Network usage optimization

• US 20060209841A1
• Filed: 03/02/2005
• Published: 09/21/2006
• Est. Priority Date: 03/02/2005
• Status: Active Grant

• Current Assignee: LinkedIn Corporation (Microsoft Corporation)
• Original Assignee: International Business Machines Corporation
• Inventors: Hamilton, Rick A. II, Le Sesne, Richard H., Boylan, Thomas F., Amorello, Stephen L.
• Granted Patent: US 7,796,523 B2
• Time in Patent Office: Days
• US Class Current: 370/395.210
• CPC Class Codes: H04L 47/10 Flow control; Congestion control
• CPC Class Codes: H04L 47/12 Avoiding congestion; Recovering from congestion

Abstract

A network usage optimization method for minimizing the total network usage fee. The method includes the steps of (a) providing a network and a data processing apparatus, wherein the data processing apparatus communicates via a PVC of the network; (b) obtaining past network traffic data for traffic over the PVC; (c) predicting future network traffic data for traffic over the PVC for a future time period based on the past network traffic data; and (d) based on the predicted future network traffic data, specifying a CIR for the PVC for the future time period that will result in a minimum predicted total network usage fee for the future time period.

Claims

1. A network usage optimization method, comprising the steps of:

(a) providing a network and a data processing apparatus, wherein the data processing apparatus communicates via a permanent virtual circuit (PVC) of the network;

(b) obtaining past network traffic data for traffic over the PVC;

(c) predicting future network traffic data for traffic over the PVC for a future time period based on the past network traffic data; and

(d) based on the predicted future network traffic data, determining and specifying an optimum CIR for the PVC for the future time period that will result in a minimum predicted total network usage fee for the future time period.

2. The method of claim 1, wherein in step (b), the past network traffic data includes a traffic rate at any time of a past time period.

3. The method of claim 1, wherein in step (b), the network traffic associated with the past network traffic data comprises sale transaction traffic originated from a point of sale.

4. The method of claim 3, wherein the network traffic associated with the past network traffic data further comprises management transaction traffic.

5. The method of claim 1, wherein step (c) comprises the step of predicting the future network traffic data for the future time period based on traffic data of a plurality of past time periods equivalent to the future time period.

6. The method of claim 5, wherein step (c) comprises the step of predicting the future network traffic data for the future time period to be an average traffic data of the plurality of past time periods.

7. The method of claim 5, wherein the future time period and the plurality of past time periods are all the same day of the week.

8. The method of claim 1, wherein step (c) comprises the step of predicting the future network traffic data for the future time period to be the same as the traffic data of a past time period if

(i) the future time period is equivalent to the past time period, and

(ii) the traffic pattern preceding the future time period is essentially the same as the traffic pattern preceding the past time period.

9. The method of claim 1, wherein the step of determining the CIR for the PVC for the future time period is further based on a CIR fee schedule and a transmission overflow fee schedule.

10. The method of claim 1, wherein the step of determining the CIR for the PVC for the future time period comprises the steps:

(i) based on the predicted future network traffic data, determining a predicted total network usage fee for the future period for each of a plurality of CIRs; and

(ii) selecting as the optimum CIR the CIR of the plurality of CIRs that is associated with the minimum predicted total network usage fee of the predicted total network usage fees.

11. The method of claim 1, wherein the step of specifying the CIR for the PVC for the future time period comprises the step of sending a setting change request via the network.

12. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, said computer readable program code comprising an algorithm adapted to implement a method for network usage optimization, said method comprising the steps of:

(a) obtaining past network traffic data for traffic over a PVC of a network;

(b) predicting future network traffic data for traffic over the PVC for a future time period based on the past network traffic data; and

(c) based on the predicted future network traffic data, determining and specifying an optimum CIR for the PVC for the future time period that will result in a minimum predicted total network usage fee for the future time period.

13. The computer program product of claim 12, wherein step (b) comprises the step of predicting the future network traffic data for the future time period based on traffic data of a plurality of past time periods equivalent to the future time period.

14. The computer program product of claim 13, wherein step (b) comprises the step of predicting the future network traffic data for the future time period to be an average traffic data of the plurality of past time periods.

15. The computer program product of claim 13, wherein the future time period and the plurality of past time periods are all the same day of the week.

16. The computer program product of claim 12, wherein step (b) comprises the step of predicting the future network traffic data for the future time period to be the same as the traffic data of a past time period if

(i) the future time period is equivalent to the past time period, and

(ii) the traffic pattern preceding the future time period is essentially the same as the traffic pattern preceding the past time period.

17. A network provisioning method, comprising integrating computer-readable code into a computing system, wherein the code in combination with the computing system is capable of performing the steps of:

(a) obtaining past network traffic data for traffic over a PVC of a network;

(b) predicting future network traffic data for traffic over the PVC for a future time period based on the past network traffic data; and

(c) based on the predicted future network traffic data, determining and specifying an optimum CIR for the PVC for the future time period that will result in a minimum predicted total network usage fee for the future time period.

18. The method of claim 17, wherein step (b) comprises the step of predicting the future network traffic data for the future time period based on traffic data of a plurality of past time periods equivalent to the future time period.

19. The method of claim 18, wherein step (b) comprises the step of predicting the future network traffic data for the future time period to be an average traffic data of the plurality of past time periods.

20. The method of claim 17, wherein step (b) comprises the step of predicting the future network traffic data for the future time period to be the same as the traffic data of a past time period if

(i) the future time period is equivalent to the past time period, and

(ii) the traffic pattern preceding the future time period is essentially the same as the traffic pattern preceding the past time period.