CN104683318A - Edge streaming media server caching selection method and edge streaming media server caching selection system - Google Patents
Edge streaming media server caching selection method and edge streaming media server caching selection system Download PDFInfo
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- CN104683318A CN104683318A CN201310643321.9A CN201310643321A CN104683318A CN 104683318 A CN104683318 A CN 104683318A CN 201310643321 A CN201310643321 A CN 201310643321A CN 104683318 A CN104683318 A CN 104683318A
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- 238000010187 selection method Methods 0.000 title claims abstract description 5
- 238000000034 method Methods 0.000 claims description 14
- 230000000694 effects Effects 0.000 claims description 13
- 238000004364 calculation method Methods 0.000 claims description 8
- 238000004220 aggregation Methods 0.000 claims description 6
- 230000002776 aggregation Effects 0.000 claims description 6
- 230000004931 aggregating effect Effects 0.000 claims description 3
- 238000004422 calculation algorithm Methods 0.000 description 3
- IXKSXJFAGXLQOQ-XISFHERQSA-N WHWLQLKPGQPMY Chemical compound C([C@@H](C(=O)N[C@@H](CC=1C2=CC=CC=C2NC=1)C(=O)N[C@@H](CC(C)C)C(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CC(C)C)C(=O)N1CCC[C@H]1C(=O)NCC(=O)N[C@@H](CCC(N)=O)C(=O)N[C@@H](CC(O)=O)C(=O)N1CCC[C@H]1C(=O)N[C@@H](CCSC)C(=O)N[C@@H](CC=1C=CC(O)=CC=1)C(O)=O)NC(=O)[C@@H](N)CC=1C2=CC=CC=C2NC=1)C1=CNC=N1 IXKSXJFAGXLQOQ-XISFHERQSA-N 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
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- 238000011156 evaluation Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
- H04L65/60—Network streaming of media packets
- H04L65/65—Network streaming protocols, e.g. real-time transport protocol [RTP] or real-time control protocol [RTCP]
-
- 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
- H04N21/23106—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion involving caching operations
-
- 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
- H04N21/258—Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data
- H04N21/25866—Management of end-user data
-
- 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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- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Databases & Information Systems (AREA)
- Computer Graphics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
Abstract
The invention relates to an edge streaming media server caching selection method, which includes the following steps: a plurality of users are grouped into a plurality of user classes according to the respective preferences of the users; the statistics of the intensity of each user class and the preferences of each user class for movies are collected; the intensity of each user class is the sum of the intensities of all the users in the user class, while the intensities of the users are the different influences of the users on the caching decision-making of a provider; according to the preference degree of each user class for the movies and the intensity of each user class, the utilities of the movies are calculated; the movies with the relatively greater utility values are chosen to be deployed into the cache space of an edge streaming media server.
Description
Technical Field
The present invention relates to the field of network communications, and in particular, to a method and a system for selecting a cache of an edge streaming media server.
Background
In order to solve the performance bottleneck problem of the C/S architecture streaming media system and reduce the operation cost, a Content Delivery Network (CDN) is widely used. CDNs place a large number of edge cache servers at the edge of the network. The content cached by the above-mentioned two-way cache can directly serve the request of the user on demand, thereby avoiding the data throughput between the user and the backbone network and achieving the purposes of reducing the data transmission delay, smoothly transmitting the fluctuation and reducing the backbone network flow.
For services such as digital interactive television and the like, streaming servers are also deployed in each service area at the edge of the network. The streaming server is located at an intermediate position between the user and the CDN, and the roles of the streaming server include: and (4) proxying the on-demand request of the user, acquiring video data from the CDN, streaming and processing the video data into a format supported by the IP-QAM, and pushing the video data to the user. The streaming server is usually very close to the user, and in order to fully utilize the advantage, the streaming server often has a proxy cache function, stores the once-obtained CDN video file, directly serves the subsequent same on-demand request, further improves the quality of service for the user, and reduces the load of the CDN.
