Measuring network traffic based on predicted amount of padding

• US 7,844,697 B1
• Filed: 07/12/2002
• Issued: 11/30/2010
• Est. Priority Date: 01/25/2002
• Status: Active Grant

• Current Assignee: Juniper Networks Incorporated
• Original Assignee: Juniper Networks Incorporated
• Inventors: Greene, Spencer
• Primary Examiner(s): Follansbee; John
• Assistant Examiner(s): Tiv; Backhean
• Application Number:
  US10/193,194
• Time in Patent Office: 3,063 Days
• Field of Search: 709/223, 709/224, 709/225, 709/232, 709/238, 370/505
• US Class Current: 709/224
• CPC Class Codes: H04L 41/147 for predicting network behaviour
• CPC Class Codes: H04L 43/0876 Network utilisation, e.g. volume of load or congestion level

Abstract

A system measures traffic in a device. The system tracks an amount of data and the data units and predicts the amount of padding associated with the data units. The system determines the amount of traffic in the device based on the predicted padding, the amount of data, and the number of data units.

Claims

1. A method for measuring traffic, comprising:

tracking an amount of data and a number of data units;

predicting an amount of padding associated with the data milts; and

determining an amount of traffic based on the predicted padding, the amount of data, and the number of data units.

2. The method of claim 1 wherein the data units include packets, and wherein the predicting includes:

determining the amount of padding on a per packet basis.

3. The method of claim 2 wherein the determining the amount of padding includes:

determining the amount of padding by subtracting the amount of data for a particular packet from a parameter.

4. The method of claim 3 wherein the parameter includes a minimum layer 3 (L3) size parameter.

5. The method of claim 4 further comprising:

determining the minimum L3 size parameter based on a minimum packet size parameter and a layer 2 (L2) header size.

6. The method of claim 1 wherein the data units include asynchronous transfer mode (ATM) cells, and wherein the predicting includes:

determining the amount of padding on a per AAL frame basis.

7. The method of claim 6 wherein the determining the amount of padding includes:

determining the amount of padding based on a cell size, a packet size, and an ATM adaptation layer (AAL) header size.

8. The method of claim 1 further comprising:

tracking the predicted amount of padding in a counter for a period of time.

9. The method of claim 1 wherein the determining the amount of traffic includes:

determining an amount of traffic based on a layer 2 (L2) header size, the number of data units, the amount of data, and the predicted amount of padding.

10. The method of claim 1 wherein the determining the amount of traffic includes:

determining the amount of traffic for a plurality of different communication protocols.

11. A network device comprising:

a first processing unit configured to;

process data to form data units, predict an amount of padding to be added to the data units, and calculate an amount of traffic in the network device based on the predicted amount of padding; and

a second processing unit configured to;

add the predicted amount of padding to the data units.

12. The network device of claim 11 wherein, when processing the data, the first processing unit is configured to:

perform layer 3 processing on the data to form packets.

13. The network device of claim 11 wherein the first processing unit is further configured to:

track an amount of data and data units for a period of time.

14. The network device of claim 13 wherein the data units include packets, and wherein the first processing unit predicts the amount of padding on a per packet basis.

15. The network device of claim 14 wherein the first processing unit predicts the amount of padding by subtracting an amount of data for a packet from a parameter.

16. The network device of claim 15 wherein the parameter includes a minimum layer 3 (L3) size parameter.

17. The network device of claim 11 wherein the data units include asynchronous transfer mode (ATM) cells, and wherein the first processing unit predicts the amount of padding on a per AAL frame basis.

18. The network device of claim 17 wherein the first processing unit predicts the amount of padding based on a cell size, a packet size, and an ATM adaptation layer (AAL) header size.

19. The network device of claim 11 wherein the second processing unit adds padding to the data units to bring the data units up to a minimum size value.

20. The network device of claim 11 wherein the first processing unit includes:

a plurality of computation units, at least two of the computation units configured to predict the amount of padding to be added to data units for a different communication protocol.

21. The network device of claim 20 wherein at least one of the plurality of computation units predicts the amount of padding to be added to data units in an Ethernet environment and at least one other communication unit predicts the amount of padding to be added to data units in an asynchronous transfer mode (ATM) environment.

22. The network device of claim 11 wherein the first processing unit includes:

a pad counter array configured to track a plurality of predicted padding amounts.

23. The network device of claim 22 wherein the first processing unit further includes:

a counter array configured to track an amount of data over a period of time, and a data unit counter array configured to track a number of data units over the period of time.

24. The network device of claim 23 wherein each counter in the pad counter array, counter array, and data unit counter array corresponds to a different stream or flow via which the network device transmits the data units.

25. The network device of claim 23 wherein each counter in the pad counter array, counter array, and data unit counter array corresponds to a different level of priority.

26. A network device comprising:

means for tracking a length and a number of data units;

means for predicting an amount of padding associated with data units; and

means for determining an amount of traffic in the network device based on the predicted padding, the length, and the number of data units.