CN116916054B - Digital media content distribution system based on cloud broadcasting control - Google Patents
Digital media content distribution system based on cloud broadcasting control Download PDFInfo
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- 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
- H04N21/231—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion
- H04N21/23103—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion using load balancing strategies, e.g. by placing or distributing content on different disks, different memories or different servers
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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
- H04N21/23—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
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- 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
- 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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- H—ELECTRICITY
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- 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
- H04N21/239—Interfacing the upstream path of the transmission network, e.g. prioritizing client content requests
- H04N21/2393—Interfacing the upstream path of the transmission network, e.g. prioritizing client content requests involving handling client requests
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- 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
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Abstract
The invention relates to the technical field of digital content management, in particular to a digital media content distribution system based on cloud broadcasting control. The system comprises: the system comprises a cloud storage part, a transcoding part, a distribution network, a content distribution part and a user side; the cloud storage part stores original media data, and each original media data is stored in an independent storage space; the transcoding part is configured to transcode the original media data corresponding to the content request instruction; the distribution network consists of nodes and network connection; the content distribution section, in response to the content request instruction, for each type of content request instruction, causes each package data to be transmitted to a user terminal corresponding to one target address. The invention realizes high-efficiency digital media content distribution by utilizing the technologies of path planning, dynamic adaptive transcoding, cloud storage and the like, and optimizes storage utilization, transmission speed and viewing experience.
Description
Technical Field
The invention belongs to the technical field of digital content management, and particularly relates to a digital media content distribution system based on cloud broadcasting control.
Background
With the increasing proliferation of digital media content and the diversification of user needs, the development of digital media content distribution systems is becoming increasingly interesting. These systems aim to efficiently distribute media content to users to meet the needs of different users. However, in the conventional digital media content distribution system, there are some problems such as challenges in terms of storage efficiency, content distribution speed, and resolution adaptability.
Conventional digital media content distribution systems use centralized storage and distribution approaches, which may result in inefficient utilization of storage resources. For example, media content requested by each user needs to be obtained from a centralized server, which can result in server overload, affecting content distribution speed. In addition, the equipment and network conditions of the user are different, and the traditional system cannot dynamically adapt according to the equipment and network conditions of the user, so that the user can not watch the media content smoothly under different resolutions.
In the current state of the art, some approaches have emerged that attempt to address these issues. For example, some systems introduce a cloud storage-based architecture to store media content at the cloud to increase the utilization of storage resources. However, these systems still face the problem of slow content distribution because the transmission and distribution of content by a centralized server is still required. In addition, some systems attempt to accommodate different devices and resolutions by transcoding media content. However, these systems may suffer from slow transcoding speeds and high storage overhead when processing large-scale media content.
Another problem is that existing digital media content distribution systems are not flexible enough to accommodate user needs. Users may wish to view media content on different devices, while existing systems have limitations in accommodating different device and network conditions. This may lead to a user having a stuck or poor image quality while viewing the media content, affecting the user experience.
In view of the foregoing, there are several challenges in the art of digital media content distribution, which remain to be addressed. Traditional centralized storage and distribution methods may result in waste of storage resources and reduction of content distribution speed, and existing adaptive transcoding methods may face problems of slow transcoding speed and high storage overhead. In addition, the existing system is not flexible enough to adapt to different devices and resolutions, and the viewing experience of the user is affected.
Disclosure of Invention
The invention mainly aims to provide a digital media content distribution system based on cloud broadcasting control.
In order to solve the problems, the technical scheme of the invention is realized as follows:
a digital media content distribution system based on cloud broadcast control, the system comprising: the system comprises a cloud storage part, a transcoding part, a distribution network, a content distribution part and a user side; the cloud storage part stores original media Volume data, each original media data stored in a separate storage space of the size of the original media data stored thereinThe multiple of which, wherein,equal to the number of clients,for setting values, responding to content request instructions from a user side each time, classifying the same content request instructions, and for each type of content request instructions, copying corresponding original media data in the content request instructions in a storage space by a cloud storage partParts by weight of the components, wherein,the number of the same content request instructions in the content request instructions for the class; the transcoding part is configured to transcode the original media data corresponding to the content request instruction to generate each original media dataMedia data of different formats and resolutions; the distribution network consists of nodes and network connections, each node is connected with other nodes in a set range through the network connections, each node consists of a user side and a transfer station, the distribution network comprisesA plurality of distribution inlets; the content distributing part responds to the content request instruction, obtains the media data of the corresponding original media data from the cloud storage part aiming at each type of content request instruction, packages the media data corresponding to each original media data and then obtains Each packed data includesMedia data, a target address is set for each package data, each target address corresponds to a user end for sending the content request instruction, and the package data is processed by the methodIn the distribution inlets, screen outA plurality of distribution inlets forThe distribution entrance is the initial node toAnd the target addresses are termination nodes, and a distribution path is planned in a distribution network for each packed data, so that each packed data is sent to a user end corresponding to one target address.
