Dynamic allocation of network resources using external inputs
Systems and methods for managing network resources are disclosed. One method can comprise receiving first information relating to network traffic parameters and receiving second information relating to one or more contextual events having an effect on the network traffic parameters. The first information and the second information and be correlated. And one or more network resources can be allocated based on the correlation of the first information and the second information.
1. A method comprising:
receiving, by one or more computing devices, first information relating to network traffic parameters associated with a network;
receiving, by the one or more computing devices, second information relating to one or more contextual events having an effect on the network traffic parameters, wherein the one or more contextual events are external to the network, and wherein the second information comprises an indication of a location of the one or more contextual events;
correlating, by the one or more computing devices, the first information and the second information; and
allocating one or more network resources based on the correlation of the first information and the second information, wherein the allocating the one or more network resources are associated with the location of the one or more contextual events.
2. The method of claim 1 , wherein the network traffic parameters comprise one or more of congestion, call volume, retransmissions, and packet loss.
3. The method of claim 1 , wherein the second information comprises one or more of a call detail record, weather information, E911 information, website information, emergency broadcast information, video feed, news feed, and geological information source.
4. The method of claim 1 , wherein the second information comprises one or more of a source identifier, readership level, and content type.
5. The method of claim 1 , wherein the correlating the first information with the second information comprises comparing one or more network signatures of the network traffic parameters to portions of the second information.
6. The method of claim 1 , wherein the correlating the first information with the second information comprises identifying a traffic pattern based at least on the first information and the second information.
7. The method of claim 1 , further comprising applying, based on at least the location of the one or more contextual events, a weight factor to at least a portion of the second information, wherein the correlating the first information with the second information is based at least in part on the applied weight factor.
8. The method of claim 1 , wherein the allocating the one or more network resources comprises allocating bandwidth to one or more services affected by the one or more contextual events.
9. The method of claim 1 , wherein the allocating the one or more network resources comprises launching virtual instances to manage network traffic associated with the network traffic parameters.
10. A method comprising:
receiving, by one or more computing devices, contextual information relating to events having a current or predicted effect on network traffic associated with a network, wherein the events are external to the network, and wherein the contextual information comprises an indication of a location of the events;
classifying, by the one or more computing devices, the contextual information based on one or more classification factors;
generating, by the one or more computing devices, a traffic predictor based on the classified contextual information; and
allocating one or more network resources based at least on the traffic predictor, wherein the allocating the one or more network resources are associated with the location of the events.
11. The method of claim 10 , wherein the contextual information comprises one or more of a call detail record, weather information, E911 information, website information, emergency broadcast information, video feed, news feed, and geological information source.
12. The method of claim 10 , wherein the classification factors comprise one or more of a source identifier, readership level, and content type.
13. The method of claim 10 , wherein the allocating the one or more network resources comprises allocating bandwidth to one or more services affected by the events.
14. The method of claim 10 , wherein the allocating the one or more network resources comprises launching virtual instances to manage network traffic associated with network traffic parameters.
15. A method comprising:
receiving, by one or more computing devices, first information from a first source relating to one or more contextual events, wherein the one or more contextual events are external to a network, and wherein the first information comprises an indication of a location of the one or more contextual events;
receiving, by the one or more computing devices, second information from a second source relating to the one or more contextual events;
determining, by the one or more computing devices, that the first information has a predictive effect on network traffic;
determining, based on the first information and the second information, a weight factor associated with the predictive effect; and
allocating, based on at least the weight factor, one or more network resources, wherein the allocating the one or more network resources are associated with one or more of a first location and a second location.
16. The method of claim 15 , wherein one or more of the first information and the second information comprises one or more of a call detail record, weather information, E911 information, website information, emergency broadcast information, video feed, news feed, and geological information source.
17. The method of claim 15 , wherein one or more of the first information and the second information comprises one or more of a source identifier, readership level, and content type.
18. The method of claim 15 , wherein identifying one or more of the first information and the second information as having a predictive effect on network traffic comprises comparing one or more network signatures of network traffic parameters to portions of the one or more of the first information and the second information.
19. The method of claim 15 , wherein identifying one or more of the first information and the second information as having a predictive effect on network traffic comprises identifying a traffic pattern based at least on the one or more of the first information and the second information.
20. The method of claim 15 , wherein identifying one or more of the first information and the second information as having a predictive effect on network traffic comprises comparing historic network traffic pattern based at least on the one or more of the first information and the second information.
21. The method of claim 15 , wherein the allocating the one or more network resources comprises allocating bandwidth to one or more services affected by the one or more contextual events.
22. The method of claim 15 , wherein the allocating the one or more network resources comprises launching virtual instances to manage network traffic associated with the location of the one or more contextual events.