System and method for proactive resource allocation

• US 9,531,522 B2
• Filed: 09/28/2011
• Issued: 12/27/2016
• Est. Priority Date: 09/28/2010
• Status: Active Grant

• Current Assignee: Ohio State Innovation Foundation (Ohio State University)
• Original Assignee: Ohio State Innovation Foundation (Ohio State University)
• Inventors: El Gamal, Hesham, Tadrous, John, Eryilmaz, Atilla
• Primary Examiner(s): Moore, Ian N
• Assistant Examiner(s): MCCALLUM, LATRESA A
• Application Number:
  US13/876,653
• Publication Number:
  US 20140016575A1
• Time in Patent Office: 1,917 Days
• US Class Current: 1/1
• CPC Class Codes: H04B 7/2656 for structure of frame, burst
• CPC Class Codes: H04L 5/0064 Rate requirement of the data, e.g. scalable bandwidth, data priority
• CPC Class Codes: H04W 16/00 Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
• CPC Class Codes: H04W 28/02 Traffic management, e.g. flow control or congestion control
• CPC Class Codes: H04W 4/00 Services specially adapted for wireless communication networks; Facilities therefor
• CPC Class Codes: H04W 72/0453 Resources in frequency domain, e.g. a carrier in FDMA

Abstract

A system and method for allocating resources in a network is disclosed. The system and method comprises a proactive resource allocation framework in which the predictability of user behavior is exploited to balance the network traffic over time and to reduce the bandwidth required to achieve a given blocking/outage probability. The disclosed proactive resource allocation framework avoids limitations associated with off-peak demand and achieves a significant reduction in the peak to average demand ratio without relying on out of network users. It is based on a model in which smart devices are assumed to predict the arrival of new requests and submit them to the network T time slots in advance. Using tools from large deviation theory, the resulting prediction diversity gain is quantified to establish that the decay rate of the outage event probabilities increases linearly with the prediction duration T.

Claims

1. A computerized method performed by a network server in communication with a mobile network comprising;

(a) collecting from a mobile user device a plurality of prior requests from an individual user for user demand content from said network, said plurality of prior requests initiated by said mobile user device;

(b) analyzing said plurality of prior requests for user demand content collected from said mobile user device with machine learning techniques to build a profile for said individual user;

(c) generating a list of anticipated requests for user demand content from said individual user, said list comprising a deadline for each anticipated request;

(d) for each anticipated request and deadline in said list;

(1) downloading to said mobile user device in advance of said deadline data responsive to said anticipated request;

(2) storing said data in a memory in said mobile user device;

(e) receiving at least one actual request for user demand content from said individual user initiated by said mobile user device, and

(f) in response to said at least one actual request for user demand content from said individual user, presenting at said mobile user device data from said memory response to said actual user request.

2. The computerized method of claim 1 wherein downloading to said mobile user device data responsive to each anticipated request in said list comprises downloading data according to a schedule of deadlines.

3. The computerized method of claim 2 wherein downloading data according to said schedule comprises establishing a timeslot for downloading said data in advance of said deadline for each anticipated request.

4. The computerized method of claim 1 wherein analyzing said plurality of prior requests for user demand content comprises analyzing a plurality of daily user requests.

5. The computerized method of claim 1 wherein downloading to said mobile user device in advance of said deadline data response to said anticipated request comprises downloading said data based on location information for said user device.

6. The computerized method of claim 5 wherein downloading occurs automatically when said location information identifies that said mobile user device is within range of a wireless network.

7. A computerized method performed by a network server in communication with a mobile network comprising:

(a) collecting from a mobile user device a plurality of prior user requests sent from said mobile user device for data from said network;

(b) generating a proactive schedule of anticipated requests for said mobile user device by analyzing said plurality of prior user requests collected from said mobile user device, said proactive schedule comprising a deadline for each anticipated request;

(c) detecting at said mobile user device a node on said network for retrieving data responsive to at least one anticipated request on said proactive schedule;

(d) collecting at said mobile user device location information, said location information identifying whether said mobile user device is in range of a wireless network;

(e) for at least one of said anticipated requests on said proactive schedule;

(1) downloading from a wireless network to said mobile user device in advance of said deadline data responsive to said anticipated request, said downloading automatically occurring when said location information identifies that said mobile user device is in range of said wireless network;

(2) storing said data in a memory in said mobile user device; and

(e)(f) in response to an actual user request for data, presenting at said mobile user device data from said memory responsive to said actual user request.

8. The computerized method of claim 7 wherein downloading data according to said proactive schedule comprises establishing a timeslot for downloading said data in advance of said deadline for each anticipated request.

9. The computerized method of claim 7 wherein generating said proactive schedule of anticipated requests for data by analyzing said plurality of prior user requests comprises analyzing a plurality of prior daily user requests.

10. A computerized method performed by a network server in communication with a mobile network comprising:

(a) collecting from a mobile user device a plurality of prior user requests from an individual user for data from said network, said requests initiated by said mobile user device;

(b) generating a list of anticipated requests for said mobile user device by analyzing said plurality of prior user requests collected from said mobile user device;

(c) generating a proactive schedule for downloading to a cache in said mobile user device data responsive to said anticipated requests according to anticipated arrivals of actual requests for said data;

(d) downloading said data to said cache in accordance with said proactive schedule, said downloading occurring automatically when said mobile user device is within range of a wireless network;

(e) storing said data in said cache;

(f) presenting at said mobile user device data from said cache responsive to said actual user request, and

(g) recommending data from said cache to said individual user, wherein said recommendation is made based upon network condition information and the data available in said cache.

11. The computerized method of claim 10 wherein said proactive schedule comprises expiration times for downloading said data to said cache.

12. The computerized method of claim 10 wherein said proactive schedule comprises deadlines for downloading said data to said cache.

13. The computerized method of claim 10 wherein downloading said data to said cache in accordance with said proactive schedule comprises downloading said data based on location information for said user device.