Further, the content distribution part only distributes content to the package data corresponding to one type of content request instruction at the same time.
Further, the system further includes a content management part configured to manage the original media data in the cloud storage part, and specifically includes: deleting, replacing and modifying the original media data; adding new original media data in the cloud storage part, and distributing storage space for the original media data.
Further, the method for planning a distribution path in a distribution network for each packaged data by the content distribution section includes: randomly selecting one packed data, taking a distribution inlet of the packed data as a starting node, taking a target address as a termination node, and carrying out path planning in a distribution network, so that the number of nodes of paths of the packed data from the starting node to the termination node is smaller than a set first threshold value, and the path length of the packed data from the starting node to the termination node is smaller than a set second threshold value, wherein the paths are taken as distribution paths of the packed data; and deleting the network connection corresponding to the distribution path in the distribution network, randomly selecting one from the rest packed data, planning the path, and the like until the path planning of all the packed data is completed.
Further, the method for randomly selecting a package data, taking a distribution entry of the package data as a start node, taking a target address as a termination node, and performing path planning in a distribution network comprises the following steps: defining a topology network map of a distribution network asWhereinA set of nodes is represented and,representing a set of edges; each nodeRepresenting a node, each edgeRepresenting nodesTo the nodeIs connected with the network; definition matrixWhereinRepresenting slave nodesTo the nodeIs equal to the weight of the slave nodeTo the nodeIs a length of the spatial distance of (2); initializing a set of particlesEach particle represents a path planning scheme in which the number of nodes of the path taken from the start node to the end node is less than a set first threshold, the path length taken by the packed data from the start node to the end node is less than a set second threshold,is a set value, and is an integer greater than 10; each particle isComprising a matrix of pathsWhereinIndicating particlesSlave nodeTo the nodeIs equal to the nodeThe inverse of the network traffic; for each particleCalculate its path fitness The method comprises the steps of carrying out a first treatment on the surface of the For each grainSonUpdating the individual optimal solutionUpdate its speedThe method comprises the steps of carrying out a first treatment on the surface of the According to the updated speedUpdating particlesPath matrix of (a)The method comprises the steps of carrying out a first treatment on the surface of the Selecting a path matrixSo thatReaching a maximum value; selecting a set of path matrices with highest fitness from individual optimal solutions of all particlesAs a population optimal solution; outputting a population optimal solutionThe most optimal path planning scheme.
Further, for each particleThe path fitness is calculated using the following formula：
;
Wherein,is one edge in the topology network graph,is a particleThe path weight on that side,is a weight;is a particleIn the represented path planning scheme, the number of nodes of the path passing from the start node to the end node,is the path length traversed from the originating node to the terminating node.
Further, for each particleThe speed is updated using the following formula:
；
wherein,is the weight of the inertia, which is the weight of the inertia,andall are acceleration coefficients, the value range is 0.25 to 0.4,andall are taken as [0,1 ]]A function of the random number in between,is the path weight in the individual optimal solution,the speed of the update.
Further, when receiving the packaged data distributed by the content distribution part through the distribution network, the user side and the transfer station stop distributing the packaged data if the target address of the packaged data is self, otherwise, forward the packaged data to the user side or the transfer station corresponding to the next node according to the distribution path.
Further, the transcoding portion transcodes the original media data corresponding to the content request command to generate each original media dataThe method for media data of different formats and resolutions includes: and transcoding each frame of image of the original media data with different resolutions to obtain transcoded media data of the original media data with different resolutions, and generating the transcoded media data into media data with corresponding formats.
Further, the method for transcoding each frame image of the original media data with a corresponding different resolution includes: performing wavelet decomposition on each frame of image to obtain a plurality of wavelet components; passing each wavelet component through a multiplierObtaining a plurality of filtered components;the value is equal to the ratio of the resolution of the image obtained by transcoding to the original resolution of the image; reconstructing all the filtered components into an image, completing the transcoding of each frame of image of the original media data with different resolutions, and dividing the transcoded imageResolution of the original imageMultiple times.
The digital media content distribution system based on cloud broadcasting control has the following beneficial effects: firstly, the invention realizes the distributed storage of the media content by introducing the cloud storage part, thereby effectively improving the utilization rate of storage resources. Each original media data is stored in an independent storage space, so that the storage redundancy is greatly reduced, and the storage space is saved. Compared with the traditional centralized storage, the distributed storage mode of the cloud storage part can better meet the storage requirement of large-scale media content, and the storage cost is reduced.
