Method and system for determining maximum transactions within a communications network

• US 20060140368A1
• Filed: 12/23/2004
• Published: 06/29/2006
• Est. Priority Date: 12/23/2004
• Status: Active Grant

• Current Assignee: T-Mobile Innovations LLC (Deutsche Telekom AG)
• Original Assignee: Sprint Communications Company LP (Deutsche Telekom AG)
• Inventors: Saghier, Dean Lee, Chen, Jianzhou, Wyett, Richard Michael, Mark, Bruce Allen
• Granted Patent: US 7,676,032 B2
• Time in Patent Office: Days
• US Class Current: 379/114.30
• CPC Class Codes: H04M 15/00 Arrangements for metering, time-control or time indication ; Metering, charging or billing arrangements for voice wireline or wireless communications, e.g. VoIP
• CPC Class Codes: H04M 15/58 based on statistics of usage or network monitoring
• CPC Class Codes: H04M 2215/0188 Network monitoring; statistics on usage on called/calling number
• CPC Class Codes: H04M 3/2218 Call detail recording
• CPC Class Codes: H04M 3/36 Statistical metering, e.g. recording occasions when traffic exceeds capacity of trunks

Abstract

A call-transaction forecasting tool taking the form of a computer-implemented method and medium in some embodiments is provided for retrieving, aggregating, sorting, and determining one or more maximum transactions within a communications network. The tool automates the process of manually extracting and analyzing call transactions pertaining to call-duration, call volume, traffic usage, bandwidth usage, processing usage and memory usage in order to properly forecast and predict future network growth and capacity within a providers network. The computer-implemented method includes retrieving transaction data files from a switch or server, merging the files in a commonly shared data structure, identifying one or more maximum transaction counts based upon an associated period of time, and displaying the maximum counts and associated period of time.

Claims

1. A computer-implemented method for using call transactions to forecast demand for processing resources, the method comprising:

receiving one or more data files having at least one record of information, the information relating to one or more call transactions;

aggregating all or a portion of the information into a data structure;

identifying one or more maximum call transactions within the data structure; and

presenting the one or more maximum call transactions.

2. The method of claim 1, wherein the one or more call transactions provides at least one of the following:

a date, a time, and a transaction count.

3. The method of claim 2, wherein the transaction count comprises at least one of the following:

a call-duration count;

a call-volume data count;

a traffic-usage count;

a bandwidth-usage count;

a CPU-utilization count;

an access/failure count;

a data-utilization count; and

a data-packet count.

4. The method of claim 1, wherein the data structure is an ascending or descending sorted spreadsheet or database table.

5. The method of claim 1, wherein the one or more maximum call transactions is derived by determining the highest transaction count in the data structure.

6. The method of claim 5, wherein the one or more maximum call transactions corresponds to one or more hours, the one or more hours being one or more peak hours.

7. The method of claim 6, wherein the one or more maximum call transactions and the one or more peak hours are selected and transferred into a second data structure.

8. The method of claim 7, wherein the second data structure is a document file, an HTML file, a spreadsheet file, a database file, a graphics file, or a combination thereof.

9. The method of claim 1, wherein presenting the one or more maximum call transactions further comprises:

displaying the one or more maximum call transactions within a printed report document;

displaying the one or more maximum call transactions on the Internet; and

displaying the one or more maximum call transactions within an electronic display.

10. A computer-implemented method for using call transactions to forecast demand for processing resources, the method comprising:

receiving one or more data files relating to call-transaction data, the call-transaction data including a plurality of time periods and a corresponding count of transactions associated with the plurality of time periods;

aggregating all or a portion of the call-transaction data into a data structure;

identifying a maximum count from the call-transaction data;

identifying a time indication corresponding to the maximum count; and

presenting the maximum count and the corresponding time indication.

11. The method of claim 10, wherein the call-transaction data includes a date.

12. The method of claim 10, wherein the data structure is a document, a spreadsheet, a database, or a combination thereof.

13. The method of claim 10, wherein the maximum count is a call-usage identifier.

14. The method of claim 13, wherein the call-usage identifier is a call-volume, a trunk-usage, or a time-tracking indication.

15. The method of claim 10, wherein the time indication corresponding to the maximum count denotes a peak hour.

16. The method of claim 10, wherein presenting the maximum count and the corresponding time indication, further comprises:

displaying the maximum count and the time indication in a printed report document;

displaying the maximum count and the time indication on the Internet; and

displaying the maximum count and the time indication within a graphical-user interface.

17. A computer-implemented method for monitoring hourly call transactions to forecast demand for processing resources, the method comprising:

scheduling automatic retrieval of one or more data files from a server;

retrieving the one or more data files based upon a scheduled indication of time;

merging the one or more data files into a data structure;

determining at least one maximum-transaction indication from the data structure; and

presenting the maximum-transaction indication.

18. The method of claim 17, wherein scheduling automatic retrieval of one or more data files is performed using a scheduling software tool.

19. The method of claim 17, wherein the one or more data files are call-usage log files having at least one of the following indications:

an identification number;

a yearly date;

an hour;

a transaction count; and

a status indication.

20. The method of claim 17, wherein collectively merging the one or more data files includes sorting the one or more data files into a list, wherein the list is a sorted list based on a plurality of transaction indications.

21. The method of claim 20, wherein the plurality of transaction indications comprises a number of call record transactions per hour.

22. The method of claim 17, wherein the data structure is a document, a spreadsheet, or a database table.

23. The method of claim 17, wherein the list includes an hour corresponding to the maximum-transaction indication, the hour is a peak hour of the maximum-transaction indication.

24. The method of claim 17, wherein presenting the maximum-transaction indication, further comprises:

displaying the maximum-transaction indication in a printed report document;

displaying the maximum-transaction indication on the Internet; and

displaying the maximum-transaction indication within a graphical-user interface.

25. One or more computer-readable media having computer-useable instructions embodied thereon for determining a peak-transaction value corresponding to an hour in order to forecast peak-processing usage on a communications network, the method comprising:

receiving one or more sets of transaction data from one or more data structures, wherein the one or more sets of transaction data includes a transaction count, an hour, and a date;

for each set of transaction data, merging the one or more sets of transaction data into a data structure;

identifying a peak hour corresponding to a maximum indication; and

presenting the peak hour and the maximum indication.

26. The method of claim 25, wherein the one or more sets of transaction data are call-usage log files.

27. The method of claim 25, wherein the one or more data structures is a communications switch or a server.

28. The method of claim 25, wherein merging the data into a data structure includes sorting in an ascending or descending order the transaction data.

29. The method of claim 28, wherein the data structure is a document, a spreadsheet, a database table, or a combination thereof.

30. The method of claim 25, wherein the maximum indication includes a call-volume number.

31. The method of claim 30, wherein the call-volume number is a binary number, a bandwidth value, or a call-traffic number.

32. The method of claim 25, wherein presenting the peak hour and the maximum indication, further comprises:

displaying the peak hour and the maximum indication in a printed report document;

displaying the peak hour and the maximum indication on the Internet; and

displaying the peak hour and the maximum indication within a graphical-user interface.