Systems, devices and methods for distributed content pre-fetching in mobile communication networks

• US 9,930,135 B2
• Filed: 12/01/2016
• Issued: 03/27/2018
• Est. Priority Date: 01/29/2015
• Status: Active Grant

• Current Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Original Assignee: Huawei Technologies Co., Ltd. (Huawei Investment & Holding Co., Ltd.)
• Inventors: Senarath, Nimal Gamini, Leroux, Philippe, Stephenne, Alex, Akhavain Mohammadi, Mehdi Arashmid, Callard, Aaron
• Primary Examiner(s): Milord, Marceau
• Application Number:
  US15/365,945
• Publication Number:
  US 20170085670A1
• Time in Patent Office: 481 Days
• Field of Search: 455436, 455437, 455442
• CPC Class Codes: H04L 67/04 specially adapted for terminals or networks with limited capabilities; specially adapted for terminal portability
• CPC Class Codes: H04L 67/52 specially adapted for the location of the user terminal
• CPC Class Codes: H04L 67/5681 Pre-fetching or pre-delivering data based on network characteristics
• CPC Class Codes: H04L 67/63 Routing a service request depending on the request content or context
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/029 Location-based management or tracking services

Abstract

There are disclosed systems, devices, and methods for distributing pre-fetch data. A parent node obtains pre-fetch data comprising at least one of: i) data expected to be of interest to a particular user, pre-fetched by the parent node from at least one data source; and (ii) at least one identifier identifying data expected to be of interest to the particular user, for pre-fetching the identified data at a child node. The parent node selects first and second subsets of the pre-fetch data for transmission, respectively, to first and second child nodes, the selecting based on at least a predicted future location of the particular user and a respective geographic location of the first and second child nodes; and transmits the first and second subsets of the pre-fetch data, respectively, to the first and second child nodes.

Claims

1. A method at a parent node for distributing pre-fetch data to at least two child nodes, the method comprising:

storing a content prediction list identifying data expected to be of interest to a particular user, based on user activity;

synchronizing the content prediction list and a local content prediction list at the client device, based on user activity at the client device;

obtaining, from at least one data source, by way of at least one data network, pre-fetch data comprising data identified in the content prediction list;

selecting a first subset and a second subset of the pre-fetch data for transmission, respectively, to a first child node and a second child node of the at least two child nodes, the selecting based on at least a predicted future location of the particular user and a respective geographic location of the first and second child nodes; and

transmitting the first subset and the second subset of the pre-fetch data, respectively, to the first child node and the second child node by way of the at least one data network.

2. The method of claim 1, comprising receiving transmissions indicative of user activity from the client device, and generating entries of the content prediction list based on the received transmissions.

3. The method of claim 1, wherein synchronizing the content list comprises receiving prediction data from the client device identifying data expected to be of interest to the particular user, and updating the content prediction list based on the received prediction data.

4. The method of claim 1, wherein synchronizing the content list comprises sending prediction data from to client device identifying data expected to be of interest to the particular user, for updating the local content prediction list.

5. The method of claim 1, further comprising:

selecting a desired location as the geographic location of a given one of the first and second child nodes based on at least the predicted future location of the particular user.

6. The method of claim 1, further comprising:

transmitting a request to a device at the desired location to function as the given one of the first and second child nodes.

7. The method of claim 1, further comprising:

determining when previously pre-fetched data is updated at the at least one data source, pre-fetching the updated data and transmitting data to at least one of the child nodes for updating data at the at least one of the child nodes.

8. The method of claim 1, further comprising:

transmitting a request to at least one of the child nodes to pre-fetch the updated data.

9. The method of claim 1, wherein the selecting is based on at least one of:

network transmission characteristics associated with data communication with at least one of the child nodes, a prediction of how soon data will be needed, content quantity, user cost preferences, traffic associated with other users, and data security requirements.

10. The method of claim 9, wherein the network transmission characteristics comprise at least one of:

a data rate, a latency, a capacity, a congestion state, and a cost.

11. The method of claim 1, wherein the at least one data source includes a cache, and the data pre-fetched at the parent node comprises data cached at the at least one data source.

12. The method of claim 1, wherein the synchronizing comprises synchronizing with a content list at a device interconnected with the client device over a local area network.

13. The method of claim 1, wherein the synchronizing comprises updating the local content prediction list based on the content prediction list.

14. The method of claim 1, wherein the synchronizing comprises updating the content prediction list based on the local content prediction list.

15. The method of claim 1, comprising storing content prediction lists at each of a plurality of nodes in a hierarchy, wherein a child node in the hierarchy is closer to the location of the client device than its respective parent node, and the content prediction list at the child node contains only part of the content prediction data at the parent node.

16. The method of claim 1, wherein the local content prediction list is generated locally at the client device.

17. A network node for distributing pre-fetch data, the node comprising:

a network interface for interconnection with at least two child nodes by at least one data network; and

at least one processor in communication with the network interface, the at least one processor configured to;

store a content prediction list identifying data expected to be of interest to a particular user;

synchronize the content prediction list and a local content prediction list at the client device, based on user activity at the device;

obtain, from at least one data source by way of at least one data network pre-fetch data comprising data identified in the content prediction list;

select a first subset and a second subset of the pre-fetch data for transmission, respectively, to a first child node and a second child node of the at least two child nodes, the selecting based on at least a predicted future location of the particular user and a respective geographic location of the first and second child nodes; and

transmit the first subset and the second subset of the pre-fetch data, respectively, to the first child node and the second child node by way of the at least one data network.

18. The network node of claim 17, wherein the at least one processor is configured to generate entries of the content prediction list based on transmissions indicative of user activity received from the client device.

19. The network node of claim 17, wherein the at least one processor is configured to update the content prediction list based on prediction data received from the client device, identifying data expected to be of interest to the particular user.

20. The network node of claim 17, wherein the at least one processor is configured to select a desired location as the geographic location of a given one of the first and second child nodes based on at least the predicted future location of the particular user.

21. The network node of claim 17, wherein the at least one processor is configured to transmit, by way of the network interface, a request to a device at the desired location to function as the given one of the first and second child nodes.

22. The network node of claim 17, wherein the at least one processor is configured to determine when previously pre-fetched data is updated at the at least one data source, pre-fetch the updated data and transmit data to at least one of the child nodes for updating data at the at least one of the child nodes.

23. The network node of claim 22, wherein the at least one processor is configured to transmit a request to at least one of the child nodes to pre-fetch the updated data.

24. The network node of claim 17, wherein the selecting is based on at least one of:

network transmission characteristics associated with data communication with at least one of the child nodes, a prediction of how soon data will be needed, content quantity, user cost preferences, traffic associated with other users, and data security requirements.

25. The network node of claim 24, wherein the network transmission characteristics comprise at least one of:

a data rate, a latency, a capacity, a congestion state, and a cost.

26. The network node of claim 17, wherein the at least one data source includes a cache, and the data pre-fetched at the network node comprises data cached at the at least one data source.

27. The network node of claim 17, wherein the processor is configured to synchronize the content prediction list and the local content prediction list by updating the content prediction list based on the local content prediction list.

28. The network node of claim 17, wherein the processor is configured to synchronize the content prediction list and the local content prediction list by updating the local content prediction list based on the content prediction list.

29. The network node of claim 17, wherein the processor is configured to synchronize the content prediction list with a local content prediction list generated locally at the client device based on user activity.