Secondly, by constructing the distribution network and the content distribution part, the present patent achieves a significant improvement in the content distribution speed. The nodes of the distribution network form an efficient distribution network for delivering media content to the clients via a plurality of distribution portals and distribution paths. Compared with the traditional centralized distribution mode, the distribution network realizes the parallel distribution of the content, greatly reduces the bottleneck of content transmission and improves the content distribution speed.
Meanwhile, the dynamic adaptive transcoding mechanism provided by the invention has important significance for improving user experience. By transcoding each frame of image at a different resolution, a more adaptive content viewing experience is provided depending on the user device and network conditions. Whatever equipment and network conditions are used by the user, the system can dynamically adapt to transcoding according to the user demands, so that the user can smoothly watch media contents under different conditions, and the problems of poor image quality, blocking and the like in the traditional transcoding mode are solved.
Drawings
Fig. 1 is a schematic system architecture diagram of a digital media content distribution system based on cloud broadcasting control according to an embodiment of the present invention.
Detailed Description
The digital media content distribution system based on cloud broadcasting control is characterized in that the high-efficiency distribution of media content and the optimized viewing experience are realized through key technologies such as cloud storage, distribution network, dynamic adaptive transcoding and the like. Through the distributed storage and distribution network, the utilization rate of storage resources and the transmission speed of content are improved. The dynamic adaptive transcoding mechanism ensures that users can smoothly watch adaptively transcoded media content under different equipment and network conditions. The path planning method further optimizes the distribution efficiency.
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
The following will describe in detail.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein.
Example 1: referring to fig. 1, a digital media content distribution system based on cloud broadcasting control, the system comprising: the system comprises a cloud storage part, a transcoding part, a distribution network, a content distribution part and a user side; the cloud storage part stores original media data, each original media data is stored in a separate storage space, and the size of the storage space is the size of the original media data stored thereinThe multiple of which, wherein,equal to the user sideThe number of the pieces of the plastic material,for setting values, responding to content request instructions from a user side each time, classifying the same content request instructions, and for each type of content request instructions, copying corresponding original media data in the content request instructions in a storage space by a cloud storage partParts by weight of the components, wherein,the number of the same content request instructions in the content request instructions for the class; the transcoding part is configured to transcode the original media data corresponding to the content request instruction to generate each original media dataMedia data of different formats and resolutions; the distribution network consists of nodes and network connections, each node is connected with other nodes in a set range through the network connections, each node consists of a user side and a transfer station, the distribution network comprises A plurality of distribution inlets; the content distributing part responds to the content request instruction, obtains the media data of the corresponding original media data from the cloud storage part aiming at each type of content request instruction, packages the media data corresponding to each original media data and then obtainsEach packed data includesMedia data, a target address is set for each package data, each target address corresponds to a user end for sending the content request instruction, and the package data is processed by the methodIn the distribution inlets, screen outA plurality of distribution inlets forThe distribution entrance is the initial node toAnd the target addresses are termination nodes, and a distribution path is planned in a distribution network for each packed data, so that each packed data is sent to a user end corresponding to one target address.
Specifically, the cloud storage section: this module is used to store the raw media data. The difference is that each original media data is stored in an independent storage space, and the size of the storage space is m×n times the size of the original media data, where N is equal to the number of clients. This approach helps to improve storage and retrieval efficiency and to provide personalized content request services for different users. And when the user side sends the content request instruction each time, the cloud storage part copies X parts of corresponding original media data in the storage space according to the category of the content request instruction, wherein X is the number of the same content request instruction in the category of the content request instruction. This design helps to increase the content response speed.
Transcoding part: this module is responsible for transcoding the original media data corresponding to the content request instruction, generating M different formats and resolutions of media data for each original media data. This transcoding strategy allows different users to select the most appropriate media format and resolution depending on their device and network conditions, providing a better user experience.
Distribution network: the distribution network is composed of nodes and network connections, wherein each node is composed of a user terminal and a transfer station. Each node is connected with other nodes in a set range through network connection to form a network topology. Unlike conventional centralized distribution, this distribution network has N distribution portals, allowing content distribution from multiple sources simultaneously. Such a distributed architecture helps to alleviate network congestion and improve distribution efficiency.
