TELECOMMUNICATIONS NETWORK TRAFFIC METRICS EVALUATION AND PREDICTION

• US 20190379592A1
• Filed: 06/06/2019
• Published: 12/12/2019
• Est. Priority Date: 06/06/2018
• Status: Active Grant

• Current Assignee: The Joan and Irwin Jacobs Technion-Cornell Institute
• Original Assignee: The Joan and Irwin Jacobs Technion-Cornell Institute
• Inventors: SAMADI, Payman
• Granted Patent: US 10,644,979 B2
• Time in Patent Office: Days
• CPC Class Codes: H04L 41/145 involving simulating, designing, planning or modelling of a network
• CPC Class Codes: H04L 43/045 for graphical visualisation of monitoring data
• CPC Class Codes: H04L 43/062 related to network traffic
• CPC Class Codes: H04L 43/0852 Delays
• CPC Class Codes: H04L 43/0882 Utilisation of link capacity
• CPC Class Codes: H04L 43/14 using software, i.e. software packages network security related monitoring H04L63/1408
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences

Abstract

A method for evaluating and predicting telecommunications network traffic includes receiving site data for multiple geographic areas via a processor. The processor also receives weather data, event data, and population demographic data for the geographic areas. The processor also generates predicted occupancy data for each of the geographic areas and for multiple time intervals. The processor also determines a predicted telecommunications network metric for each of the geographic areas and for each of the time intervals, based on the predicted occupancy data.

Claims

1. A method, comprising:

receiving, via a processor, site data for each geographic area of a plurality of geographic areas;

generating, via the processor and for each geographic area of the plurality of geographic areas and for each time interval of a plurality of time intervals, predicted occupancy data; and

determining, via the processor and based on the predicted occupancy data, a predicted telecommunications network metric for each geographic area of the plurality of geographic areas and for each time interval of the plurality of time intervals.

2. The method of claim 1, further comprising generating, via the processor and for each geographic area of the plurality of geographic areas and for each time interval of a plurality of time intervals, predicted activity category data,

wherein the determining the predicted telecommunications network metric is further based on the predicted activity category data.

3. The method of claim 1, further comprising:

receiving, via at least one of;

a graphical user interface (GUI), an application programming interface (API), or an associated comma-separated values (CSV) file;

(1) an indication of a first geographic area of the plurality of geographic areas and (2) an indication of a first time interval of the plurality of time intervals,

sending, in response to receiving the indication of the first geographic area of the plurality of geographic areas and the indication of the first time interval of the plurality of time intervals, a signal to cause at least one of;

display within the GUI of the predicted telecommunications network metric associated with the first geographic area and the first time interval, delivery of the predicted telecommunications network metric associated with the first geographic area and the first time interval via the API, or delivery of the predicted telecommunications network metric associated with the first geographic area and the first time interval via an associated CSV file.

4. The method of claim 1, wherein the generating the predicted occupancy data is based on the site data, weather data, event data, and population demographic data.

5. The method of claim 1, wherein the site data includes site occupancy capacity data.

6. The method of claim 1, wherein the generating the predicted occupancy data includes an autoregressive moving average process.

7. The method of claim 1, wherein the generating the predicted occupancy data is performed using time series modeling.

8. The method of claim 1, further comprising receiving at least one of:

event data, historical data, predictive data, live data, or static data for the plurality of geographic areas,

the generating the predicted occupancy data being based on the at least one of event data, historical data, predictive data, live data, or static data.

9. The method of claim 1, further comprising sending a signal to cause at least one of:

display of the predicted telecommunications network metrics within a graphical user interface (GUI), delivery of the predicted telecommunications network metrics via an application programming interface (API), or delivery of the predicted telecommunications network metrics via a comma-separated values (CSV) file.

10. The method of claim 1, wherein the receiving the site data is via at least one of a GUI, an API, or a CSV file.

11. A method, comprising:

receiving, via a processor, site data for a predetermined geographic area;

receiving, via the processor, event data for the predetermined geographic area;

generating, via the processor, a predicted telecommunications traffic metric for the predetermined geographic area and for a predetermined time interval, based on the site data and the event data;

in response to receiving an indication of the predetermined geographic area and an indication of the predetermined time interval via at least one of a GUI, an API, or a CSV file, sending a signal to cause at least one of;

display of the predicted telecommunications traffic metric via the GUI, delivery of the predicted telecommunications traffic metric via an API, or delivery of the predicted telecommunications traffic metric via an associated CSV file.

12. The method of claim 11, wherein the predicted telecommunications traffic metric includes a predicted traffic volume and an associated traffic type.

13. The method of claim 11, wherein the event data includes movement data associated with an individual.

14. The method of claim 11, further comprising sending a signal to cause at least one of:

display, within the GUI, of a map including the predetermined geographic area, delivery of the map including the predetermined geographic area via the API, or delivery of the map including the predetermined geographic area via an associated CSV file.

15. The method of claim 11, wherein the generating the predicted telecommunications traffic metric includes an autoregressive moving average process.

16. The method of claim 11, wherein the generating the predicted telecommunications traffic metric is performed using time series modeling.

17. The method of claim 11, wherein the receiving the site data is via at least one of:

the GUI, the API, or an associated CSV file.

18. The method of claim 11, wherein the receiving the event data is via at least one of:

the GUI, the API, or an associated CSV file.

19. A method, comprising:

receiving, via a processor, event data for a geographic area;

receiving, via the processor, capacity data for a venue within the geographic area;

determining, via the processor and based on the event data and the capacity data, a population volume time series;

receiving, via the processor, historical data associated with the geographic area;

determining, via the processor and based on the population volume time series and the historical data, a relativized population volume time series; and

predicting a resource demand for the geographic area based on the relativized population volume time series.

20. The method of claim 19, wherein the predicting the resource demand for the geographic area is based on a combination of the population volume time series and the relativized population volume time series.

21. The method of claim 19, wherein the combination of the population volume time series and the relativized population volume time series is generated using at least one of normalization. re-factoring and re-sampling.

22. The method of claim 19, wherein the predicting the resource demand for the geographic area is further based on an autoregressive moving average (ARMA).

23. The method of claim 19, wherein the resource demand is a demand for a telecommunications resource.

24. The method of claim 19, further comprising:

generating a recommended action based on the predicted resource demand; and

sending a signal to cause at least one of;

display of the recommended action within a GUI, notification of the recommended action via the API, or notification of the recommended action via an associated CSV file.

25. The method of claim 19, further comprising:

identifying a remediation measure based on the predicted resource demand; and

sending a signal to cause at least one of;

display of the remediation measure within a GUI, notification of the remediation measure via the API, or notification of the remediation measure via an associated CSV file.

26. The method of claim 19, wherein the receiving the event data for the geographic area is via at least one of:

a GUI, an API, or an associated CSV file.

27. The method of claim 19, wherein the receiving the capacity data for a value within the geographic area is via a at least one of:

a GUI, an API, or an associated CSV file.

28. The method of claim 19, wherein the receiving the historical data associated with the geographic area is via at least one of:

a GUI, an API, or an associated CSV file.