Since video files are usually large in size, both CDN edge cache servers and streaming servers that support proxy cache functionality face pressure on storage capacity. Therefore, a crucial problem is how to reasonably select cache deployment content of the cache server, and effectively utilize the limited storage space of the cache server, so as to fully play the role of cache and improve the overall service performance.
Disclosure of Invention
The invention aims to overcome the defect that cache deployment content of a cache server cannot be reasonably selected in the prior art, and provides a method and a system for selecting an edge streaming media server cache.
In order to achieve the above object, the present invention provides a method for selecting a cache of an edge streaming media server, including:
step 1), aggregating a plurality of users into a plurality of user classes according to respective preferences of the users;
step 2), counting the intensity of each user class obtained in the step 1) and the preference of each user class to the film; the intensity of the user class is the sum of the intensities of all users in the user class, and the user intensities are different influences of the users on caching decisions of the provider;
step 3), calculating the effectiveness of the film according to the preference degree of the film to each user class and the intensity of each user class;
and 4) selecting a film with a larger utility value to be deployed in a cache space of the edge streaming media server.
In the above technical solution, the step 1) includes:
step 1-1), defining the preference of a user for a certain film according to the watching time and watching times of the user for the film;
step 1-2), adding labels to the films according to film attributes, and dividing the films into film classes according to the labels;
step 1-3), obtaining the preference value of a user to a film class to which a certain film belongs according to the preference of the user to the film;
and 1-4) clustering the users according to the preference of the users to each film class to obtain a plurality of user classes.
In the above technical solution, the step 2) includes:
step 2-1), calculating the activity degree of the user according to the frequency degree of the user to execute the on-demand operation and the watching time of the user;
step 2-2), setting the service level of the user;
step 2-3), calculating the user intensity according to the activity degree and the service level of the user;
step 2-4), calculating the user type intensity according to the user intensity;
step 2-5), in a certain user class, quantifying the recent activity degree of the user;
step 2-6), the user activity degree obtained in the step 2-5) is taken as a weight, and the preference of the user class to a certain film is measured.
In the above technical solution, in the step 3), the utility of the movie is calculated in the following manner: and taking the user class strength as a weight, and carrying out weighted sum on the preference value of each user class to the film.
The invention also provides a system for selecting the cache of the edge streaming media server, which comprises the following steps: the system comprises a user aggregation module, a user intensity and user preference generation module, a film utility calculation module and a deployment module; wherein,
the user aggregation module aggregates a plurality of users into a plurality of user classes according to respective preferences of the users;
the user type intensity and user type preference generation module counts the intensity of each user type obtained by the user type combination module and the preference of each user type to the film; the intensity of the user class is the sum of the intensities of all users in the user class, and the user intensities are different influences of the users on caching decisions of the provider;
the film utility calculation module calculates the utility of the film according to the preference degree of the film to each user class and the intensity of each user class;
and the deployment module selects the film with larger utility value to deploy in the cache space of the edge streaming media server.
The invention has the advantages that:
according to the method, the user preference in the region is obtained more accurately by using a clustering and recommending algorithm and is used as a cache deployment basis, so that the accuracy of judgment is improved.
Drawings
Fig. 1 is a flowchart of an edge streaming media server cache selection method according to the present invention.
Detailed Description
The invention will now be further described with reference to the accompanying drawings.
In the present application, an edge cache server and a streaming server in the CDN are collectively referred to as an edge streaming server.
Referring to fig. 1, the method of the present invention comprises:
step 1), aggregating a plurality of users into a plurality of user classes according to respective preferences of the users.
In order to implement differentiated services in the present application, it is necessary to discover the preference of each user from the user's on-demand history. However, the on-demand behavior of a single user individual has limited information, so different users should be gathered into several user classes according to their preferences for each movie, and then the importance of each movie is analyzed for each user class by using a collaborative filtering technique.