Content distribution section: this module obtains the corresponding media data from the cloud storage section according to the content request instruction and packages it. For each original media data, classifying according to the content request instruction, obtaining X packed data, wherein each packed data contains M media data. Each packet data is assigned a destination address corresponding to the client that sent the content request command. The packaged data is then distributed from the originating node to the corresponding target client by path planning in the distribution network.
The prior art often employs a centralized media distribution approach, whereas the distributed distribution network of the present invention and transcoding strategies customized according to user requests. Through storing the media data in the independent storage space, the multi-entry design of the distribution network and the personalized transcoding scheme, the system can better meet the requirements of different users, improve the content distribution efficiency, reduce the network congestion and provide better user experience. These innovations help improve the scalability, efficiency, and adaptability of media content distribution.
Path planning: the invention realizes the optimal content distribution path planning through a method for randomly selecting paths, and the set node quantity and path length threshold value. The technical scheme fully considers the complexity of the distribution network and ensures the efficient transmission of the content in the network. By gradually selecting the distribution path and deleting the related network connection, the system can avoid network congestion and transmission delay in the content distribution process, thereby effectively improving the content distribution efficiency and optimizing the user viewing experience.
Dynamically adapting transcoding: the transcoding scheme of the invention adopts multiple complex wavelet decomposition and reconstruction processes, and carries out adaptive transcoding according to different resolution requirements, so that each frame of image can obtain high-quality performance under different resolutions. The technical scheme not only solves the problems of blurring and blocking of image quality possibly occurring in the traditional transcoding mode, but also can realize dynamic transcoding adaptation according to the conditions of user equipment and network, ensures that users can smoothly watch media content under various conditions, and improves user experience.
Cloud storage part: the cloud storage scheme of the invention adopts a distributed storage mode to store each original media data in an independent storage space. The technical scheme not only avoids the redundancy phenomenon in the traditional centralized storage, but also effectively improves the utilization rate of storage resources. The content requested by each user can be acquired from the corresponding storage space, so that the load of the server is greatly reduced, and the content acquisition speed is improved. Meanwhile, the dynamic allocation of the storage space also provides convenience for the expansibility and maintainability of the system.
And the content distribution part only distributes the content of the packed data corresponding to one type of content request instruction at the same time.
Specifically, because different processing modes, such as different transcoding parameters, distribution paths and the like, may be required for each type of content request instruction, system resources can be fully utilized by independently processing one type of instruction, and resource waste caused by simultaneous processing of multiple types of instructions is avoided.
Only one type of content request instruction is processed at the same time, so that competition and conflict in the system can be reduced. Processing multiple different types of requests simultaneously may result in resource contention, affecting system stability and performance.
The system further comprises a content management part configured to manage the original media data in the cloud storage part, and specifically comprises: deleting, replacing and modifying the original media data; adding new original media data in the cloud storage part, and distributing storage space for the original media data.
Specifically, deletion, substitution, and modification: the content management section allows an administrator to delete, replace, and modify original media data in the cloud storage section. This allows the system to update and maintain existing media content as desired. This dynamic management capability makes the system more flexible and adaptable to changes than conventional distribution systems.
Adding new original media data: the content management section allows an administrator to add new raw media data to the cloud storage section and allocate appropriate storage space for such data. Thus, the system can add new content at any time, and the richness and diversity of the content library are maintained.
Allocating storage space: the content management section allocates an appropriate storage space for each media data according to the size and the number of the original media data. The on-demand allocation method is helpful for optimizing the utilization of storage resources and avoiding resource waste.
The method of the content distribution part planning a distribution path in a distribution network for each packaged data includes: randomly selecting one packed data, taking a distribution inlet of the packed data as a starting node, taking a target address as a termination node, and carrying out path planning in a distribution network, so that the number of nodes of paths of the packed data from the starting node to the termination node is smaller than a set first threshold value, and the path length of the packed data from the starting node to the termination node is smaller than a set second threshold value, wherein the paths are taken as distribution paths of the packed data; and deleting the network connection corresponding to the distribution path in the distribution network, randomly selecting one from the rest packed data, planning the path, and the like until the path planning of all the packed data is completed.
Specifically, the method uses each package data as a unit to plan the distribution path. First, one of the remaining packed data is randomly selected, and the distribution entry of the packed data is used as a start node and the target address is used as a termination node. Path planning is then performed in the distribution network to ensure that the number of path nodes from the start node to the end node is less than a set first threshold and that the path length is less than a set second threshold. Once a eligible path is found, it is determined as the distribution path for the packed data. Then, the network connection corresponding to the path is deleted from the distribution network to avoid repeated distribution.
