SYSTEM AND METHOD FOR PROACTIVE RESOURCE ALLOCATION

• US 20140016575A1
• Filed: 09/28/2011
• Published: 01/16/2014
• Est. Priority Date: 09/28/2010
• Status: Active Grant

• Current Assignee: Ohio State Innovation Foundation (Ohio State University)
• Original Assignee: Ohio State University
• Inventors: El Gamal, Hesham, Tadrous, John, Eryilmaz, Atilla
• Granted Patent: US 9,531,522 B2
• Time in Patent Office: Days
• US Class Current: 370/329
• 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 for allocating resources in a network comprising:

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

(b) generating a list of anticipated requests for data by analyzing said plurality of user requests;

(c) for each anticipated request in said list;

(1) downloading to said user device data responsive to said anticipated request;

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

(d) in response to at least one actual user request for data, presenting at said user device data from said memory responsive to said actual user request.

2. The computerized method of claim 1 wherein said list of anticipated requests comprises a deadline for downloading to said user device data responsive to said anticipated request.

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

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

5. The computerized method of claim 1 wherein generating a list of anticipated requests for data by analyzing said plurality of user requests comprises analyzing a plurality of daily user requests.

6. A computerized method for allocating resources in a network comprising:

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

(b) generating a list of anticipated requests for data by analyzing said plurality of user requests;

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

(d) for said anticipated request;

(1) downloading to said user device data responsive to said anticipated request;

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

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

7. The computerized method of claim 6 wherein said list of anticipated requests comprises a deadline for downloading to said user device data responsive to said anticipated request.

8. The computerized method of claim 7 wherein downloading to said user device data responsive to each anticipated request in said list comprises downloading data according to a schedule.

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

10. The computerized method of claim 6 wherein generating a list of anticipated requests for data by analyzing said plurality of user requests comprises analyzing a plurality of daily user requests.