The method specifically comprises the following steps:
step 1-1), first, defining the preference of the user u for the movie v as:
wherein,Nu，Tuand respectively representing the video-on-demand times and the video viewing time of the user u to v and the total video-on-demand times and the video viewing time of the user u in a period of time.
Preference of user u for movie vTwo-dimensional vector forming user and preference valuesThe missing items (i.e. user u has not watched a certain film) are zeroed or predicted by SVD model.
Step 1-2), generating film classes. And selecting a plurality of film attributes to add labels to the film objects, wherein the selectable label attributes comprise subject matters, showing time, related characters and the like. The films sharing the label value are classified into one film class, the same film can enter a plurality of film classes, and accurate and various classification labels are the basis of user clustering.
Step 1-3), obtaining the preference value of the user to the film class to which the film belongs according to the preference of the user to a certain film.
The user's preference for a certain film category is the sum of the preferences for all films of that category.
Suppose that the preference value of user u for a certain tag t is:the user's preference vector may be defined as <math>
<mrow>
<msub>
<mi>P</mi>
<mi>u</mi>
</msub>
<mo>=</mo>
<mrow>
<mo>(</mo>
<msubsup>
<mi>ρ</mi>
<mi>u</mi>
<mn>1</mn>
</msubsup>
<mo>,</mo>
<msubsup>
<mi>ρ</mi>
<mi>u</mi>
<mn>2</mn>
</msubsup>
<mo>,</mo>
<mo>·</mo>
<mo>·</mo>
<mo>·</mo>
<mo>,</mo>
<msubsup>
<mi>ρ</mi>
<mi>u</mi>
<mi>t</mi>
</msubsup>
<mo>,</mo>
<mo>·</mo>
<mo>·</mo>
<mo>·</mo>
<mo>)</mo>
</mrow>
<mo>.</mo>
</mrow>
</math>
Step 1-4), and finally, clustering the users by using a K-Means algorithm according to the preference of the users to each film class to obtain a plurality of user classes.
Step 2), counting the intensity of each user class and the preference of the user class to the film.
The different impact that a user has on a provider's caching decisions is called user strength. The user intensity is defined by the higher and more active the user is at the higher service level, the greater its intensity. The user classes have different numbers and importance, and also present different importance, which is called user class strength, and is the sum of the user strengths in the user classes. The active degree of the user is measured by two factors, namely the frequency degree of the user for performing the on-demand operation and the watching time of the user, and is the weighted sum of the frequency degree and the watching time of the user; the user service level depends on the non-technical policy of the service provider and is an important basis for allocating service resources, and more important users have higher user level values.
The preference of a user class to a certain movie is defined as the weighted sum of the preferences of the users in the class to the movie, and the user activity degree is taken as a weight.
The method specifically comprises the following steps:
step 2-1), calculating the activity degree of the user.
The user's activity level can be measured by two factors, the frequency of the user performing the on-demand operation and the viewing time of the user.
Wherein N isu、Tu、NU、TURespectively representing the number of requesting programs and the viewing time of a user U and the total number of requesting programs and the viewing time of a user set U in a period of time, wherein the alpha factor belongs to a real number interval [0,1 ]]For regulating the phase of two factorsAnd (4) the weight.
Step 2-2), setting the service level of the user. The user service level depends on the non-technical policy of the service provider and is an important basis for allocating service resources. Subscribers can be simply classified into a member subscriber UM and a general subscriber UN.
Step 2-3), calculating the user intensity.
The strength of user u is defined as:
where γ is used to distinguish between ordinary users and member users, β itself has no special meaning, and β is added only to avoid the term being zero.
The user intensity can be normalized:
through simulation evaluation, when alpha involved in the step 2-1) and beta and gamma in the step are respectively 0.4,1 and 128, the method has high cache hit rate.
Step 2-4), calculating the user class strength.
The intensity of the user class is the sum of the intensities of all users in the user class, namely the intensity of the user class c is defined as
Step 2-5), in each user class c, quantifying the recent activity degree of the user:
wherein, u represents any user in the user class c.
