Systems and methods for use in imposing network load restrictions

1. A computer-implemented method of imposing a restriction on requests for content by clients passed to a backend content source, the method comprising:

generating, by a computing device associated with a backend content source, a restriction value (RV) for content of the backend content source, based on: a number of supported requests (S) for the content by the backend content source, a number of current requests (C) for the content, a number of expected requests (E) for the content, and the following equation:

RV=1−mean( C/S,E/S );

transmitting, by the computing device, the restriction value to a content delivery network (CDN) interposed between one or more clients associated with the requests and the backend content source; and

routing, by the CDN, a percentage of requests for the content of the backend content source to a waiting room based on the restriction value, thereby permitting the CDN to account for the number of supported requests in offloading requests for the content to the waiting room.

2. The method of claim 1 , wherein the content includes an application.

3. The method of claim 1 , further comprising determining, by the computing device, the number of supported requests based on a stochastic prediction model.

4. The method of claim 3 , wherein the stochastic prediction model utilizes Monte Carlo simulation.

5. The method of claim 3 , further comprising determining, by the computing device, the number of current requests for the content and the number of expected requests for the content.

6. The method of claim 5 , wherein determining the number of current requests for the content includes determining the number of current requests for the content based on real time access logs for the content at the backend content source.

7. The method of claim 6 , wherein determining the number of expected requests for the content includes determining the number of expected requests for the content based on a moving average trend linear regression of historic data for the content at the backend content source for a defined interval.

8. The method of claim 1 , wherein the restriction value includes a probability of passing the request to the backend content source.

9. The method of claim 1 , further comprising determining the number of supported request for the content based on one or more dependencies of the content included in the backend content source.

10. A system for imposing a restriction on requests for content by clients passed to a backend content source, the system comprising:

at least one backend computing device associated with a backend content source configured to provide content in response to requests by one or more clients; and

at least one content delivery network (CDN) coupled between the at least one backend computing device and the one or more clients;

wherein the at least one backend computing device is configured to:

generate a restriction value (RV) for the content of the backend content source, based on a number of supported requests (S) for the content by the backend content source, a number of current requests (C) for the content, a number of expected requests (E) for the content, and the following equation:

RV=1−mean( C/S,E/S );

transmit the restriction value to the CDN; and

wherein the CDN is configured to route the requests by the one or more clients for the content of the backend content source between the at least one backend computing device and a waiting room based on the restriction value.

11. The system of claim 10 , wherein the restriction value includes a probability of passing the request to the backend content source.

12. The system of claim 10 , wherein the at least one backend computing device is further configured to determine the number of supported requests based on a stochastic prediction model utilizing Monte Carlo simulation.

13. The system of claim 12 , wherein the at least one backend computing device is further configured to determine the number of current requests for the content and the number of expected requests for the content.

14. The system of claim 13 , wherein the at least one backend computing device is configured, in connection with determining the number of expected requests for the content, to determine the number of expected requests for the content based on a moving average trend linear regression of historic data for the content at the backend content source for a defined interval.

15. The system of claim 14 , wherein the at least one backend computing device is configured, in connection with determining the number of current requests for the content, to determine the number of current requests for the content based on real time access logs for the content at the backend content source.

16. A non-transitory computer readable storage medium including executable instructions for imposing a restriction on requests for content by clients passed to a backend content source, which when executed by at least one processor, cause the at least one processor to:

generate a restriction value (RV) for content of the backend content source, based on a number of supported requests for the content by the backend content source, a number of current requests for the content, and a number of expected requests for the content, as defined by the following equation:

RV

=

1

-

mean

⁡

(

C

S

,

E

S

)

,

where C is the number of current requests for the content, S is the number of supported requests for the content, and E is the number of expected request for the content; and

transmit the restriction value to a content delivery network (CDN) interposed between one or more clients associated with the requests and the backend content source, whereby a percentage of requests for the content of the backend content source, based on the restriction value, are routed to a waiting room.

17. The non-transitory computer readable storage medium of claim 16 , wherein the executable instructions, when executed by the at least one processor, further cause the at least one processor to route the percentage of requests for the content of the backend content source to the waiting room based on the restriction value.

18. The non-transitory computer readable storage medium of claim 16 , wherein the executable instructions, when executed by the at least one processor, further cause the at least one processor to determine the number of current requests for the content and the number of expected requests for the content.