The random selection of a package data takes the distribution entry of the package data as the initial node and the target address as the final node, and the path is carried out in the distribution networkThe planning method comprises the following steps: defining a topology network map of a distribution network asWhereinA set of nodes is represented and,representing a set of edges; each nodeRepresenting a node, each edgeRepresenting nodesTo the nodeIs connected with the network; definition matrixWhereinRepresenting slave nodesTo the nodeIs equal to the weight of the slave nodeTo the nodeIs a length of the spatial distance of (2); initializing a set of particlesEach particle represents a path planning scheme in which, from the beginningThe number of nodes of the path taken by the node to the termination node is less than a set first threshold, the path length taken by the packed data from the start node to the termination node is less than a set second threshold,is a set value, and is an integer greater than 10; each particle isComprising a matrix of pathsWhereinIndicating particlesSlave nodeTo the nodeIs equal to the nodeThe inverse of the network traffic; for each particleCalculate its path fitnessThe method comprises the steps of carrying out a first treatment on the surface of the For each particle Updating the individual optimal solutionUpdate its speedThe method comprises the steps of carrying out a first treatment on the surface of the According to the updated speedUpdating particlesPath matrix of (a)The method comprises the steps of carrying out a first treatment on the surface of the Selecting a path matrixSo thatReaching a maximum value; selecting a set of path matrices with highest fitness from individual optimal solutions of all particlesAs a population optimal solution; outputting a population optimal solutionThe most optimal path planning scheme.
Specifically, a distribution network topology map is defined: this step is to abstract the actual distribution network into a graph, where nodes represent locations or devices in the network and edges represent connections between nodes. The essence of this topology is to capture the relationships between nodes, i.e. which nodes can communicate directly through the connection. This information is crucial in path planning, as it defines the paths that can be selected.
Definition of a weight matrix: the weight matrix defines weights between nodes, typically based on spatial distances between the nodes. The essence of this step is to translate the physical distance between nodes into numerical weights, thereby quantifying the connection strength between nodes. In path planning, this weight reflects the transmission cost between nodes, i.e., the "cost" of the path.
Particle swarm initialization and path representation: in the establishment of the distribution path, particles represent a potential solution. The path matrix for each particle represents a path planning scheme in which the values represent "weights" from one node to another. The essence of this step is to create a set of possible solutions as the starting point for the algorithm. Different path planning schemes for particles represent different exploration points of the problem space.
Path fitness calculation and updating: in the establishment of the distribution path, the fitness function measures the quality of the solution. In path planning, the fitness function calculates the "quality" of the path planning scheme based on the specific objective of the problem, such as the length of the path and the number of nodes. The goal of particle swarms is to find solutions with higher fitness. The essence of this step is to quantify the objective of the problem so that a better solution can be found in the solution space.
Path matrix update and optimization: the speed and location update of the particles is a core mechanism for the establishment of the distribution path. In path planning, the speed update takes into account the individual history optima and the group history optima, as well as the weights of the current location and speed. The speed update causes the path planning scheme to move in a more optimal direction. The updating of the path matrix is achieved by speed adjusting the weights. The essence of this step is to gradually bring the particles towards the optimal path through information exchange and iteration.
Selecting a group optimal solution: in the establishment of the distribution path, the group optimal solution is the optimal solution found at present. For path planning, the population optimal solution represents the best path planning scheme in the whole particle swarm. The essence of this step is to keep a globally optimal solution in order to continually find a better solution in the iteration.
For each particleThe path fitness is calculated using the following formula：
;
Wherein,is one edge in the topology network graph,is a particleThe path weight on that side,is a weight;is a particleIn the represented path planning scheme, the number of nodes of the path passing from the start node to the end node,is the path length traversed from the originating node to the terminating node.
Specifically, the path length and the number of nodes are adjusted: in the formulaPart is an adjustment factor that normalizes the path fitness. Wherein the method comprises the steps ofThe number of nodes representing paths taken from the originating node to the terminating node,representing the actual length of the path taken from the originating node to the terminating node. Taking the product of these two factors and taking the logarithm plus one, then taking the reciprocal, in order to ensure that the fitness value is within the appropriate scale. The principle of this is to avoid too large or too small a fitness value while taking into account the complexity (number of nodes) of the path planning and the actual path length.
Comprehensively considering path cost:in part, a comprehensive calculation of path cost, particlesThe products of the path weights and edge weights on all connected edges are summed. The principle of this part is to comprehensively consider the cost of each path to obtain particlesCost conditions in overall path planning.
Comprehensively considering path quality: dividing the comprehensive calculation of the path cost by the adjustment factor of the path length and the number of nodes, i.eThis step combines the path cost with the complexity and length of the path. The principle of this is to comprehensively consider the economical efficiency, feasibility and actual path situation of the path so as to quantify the quality of the path planning scheme represented by each particle.
