Cache management in a video content distribution network

Patent metadata

Field	Value
Publication number	US-11039176-B2
Application number	US-202016899234-A
Country	US
Kind code	B2
Filing date	Jun 11, 2020
Priority date	Dec 20, 2010
Publication date	Jun 15, 2021
Grant date	Jun 15, 2021

Abstract

Cache management techniques are described for a content distribution network (CDN), for example, a video on demand (VOD) system supporting user requests and delivery of video content. A preferred cache size may be calculated for one or more cache devices in the CDN, for example, based on a maximum cache memory size, a bandwidth availability associated with the CDN, and a title dispersion calculation determined by the user requests within the CDN. After establishing the cache with a set of assets (e.g., video content), an asset replacement algorithm may be executed at one or more cache devices in the CDN. When a determination is made that a new asset should be added to a full cache, a multi-factor comparative analysis may be performed on the assets currently residing in the cache, comparing the popularity and size of assets and combinations of assets, along with other factors to determine which assets should be replaced in the cache device.

First claim

The invention claimed is:

1. An apparatus comprising:
one or more processors; and
memory storing instructions that, when executed by the one or more processors, cause the apparatus to:
determine a first target percentage of content asset requests to be serviced by a cache;
determine a content asset request history associated with the cache;
based on the content asset request history:
determine, for each of a plurality of unique asset titles, a quantity of historical content asset requests corresponding to the unique asset title;
determine, for each of the plurality of unique asset titles, a corresponding percentage of a total number of the historical content asset requests, corresponding to the unique asset title, serviced by the cache;
rank the plurality of unique asset titles, based on the determined percentages, to generate a list of top ranked unique asset titles; and
select, from the list and based on the ranking, a target plurality of the unique asset titles, such that a sum of the percentages for each of the unique asset titles in the target plurality satisfies the first target percentage; and
transfer, from a content library and to the cache, content assets corresponding to the target plurality of the unique asset titles.

2. The apparatus of claim 1 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to:
determine the first target percentage based on a first time of day; and
determine a second target percentage based on a second time of day, wherein the first time of day and the second time of day are different.

3. The apparatus of claim 1 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to:
alter the first target percentage based on a pricing status or an advertising status of the content assets.

4. The apparatus of claim 1 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to:
measure requests for a plurality of content assets at a plurality of cache devices; and
determine, for each cache device of the plurality of cache devices and based on a weighted comparison of the measured requests at the plurality of cache devices, the first target percentage.

5. The apparatus of claim 1 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to:
determine the first target percentage based on:
rankings of the unique asset titles; and
a frequency of access hits.

6. The apparatus of claim 1 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to:
determine the first target percentage based on:
an available bandwidth associated with a content distribution network; and
a size of the cache.

7. The apparatus of claim 1 , wherein the first target percentage is at least 50%.

8. The apparatus of claim 1 , wherein the instructions, when executed by the one or more processors, further cause the apparatus to:
determine the first target percentage of content asset requests by:
determining the first target percentage before selecting the target plurality of the unique asset titles; and

select the target plurality of the unique asset titles by:
iteratively selecting unique asset titles, from the plurality of unique asset titles, until a total percentage, corresponding to the iteratively selected unique asset titles, satisfies the first target percentage.

9. A system comprising:
an apparatus and
a cache;
wherein the apparatus comprises:
one or more processors; and
memory storing instructions that, when executed by the one or more processors, cause the apparatus to:
determine a first target percentage of content asset requests to be serviced by the cache;
determine a content asset request history associated with the cache;
based on the content asset request history:
determine, for each of a plurality of unique asset titles, a quantity of historical content asset requests corresponding to the unique asset title;
determine, for each of the plurality of unique asset titles, a corresponding percentage of a total number of the historical content asset requests, corresponding to the unique asset title, serviced by the cache;
rank the plurality of unique asset titles, based on the determined percentages, to generate a list of top ranked unique asset titles; and
select, from the list and based on the ranking, a target plurality of the unique asset titles, such that a sum of the percentages for each of the unique asset titles in the target plurality satisfies the first target percentage; and
transfer, from a content library and to the cache, content assets corresponding to the target plurality of the unique asset titles.

10. The system of claim 9 , wherein the instructions stored in the memory of the apparatus, when executed by the one or more processors of the apparatus, further cause the apparatus to:
determine the first target percentage based on a first time of day; and
determine a second target percentage based on a second time of day, wherein the first time of day and the second time of day are different.

11. The system of claim 9 , wherein the instructions stored in the memory of the apparatus, when executed by the one or more processors of the apparatus, further cause the apparatus to:
alter the first target percentage based on a pricing status or an advertising status of the content assets.

12. The system of claim 9 , wherein the instructions stored in the memory of the apparatus, when executed by the one or more processors of the apparatus, further cause the apparatus to:
measure requests for a plurality of content assets at a plurality of cache devices; and
determine, for each cache device of the plurality of cache devices, and based on a weighted comparison of the measured requests at the plurality of cache devices, the first target percentage.

13. The system of claim 9 , wherein the instructions stored in the memory of the apparatus, when executed by the one or more processors of the apparatus, further cause the apparatus to:
determine the first target percentage based on:
rankings of the unique asset titles; and
a frequency of access hits.

14. The system of claim 9 , wherein the instructions stored in the memory of the apparatus, when executed by the one or more processors of the apparatus, further cause the apparatus to:
determine the first target percentage based on:
an available bandwidth associated with a content distribution network; and
a size of the cache.

15. The system of claim 9 , wherein the first target percentage is at least 50%.

16. The system of claim 9 , wherein the instructions stored in the memory of the apparatus, when executed by the one or more processors of the apparatus, further cause the apparatus to:
determine the first target percentage of content asset requests by:
determining the first target percentage before selecting the target plurality of the unique asset titles; and

select the target plurality of the unique asset titles by:
iteratively selecting unique asset titles, from the plurality of unique asset titles, until a total percentage, corresponding to the iteratively selected unique asset titles, satisfies the first target percentage.

17. A non-transitory computer-readable medium storing instructions that, when executed, cause:
determining a first target percentage of content asset requests to be serviced by a cache;
determining a content asset request history associated with the cache;
based on the content asse

Assignees

• Comcast Cable Comm Llc

Inventors

• Whyte Volnie
• Garg Amit
• Brown Tom
• Gaydos Robert
• Muehl Mark

Classifications

• G06F2212/263

  Network storage, e.g. SAN or NAS · CPC title

• H04N21/2402

  Monitoring of the downstream path of the transmission network, e.g. bandwidth available (traffic monitoring in data switching networks H04L43/00; monitoring data switching networks utilization H04L43/0876) · CPC title

• G06F12/0871

  Allocation or management of cache space · CPC title

• H04N21/47202

  for requesting content on demand, e.g. video on demand · CPC title

• H04N7/17336

  Handling of requests in head-ends · CPC title