Exponential moving maximum (EMM) filter for predictive analytics in network reporting
View Patent ↗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.
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.