For each particleThe speed is updated using the following formula:
；
wherein,is the weight of the inertia, which is the weight of the inertia,andall are acceleration coefficients, the value range is 0.25 to 0.4,andall are taken as [0,1 ]]A function of the random number in between,is the path weight in the individual optimal solution,the speed of the update.
Concretely, the inertia term [ ]): the inertia term simulates the historical direction of movement of the particles in the search space. Inertial weightThe extent of influence of this factor is determined. Larger sizeMaintaining a greater speed of the particles in the current direction of movement, but a smaller speed The speed is slowed down. The effect of this part is to keep the particles in the search space going further towards the past direction of motion, helping to cover the space quickly.
Individual history optimal solution) Individual history optimal solution term individual history optimal solution of particlesAnd the current positionIs weighted by the difference in (a). Acceleration coefficientThe influence of the term is controlled, and the term is randomRandomness is introduced to help avoid trapping in locally optimal solutions. The effect of this section is to guide the particle towards a better performing position in its own search history to gradually improve the individual solution.
Group history optimal solution): path fitness of particles by group history optimal solution termWith another random termEdge weightsWeighting is performed. Acceleration coefficientThe impact of this term is controlled, while randomness and edge weights introduce additional information to increase the diversity of the search. The effect of this part is to guide the particles towards the best solution direction of the whole particle population, thus performing a global search.
By integrating the three parts, the speed updating of the particles is a process of comprehensively considering inertia, an individual history optimal solution, a group history optimal solution and randomness. This comprehensive updating mechanism allows the particles to simultaneously maintain historical useful information in the search space, tending to advance toward individual and population optimal solutions, while maintaining some randomness to avoid trapping in the local optimal solutions. Through multiple iterations, the particles gradually adjust the speed and position, and finally a solution of the global optimal solution or a solution close to the global optimal solution is hopeful to be found.
When receiving the packed data distributed by the content distribution part through the distribution network, the user terminal and the transfer station stop distributing the packed data if the target address of the packed data is self, otherwise, the packed data is forwarded to the user terminal or the transfer station corresponding to the next node according to the distribution path.
Specifically, the determination of the target address: in a content distribution system, each package is assigned a destination address that represents the destination point to which the package is to be delivered. When a client or transfer station receives a packet, it first checks the destination address of the packet. This destination address may be a specific node (user side or transfer station) in the system.
Comparison of target address with current node: if the destination address of the received packed data matches the identity of the current node, i.e., the destination address is itself, the system will cease distributing this packed data. This is because the packed data has reached the end point it should have reached, and no further delivery is required. This also avoids repetitive data transfer and processing and improves system efficiency.
Forwarding according to the distribution path: if the destination address of the received packed data is not the current node, the system will continue to deliver the packed data to the next node according to the previously planned distribution path. The distribution path is planned according to the content distribution portion, ensuring that the packaged data can be delivered to the target node along a predetermined path. In this way, the system can gradually transfer data from the source node to the target node, and the effective distribution of the content is realized.
The transcoding part transcodes the original media data corresponding to the content request instruction to generate each original media dataThe method for media data of different formats and resolutions includes: and transcoding each frame of image of the original media data with different resolutions to obtain transcoded media data of the original media data with different resolutions, and generating the transcoded media data into media data with corresponding formats.
Specifically, the transcoding process outlines: transcoding refers to the conversion of raw media data (typically video or audio) from one format or resolution to another to meet the needs of different devices, network conditions, or applications. In this case, the goal of the transcoding portion is to generate a plurality of different resolutions and formats of media data for each original media data.
Resolution transcoding: the transcoding portion transcodes each frame of image of the original media data at a different resolution. This means that each frame of image will be re-encoded to accommodate the display requirements of different resolutions. Lower resolution images are typically suitable for mobile devices or networks where bandwidth is limited, while high resolution is suitable for large screen devices or high speed networks.
Format transcoding: after the transcoded media data of different resolutions is generated, the transcoded portion may further process the transcoded media data in a desired format to generate final media data. Different devices or applications may require different media formats, such as MP4, AVI, FLV, etc. Therefore, the transcoding portion may repackage the transcoded media data into the media data in the target format as desired.
The method for transcoding each frame image of the original media data with different resolutions comprises the following steps: performing wavelet decomposition on each frame of image to obtain a plurality of wavelet components; passing each wavelet component through a multiplierObtaining a plurality of filtered components;the value is equal to the ratio of the resolution of the image obtained by transcoding to the original resolution of the image; reconstructing all the filtered components into an image, completing the transcoding of each frame of image of the original media data with different resolutions, wherein the resolution of the transcoded image is the original imageMultiple times.
