Exponential moving maximum (EMM) filter for predictive analytics in network reporting

• US 9,602,462 B2
• Filed: 04/17/2015
• Issued: 03/21/2017
• Est. Priority Date: 09/11/2014
• Status: Active Grant

• Current Assignee: Infoblox Incorporated
• Original Assignee: Infoblox Incorporated
• Inventors: Yu, Bin, Smith, Les, Threefoot, Mark
• Primary Examiner(s): Pham, Chi H
• Assistant Examiner(s): HOM, SHICK C
• Application Number:
  US14/689,823
• Publication Number:
  US 20160080216A1
• Time in Patent Office: 704 Days
• Field of Search: None
• US Class Current: 1/1
• CPC Class Codes: H04L 41/0604 using filtering, e.g. reduction of information by using priority, element types, position or time
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 41/40 using virtualisation of network functions or resources, e.g. SDN or NFV entities
• CPC Class Codes: H04L 41/5009 Determining service level performance parameters or violations of service level contracts, e.g. violations of agreed response time or mean time between failures [MTBF]
• CPC Class Codes: H04L 43/045 for graphical visualisation of monitoring data
• CPC Class Codes: H04L 43/08 Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
• CPC Class Codes: H04L 43/20 the monitoring system or the monitored elements being virtualised, abstracted or software-defined entities, e.g. SDN or NFV
• CPC Class Codes: H04L 61/4511 using domain name system [DNS]
• CPC Class Codes: H04L 61/5014 using dynamic host configuration protocol [DHCP] or bootstrap protocol [BOOTP]

Abstract

Techniques for an exponential moving maximum (EMM) filter for predictive analytics in network reporting are disclosed. In some embodiments, a process for predictive analytics in network reporting using an EMM filter includes pre-processing network-related data by performing exponential moving maximum (EMM) filtering on the network-related data; and determining predictive analytics based on the EMM filtered network-related data.

Claims

1. A system for predictive analytics in network reporting, comprising:

a processor configured to;

pre-process network-related data by performing exponential moving maximum (EMM) filtering on the network-related data, comprising to;

aggregate peak values of numbers of transactions per second (TPS) of network events over a plurality of periods of time to obtain the network-related data, a peak value relating to the maximum value of TPS of network events over a period of time; and

perform the EMM filtering on the network-related data; and

determine predictive analytics based on the EMM filtered network-related data, comprising to;

adjust a network capacity of a network based on the determined predictive analytics; and

a memory coupled to the processor and configured to provide the processor with instructions.

2. The system recited in claim 1, wherein the network-related data includes monitored network events data.

3. The system recited in claim 1, wherein the network-related data includes Domain Name System (DNS) data.

4. The system recited in claim 1, wherein the network-related data includes Domain Name System (DNS) query and DNS response data.

5. The system recited in claim 1, wherein to determine predictive analytics based on the EMM filtered network-related data includes to:

generate a trend prediction based on the EMM filtered network-related data.

6. The system recited in claim 1, wherein the processor is further configured to:

generate a trend prediction based on the EMM filtered network-related data; and

generate a visualization of the trend prediction for display.

7. The system recited in claim 1, wherein the processor is further configured to:

receive network-related data.

8. The system recited in claim 1, wherein the processor is further configured to:

receive Domain Name System (DNS) data that is collected from an agent executed on a DNS appliance.

9. The system recited in claim 1, wherein the processor is further configured to:

collect network-related data from one or more network devices.

10. The system recited in claim 1, wherein the processor is further configured to:

collect network-related data from one or more network devices; and

store the network-related data in a data store.

11. A method of predictive analytics in network reporting, comprising:

pre-processing network-related data by performing exponential moving maximum (EMM) filtering on the network-related data, comprising;

aggregating peak values of numbers of transactions per second (TPS) of network events over a plurality of periods of time to obtain the network-related data, a peak value relating to the maximum value of TPS of network events over a period of time; and

performing the EMM filtering on the network-related data; and

determining predictive analytics based on the EMM filtered network-related data, comprising;

adjusting a network capacity of a network based on the determined predictive analytics.

12. The method of claim 11, wherein the network-related data includes monitored network events data.

13. The method of claim 11, wherein the network-related data includes Domain Name System (DNS) data.

14. The method of claim 11, wherein the network-related data includes Domain Name System (DNS) query and DNS response data.

15. The method of claim 11, further comprising:

generating a trend prediction based on the EMM filtered network-related data; and

generating a visualization of the trend prediction for display.

16. A computer program product for predictive analytics in network reporting, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for:

pre-processing network-related data by performing exponential moving maximum (EMM) filtering on the network-related data, comprising;

aggregating peak values of numbers of transactions per second (TPS) of network events over a plurality of periods of time to obtain the network-related data, a peak value relating to the maximum value of TPS over a period of time; and

performing the EMM filtering on the network-related data; and

determining predictive analytics based on the EMM filtered network-related data, comprising;

adjusting a network capacity of a network based on the determined predictive analytics.

17. The computer program product recited in claim 16, wherein the network-related data includes monitored network events data.

18. The computer program product recited in claim 16, wherein the network-related data includes Domain Name Systems (DNS) data.

19. The computer program product recited in claim 16, wherein the network-related data includes Domain Name Systems (DNS) query and DNS response data.

20. The computer program product recited in claim 16, further comprising computer instructions for:

generating a trend prediction based on the EMM filtered network-related data; and

generating a visualization of the trend prediction for display.