Assisted determination of data flows in communication/data networks

• US 20060168168A1
• Filed: 03/19/2004
• Published: 07/27/2006
• Est. Priority Date: 03/20/2003
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Xia, Quanshi, Simonis, Helmut Matthias
• Granted Patent: US 8,423,633 B2
• Time in Patent Office: Days
• US Class Current: 709/223
• CPC Class Codes: H04L 41/142 using statistical or mathematical methods
• CPC Class Codes: H04L 43/00 Arrangements for monitoring or testing data switching networks
• CPC Class Codes: H04L 43/067 using time frame reporting
• CPC Class Codes: H04L 43/12 Network monitoring probes

Abstract

There is provided a method of determining data flow in a network, the method comprising: (a) selecting a location within the network for providing a data processing means adapted to process data pertaining to the network data flow; (b) determining the expense and/or level of data capture that would result from providing the data processing means at the selected location; and (c) providing the data processing means at the selected location dependent on the determination in step (b) and predetermined expense and/or data capture targets. This method can be used to select points inside the core of a network for data capture of flows routed through them in order to construct the traffic matrix of the network. This method has a number of advantages over known methods of obtaining the traffic matrix of a data network. In particular, it can be used for different use cases, maximizing the capture level for a given investment or finding the minimal investment to achieve a given capture level.

Claims

1. A method of determining data traffic flow in a network, the method comprising:

(a) selecting a location within the network for providing a data processing means adapted to process data pertaining to the network data traffic flow;

(b) determining the expense and/or level of data capture that would result from providing the data processing means at the selected location; and

(c) providing the data processing means at the selected location dependent on the determination in step (b) and predetermined expense and/or data capture targets.

2. The method of claim 1, further comprising:

repeating steps (a) and (b) for a plurality of locations; and

providing a said data processing means at each of a number of the selected locations dependent on the determination in steps (b) and predetermined expense and/or data capture targets.

3. The method of claim 2, further comprising:

determining a minimum overall data capture target; and

providing a said data processing means at each of a number of the selected locations to minimize the overall expense while meeting the minimum overall data capture target.

4. The method of claim 2, further comprising:

determining a maximum overall expense target; and

providing a said data processing means at each of a number of the selected locations to maximize the overall data capture while not exceeding the maximum overall expense target.

5. The method of claim 1, further comprising:

changing the configuration of the network;

determining the expense and/or increase or decrease in data capture that would result from re-locating a data processing means;

re-locating the data processing means dependent on the determination in the previous step and predetermined expense and/or data capture targets.

6. The method of claim 1, further comprising:

determining the traffic matrix of the network using data processed by the data processing means.

7. The method of claim 6, further comprising:

determining a plurality of traffic matrices over a predetermined period of time.

8. The method of claim 7, further comprising:

averaging the plurality of traffic matrices over said predetermined period of time.

9. The method of claim 7, further comprising:

determining the maximum data flow between two points in any of said plurality of traffic matrices to obtain a data flow worst case scenario.

10. The method of claim 6, further comprising:

repeating the traffic matrix determination to obtain data indicative of traffic evolution over time.

11. The method of claim 6, wherein the data capture target is determined by a percentage of the traffic matrix.

12. The method of claim 11, wherein the percentage of the traffic matrix is determined by a percentage of the total data flow volume in the network.

13. The method of claim 11, wherein the percentage of the traffic matrix is determined by a fraction of the number of data flows in the network.

14. The method of claim 1, further comprising:

simulating the routing algorithm used by the network to calculate the data capture of the data processing means.

15. The method of claim 1, wherein the expense is determined by the administration overhead in connection with processing data processed by a data processing means at a selected location.

16. The method of claim 1, wherein the expense is determined by the cost incurring by providing a data processing means at a selected location.

17. The method of claim 1, wherein the expense is determined by the decrease of performance by the network resulting from the provision of a data processing means at a selected location.

18. The method of claim 1, wherein said predetermined expense and/or data capture targets are met by varying the number of data processing means provided.

19. The method of claim 1, wherein the number of data processing means to be provided is predetermined.

20. The method of claim 1, wherein the data processing means comprise data collection means for collecting data pertaining to the network data flow.

21. The method of claim 1, wherein the data processing means comprise data extraction means for extracting data indicative of the network data flow from data processed by the data processing system.

22. The method of claim 20, wherein each data collection means is allocated to a data extraction means.

23. The method of claim 22, wherein the expense is determined by the cost of traffic between a data collection means and an allocated data extraction means.

24. The method of claim 1 implemented by mixed integer programming.

25. A computer program adapted to perform the method of claim 1 on a data processing system.

26. A method of observing data traffic in a network, the method comprising;

(a) determining a desired data collection result in relation to an acceptable data collection expense; and

(b) selecting a number of locations within the network for placing data collection means to obtain said desired data collection result at said acceptable data collection expense.

27. A data network comprising one or more inputs, outputs and routers, and a plurality of data processing means for processing data pertaining to the data flow in the network, wherein each of the data processing means is associated with a data capture value and/or an expense value, dependent on its location within the network, and wherein the number and/or locations of the data processing means are selected in accordance with predetermined expense and/or data capture targets.

28. The data network of claim 27, wherein the data processing means comprises data collection means for collecting data pertaining to the data flow in the network.

29. The data network of claim 28, wherein each of the data collection means is associated with one or more routers.

30. The data network of claim 29, wherein each data collection means is associated with one or more interface of an associated router.

31. The data network of claim 27, wherein the data processing means comprises data extraction means for extracting data indicative of the data flow in the network from the data processed by the data processing means.

32. The data network of claim 31, wherein each data collection means is allocated to a data extraction means.

33. The data network of claim 27, wherein some or all of the data processing means are connected to one another through a local area network.

34. The data network of any of claim 27, further comprising a central processing means for receiving data from the data processing means and determining the data flow in the network.

35. The data network of claim 34, wherein the central processing means is connected to some or all of the data processing means via the data network.

36. The data network of claim 27, wherein some or all of the data processing means are implemented in one or more of the routers.

37. The data network of claim 27, wherein the data processing means are software-implemented.

38. The data network of claim 27, wherein the data processing means are located and adapted to collect data pertinent to the data flow between routers.

39. The data network of claim 27, wherein the data processing means are located and adapted to collect data pertinent to the data flow between inputs and/or outputs.