Step 2-6), taking the user activity degree obtained in step 2-5) as a weight, and measuring the preference of the user class c on the movie v:
and 3) calculating the utility of the film according to the preference degree of each user class of each film obtained by calculation in the step 2) and the intensity of each user class.
The utility of a movie is defined as the weighted sum of the preference values of the various user classes for the movie, weighted by the user class strength. The calculation formula is as follows:
and 4), selecting a film with a larger utility value, and deploying in a limited cache space.
The invention also provides a cache selection system of the edge streaming media server corresponding to the selection method, which comprises the following steps: the system comprises a user aggregation module, a user intensity and user preference generation module, a film utility calculation module and a deployment module; wherein,
the user aggregation module aggregates a plurality of users into a plurality of user classes according to respective preferences of the users;
the user type intensity and user type preference generation module counts the intensity of each user type obtained by the user type combination module and the preference of each user type to the film; the intensity of the user class is the sum of the intensities of all users in the user class, and the user intensities are different influences of the users on caching decisions of the provider;
the film utility calculation module calculates the utility of the film according to the preference degree of the film to each user class and the intensity of each user class;
and the deployment module selects the film with larger utility value to deploy in the cache space of the edge streaming media server.
The method and the system of the invention can more accurately obtain the user preference of the region by utilizing the clustering and recommending algorithm, and the preference is used as a cache deployment basis, thereby increasing the accuracy of judgment.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (5)
1. A cache selection method for an edge streaming media server comprises the following steps:
step 1), aggregating a plurality of users into a plurality of user classes according to respective preferences of the users;
step 2), counting the intensity of each user class obtained in the step 1) and the preference of each user class to the film; the intensity of the user class is the sum of the intensities of all users in the user class, and the user intensities are different influences of the users on caching decisions of the provider;
step 3), calculating the effectiveness of the film according to the preference degree of the film to each user class and the intensity of each user class;
and 4) selecting a film with a larger utility value to be deployed in a cache space of the edge streaming media server.
2. The method for selecting the cache of the edge streaming media server according to claim 1, wherein the step 1) comprises:
step 1-1), defining the preference of a user for a certain film according to the watching time and watching times of the user for the film;
step 1-2), adding labels to the films according to film attributes, and dividing the films into film classes according to the labels;
step 1-3), obtaining the preference value of a user to a film class to which a certain film belongs according to the preference of the user to the film;
and 1-4) clustering the users according to the preference of the users to each film class to obtain a plurality of user classes.
3. The method for selecting the cache of the edge streaming media server according to claim 1, wherein the step 2) comprises:
step 2-1), calculating the activity degree of the user according to the frequency degree of the user to execute the on-demand operation and the watching time of the user;
step 2-2), setting the service level of the user;
step 2-3), calculating the user intensity according to the activity degree and the service level of the user;
step 2-4), calculating the user type intensity according to the user intensity;
step 2-5), in a certain user class, quantifying the recent activity degree of the user;
step 2-6), the user activity degree obtained in the step 2-5) is taken as a weight, and the preference of the user class to a certain film is measured.
4. The method for selecting the cache of the edge streaming media server according to claim 1, wherein in the step 3), the utility of the movie is calculated by: and taking the user class strength as a weight, and carrying out weighted sum on the preference value of each user class to the film.
5. An edge streaming server cache selection system, comprising: the system comprises a user aggregation module, a user intensity and user preference generation module, a film utility calculation module and a deployment module; wherein,
the user aggregation module aggregates a plurality of users into a plurality of user classes according to respective preferences of the users;
the user type intensity and user type preference generation module counts the intensity of each user type obtained by the user type combination module and the preference of each user type to the film; the intensity of the user class is the sum of the intensities of all users in the user class, and the user intensities are different influences of the users on caching decisions of the provider;
the film utility calculation module calculates the utility of the film according to the preference degree of the film to each user class and the intensity of each user class;
and the deployment module selects the film with larger utility value to deploy in the cache space of the edge streaming media server.
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