In particular, it is assumed that each frame image of the original media data is represented asWhereinIs the coordinates of the image. A higher-dimensional wavelet basis function will be used Performing wavelet decomposition in whichThe scale parameter is represented by a scale parameter,the parameter of the rotation angle is indicated,representing the newly added parameters for adjusting the shape of the feature.
And (3) line direction decomposition: for each line of the image, it is subjected to a two-dimensional wavelet decomposition. By usingAndrepresenting the approximation and detail components, respectively:
；
here, theRepresenting a new high-pass filter function, anParameters interact to adjust the detail information;an integral variable representing the abscissa of the image,an integral variable representing the ordinate of the image.
Column direction decomposition: the approximate components obtained separately for each rowAnd detail componentPerforming two-dimensional wavelet decomposition to obtain new approximate componentsAnd detail component：
；
Repeating the steps, and performing row-column decomposition on the approximate components step by step to obtain approximate and detail components with different frequency resolutions.
Assuming that one-dimensional wavelet components have been obtained(here, the detail component is taken as an example) will be passed through a multiple ofIs processed by the filter of (a). The purpose of the filtering is to extract the characteristic information in different frequency ranges.
A selection filter: for the filtering process, an appropriate filter will be selected for the extraction of the different frequency components. Common options include low pass, high pass, band pass, etc. filters.
The filtering process comprises the following steps: for wavelet componentsWill apply a multiple ofA plurality of filtered components is obtained. Suppose a low pass filter is selectedFor extracting features of lower frequencies. The filtered components are noted as：
；
Wherein,is a coefficient of the low-pass filter.
A plurality of filtered components: by repeating the above steps, a plurality of filter components can be obtained by selecting different filters (low pass, high pass, etc.), each of which extracts characteristic information in a different frequency range.
Assuming that each frame of image has been wavelet decomposed and a number of filtered components are obtained, these components will be recombined at different resolutions to complete transcoding of the original media data.
Selecting a reconstruction filter: during the recombination process, a suitable reconstruction filter needs to be selected for restoring the filtered components to the original image. The selection of the reconstruction filter generally corresponds to the previously selected wavelet basis functions and filters.
The reconstruction process comprises the following steps: for each resolution of the filtered component, an inverse wavelet transform will be applied to reconstruct the original image. Suppose a low-pass reconstruction filter is selectedFor reconstructing the approximation components. The reconstructed image component is noted as ：
；
Wherein,is a filtered component obtained before and is a filtered component,is a coefficient of the low-pass reconstruction filter.
Reconstruction of multiple resolutions: the above steps are repeated for filtered components of different resolutions, which are reconstructed separately into different image components.
Combining the reconstructed images: and superposing all reconstructed image components with different resolutions according to the positions of the original image to generate a final transcoding image.
Through this process, the plurality of filtered components can be recombined into one image, thereby completing transcoding of each frame image of the original media data with a corresponding different resolution. The transcoded image will contain characteristic information at different resolutions, the resolution being that of the original imageMultiple times.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A digital media content distribution system based on cloud broadcasting control, characterized in that the system comprises: the system comprises a cloud storage part, a transcoding part, a distribution network, a content distribution part and a user side; the cloud storage part stores original media data, each original media data is stored in a separate storage space, and the size of the storage space is the size of the original media data stored thereinMultiple of (a) wherein->Equal to the number of clients>For setting values, responding to content request instructions from a user side each time, classifying the same content request instructions, and for each type of content request instructions, copying corresponding original media data in the content request instructions in a storage space by a cloud storage part>Parts of (a) parts of (b)>The number of the same content request instructions in the content request instructions for the class; the transcoding part is configured to transcode the original media data corresponding to the content request instruction to generate +.>Media data of different formats and resolutions; the distribution network consists of nodes and network connection, each node is connected with other nodes in a set range through the network connection, each node consists of a user side and a transfer station, and the distribution network is provided with + >A plurality of distribution inlets; the content distributing part responds to the content request instruction, obtains the media data of the corresponding original media data from the cloud storage part aiming at each type of content request instruction, packages the media data corresponding to each original media data, and obtains ++>Each packed data, each packed dataComprises->Each media data, for each package data set a target address, each target address is correspondent to a user end for sending said type of content request instruction from +.>In the distribution portal, screening out->A distribution portal for->The distribution entry is the starting node, in +.>The target addresses are termination nodes, and a distribution path is planned in a distribution network for each package data, so that each package data is sent to a user end corresponding to one target address;
