| CN111447506B (en) * | 2020-03-25 | 2021-10-15 | 武汉理工大学 | Streaming media content placement method based on delay and cost balance in cloud edge environment |
| CN111629217B (en) * | 2020-04-20 | 2021-11-26 | 南京邮电大学 | XGboost algorithm-based VOD (video on demand) service cache optimization method in edge network environment |
| CN114630183B (en) * | 2022-03-17 | 2024-03-26 | 东南大学 | Edge equipment caching method and evaluation method based on scalable coding |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102186072A (en) * | 2011-04-20 | 2011-09-14 | 上海交通大学 | Optimized transmission method of multi-rate multicast communication for scalable video stream |
| CN103069492A (en) * | 2010-06-18 | 2013-04-24 | 三星电子株式会社 | Storage file format for multimedia streaming file, and storage method and client apparatus using the same |
| CN103428107A (en) * | 2012-05-14 | 2013-12-04 | 中国科学院声学研究所 | Self-adaptive bitstream switching method and system based on cache underflow probability estimation |
| CN103733589A (en) * | 2011-08-09 | 2014-04-16 | 阿尔卡特朗讯公司 | Method for streaming video content, edge node and client entity realizing such a method |
| CN105007541A (en) * | 2015-07-29 | 2015-10-28 | 上海交通大学 | Scalable video stream dynamic multi-rate multicast optimal transmission method |
| CN105068755A (en) * | 2015-07-08 | 2015-11-18 | 南京邮电大学 | Data duplicate storage method facing cloud computing content distribution network |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8693850B2 (en) * | 2011-06-09 | 2014-04-08 | Xiaoping Zhang | System and method for video summarization and navigation based on statistical models |
| US9756142B2 (en) * | 2013-03-14 | 2017-09-05 | The Regents Of The University Of California | System and method for delivering video data from a server in a wireless network by caching the video data |
| US9241204B2 (en) * | 2013-05-31 | 2016-01-19 | Broadcom Corporations | Transmitting multiple adaptive bit rate (ABR) segment streams on a shared frequency |
| US9544623B2 (en) * | 2013-07-08 | 2017-01-10 | The Trustees Of Princeton University | Quota aware video adaptation |
-
2016
- 2016-05-06 CN CN201610298248.XA patent/CN105979274B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103069492A (en) * | 2010-06-18 | 2013-04-24 | 三星电子株式会社 | Storage file format for multimedia streaming file, and storage method and client apparatus using the same |
| CN102186072A (en) * | 2011-04-20 | 2011-09-14 | 上海交通大学 | Optimized transmission method of multi-rate multicast communication for scalable video stream |
| CN103733589A (en) * | 2011-08-09 | 2014-04-16 | 阿尔卡特朗讯公司 | Method for streaming video content, edge node and client entity realizing such a method |
| CN103428107A (en) * | 2012-05-14 | 2013-12-04 | 中国科学院声学研究所 | Self-adaptive bitstream switching method and system based on cache underflow probability estimation |
| CN105068755A (en) * | 2015-07-08 | 2015-11-18 | 南京邮电大学 | Data duplicate storage method facing cloud computing content distribution network |
| CN105007541A (en) * | 2015-07-29 | 2015-10-28 | 上海交通大学 | Scalable video stream dynamic multi-rate multicast optimal transmission method |
Non-Patent Citations (2)
| Title |
|---|
| Distributed Robust Optimization for Scalable Video Multirate Multicast Over Wireless Networks;Chenglin Li，, Hongkai Xiong;《IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY》;20120630;第22卷(第6期);全文 |
| Optimal Transcoding and Caching for Adaptive Streaming in Media Cloud:an Analytical Approach;Yichao Jin et al;《IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY》;20151231;第25卷(第12期);全文 |
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