the method of the content distribution part planning a distribution path in a distribution network for each packaged data includes: randomly selecting one packed data, taking a distribution inlet of the packed data as a starting node, taking a target address as a termination node, and carrying out path planning in a distribution network, so that the number of nodes of paths of the packed data from the starting node to the termination node is smaller than a set first threshold value, and the path length of the packed data from the starting node to the termination node is smaller than a set second threshold value, wherein the paths are taken as distribution paths of the packed data; then deleting the network connection corresponding to the distribution path in the distribution network, randomly selecting one from the rest of the packed data, planning the path, and the like until the path planning of all the packed data is completed;
The method comprises the steps of randomly selecting a package data, taking a distribution inlet of the package data as a starting node, taking a target address as a termination node, and planning a path in a distribution networkThe method comprises the following steps: defining a topology network map of a distribution network asWherein->Representing node set,/->Representing a set of edges; every node->Represents a node, each side +.>Representing node->To node->Is connected with the network; definition matrix->Wherein->Representing slave node->To node->Is equal to the weight of the slave node +.>To node->Is longer than the spatial distance of (a)A degree; initializing a set of particlesEach particle represents a path planning scheme in which the number of nodes of a path taken from a start node to a termination node is less than a set first threshold and the path length taken by packed data from the start node to the termination node is less than a set second threshold>Is a set value, and is an integer greater than 10; every particle->Comprising a path matrix->Wherein->Indicating particle->Slave node->To node->Is equal to the node +.>The inverse of the network traffic; for each particle->Calculate its path fitness +. >The method comprises the steps of carrying out a first treatment on the surface of the For each particle->Update its individual optimal solution->Update its speed +.>The method comprises the steps of carrying out a first treatment on the surface of the According to updated speed->Update particle->Path matrix of->The method comprises the steps of carrying out a first treatment on the surface of the Select Path matrix->Make->Reaching a maximum value; selecting a set of path matrices with highest fitness from the individual optimal solutions of all particles +.>As a population optimal solution; output population optimal solution->The most optimal path planning scheme.
2. The digital media content distribution system based on cloud broadcasting control as claimed in claim 1, wherein said content distribution section performs content distribution only on the package data corresponding to one type of content request instruction at the same time.
3. The digital media content distribution system based on cloud seeding control according to claim 1, wherein the system further comprises a content management section configured to manage the original media data in the cloud storage section, specifically comprising: deleting, replacing and modifying the original media data; adding new original media data in the cloud storage part, and distributing storage space for the original media data.
4. The digital media content distribution system based on cloud seeding control as recited in claim 1, wherein for each particle The path fitness +.>：/>;
Wherein,is an edge in the topology network map, < >>Is particle->Path weight on the edge, +.>Is a weight; />Is particle->The represented path planning scheme includes the number of nodes of the path from the start node to the end node，Is the path length traversed from the originating node to the terminating node.
5. The digital media content distribution system based on cloud seeding control as recited in claim 4, wherein for each particleThe speed is updated using the following formula:the method comprises the steps of carrying out a first treatment on the surface of the Wherein (1)>Is inertial weight, ++>And->All are acceleration coefficients, the value range is 0.25 to 0.4, and the value of the +.>And->All are taken as [0,1 ]]Function of random number between +.>Is the path weight in the individual optimal solution, < +.>The speed of the update.
6. The digital media content distribution system based on cloud broadcasting control as claimed in claim 5, wherein when receiving the packed data distributed by the content distribution part through the distribution network, the user terminal and the transfer station stop distributing the packed data if the destination address of the packed data is self, otherwise, forward the packed data to the user terminal or the transfer station corresponding to the next node according to the distribution path.
7. The digital media content distribution system based on cloud broadcasting control as claimed in claim 1, wherein said transcoding portion transcodes original media data corresponding to the content request command to generate each original media dataThe method for media data of different formats and resolutions includes: and transcoding each frame of image of the original media data with different resolutions to obtain transcoded media data of the original media data with different resolutions, and generating the transcoded media data into media data with corresponding formats.
8. The digital media content distribution system based on cloud broadcasting control as claimed in claim 7, wherein said method of transcoding each frame image of original media data with a corresponding different resolution comprises: performing wavelet decomposition on each frame of image to obtain a plurality of wavelet components; passing each wavelet component through a multiplierObtaining a plurality of filtered components; />The value is equal to the ratio of the resolution of the image obtained by transcoding to the original resolution of the image; reconstructing all the filtered components into an image, and completing the transcoding of each frame of image of the original media data with different resolutions, wherein the resolution of the transcoded image is +_ of the original image >Multiple times.
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