Selective topology routing for distributed data collection

• US 8,971,188 B2
• Filed: 09/20/2013
• Issued: 03/03/2015
• Est. Priority Date: 07/12/2011
• Status: Active Grant

• Current Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Original Assignee: Cisco Technology, Inc. (Cisco Systems, Inc.)
• Inventors: Vasseur, Jean-Philippe, Hui, Jonathan W.
• Primary Examiner(s): Elliott, IV, Benjamin H
• Application Number:
  US14/032,884
• Publication Number:
  US 20140022906A1
• Time in Patent Office: 529 Days
• Field of Search: 370/235, 370/252
• US Class Current: 370/235
• CPC Class Codes: H04L 41/12 Discovery or management of network topologies
• CPC Class Codes: H04L 45/48 Routing tree calculation
• CPC Class Codes: H04L 45/488 using root node determination
• CPC Class Codes: H04L 47/12 Avoiding congestion; Recovering from congestion

Abstract

In one embodiment, a device, such as a network management server, determines a traffic matrix of a mesh network, where the traffic matrix indicates an amount of traffic per type of traffic transitioning between the mesh network and a global computer network via one or more current root devices. One or more optimized root devices may then be selected for corresponding directed acyclic graphs (DAGs) based on the amount of traffic and type of traffic. As such, a DAG formation request may be transmitted to the selected root devices, carrying a characteristic for a corresponding DAG to form by the respective selected root devices that indicates which one or more types of traffic correspond to the corresponding DAG.

Claims

1. A method, comprising:

selecting one or more optimized root devices from a plurality of capable devices in a mesh network for corresponding directed acyclic graphs (DAGs) based on an amount of traffic and type of traffic transitioning via one or more route devices; and

transmitting a DAG formation request to the selected one or more optimized root devices, the DAG formation request carrying a characteristic for a corresponding DAG to be formed by the respective selected optimized root devices that indicates which one or more types of traffic correspond to the corresponding DAG.

2. The method as in claim 1, furthermore comprising:

providing a traffic matrix for a mesh network, the traffic matrix indicating the amount of traffic per type of traffic transitioning via one or more current root devices;

wherein the traffic matrix further indicates the amount of traffic and the type of traffic per time of day, and wherein selecting the one or more optimized root devices for corresponding DAGs is further based on the amount of traffic and the type of traffic per time of day.

3. The method as in claim 2, wherein the characteristic for a particular corresponding DAG to form further indicates a time of day during which the particular corresponding DAG is active.

4. The method as in claim 1, wherein the type of traffic is selected from a group consisting of:

a particular class of service;

a particular application;

a particular priority of traffic;

a particular data type;

a particular head-end server; and

a particular size of traffic.

5. The method as in claim 1, wherein selecting comprises:

selecting a plurality of optimized root devices for corresponding DAGs, wherein the characteristics for the corresponding DAGs indicate at least one overlapping type of traffic between the corresponding DAGs.

6. The method as in claim 2, further comprising:

adjusting the selected optimized root devices based on an updated traffic matrix.

7. The method as in claim 6, further comprising:

utilizing hysteresis to limit a frequency of adjusting the selected one or more optimized root devices.

8. The method as in claim 1, wherein selecting the one or more optimized root devices for corresponding DAGs is in response to an event-driven trigger.

9. The method as in claim 8, wherein the event-driven trigger is in response to congestion in the mesh network.

10. An apparatus, comprising:

one or more network interfaces to communicate with nodes of a mesh network;

a processor coupled to the network interfaces and adapted to execute one or more processes; and

a memory configured to store the one or more processes executable by the processor, the one or more processes when executed operable to;

select one or more optimized root devices from a plurality of capable devices in the mesh network for corresponding directed acyclic graphs (DAGs) based on an amount of traffic and type of traffic transitioning via one or more root devices; and

transmit a DAG formation request to the selected one or more selected root devices, the DAG formation request carrying a characteristic for a corresponding DAG to be formed by the respective selected optimized root devices that indicates which one or more types of traffic correspond to the corresponding DAG.

11. The apparatus as in claim 10, wherein the one or more processes are further operable to provide a traffic matrix of the mesh network, the traffic matrix indicating the amount of traffic per type of traffic transitioning via one or more current root devices,

wherein the traffic matrix further indicates the amount of traffic and the type of traffic per time of day, and wherein selecting the one or more optimized root devices for corresponding DAGs is further based on the amount of traffic and the type of traffic per time of day.

12. The apparatus as in claim 11, wherein the characteristic for a particular corresponding DAG to form further indicates a time of day during which the particular corresponding DAG is active.

13. The apparatus as in claim 10, wherein the process when executed is further operable to:

adjust the selected optimized root devices based on an updated traffic matrix.

14. The apparatus as in claim 10, wherein selecting the one or more optimized root devices for corresponding DAGs is in response to an event-driven trigger.

15. A tangible, non-transitory, computer-readable media having software encoded thereon, the software when executed by a processor operable to:

select one or more optimized root devices from a plurality of capable devices in the mesh network for corresponding directed acyclic graphs (DAGs) based on an amount of traffic and type of traffic transitioning via one or more root devices; and

control transmission of a DAG formation request to the selected one or more selected root devices, the DAG formation request carrying a characteristic for a corresponding DAG to be formed by the respective selected optimized root devices that indicates which one or more types of traffic correspond to the corresponding DAG.

16. The computer-readable media as in claim 15, wherein the software when executed is further operable to:

provide a traffic matrix of the mesh network, the traffic matrix indicating the amount of traffic per type of traffic transitioning via one or more current root devices,

wherein the traffic matrix further indicates the amount of traffic and the type of traffic per time of day, and wherein selecting the one or more optimized root devices for corresponding DAGs is further based on the amount of traffic and the type of traffic per time of day.

17. The computer-readable media as in claim 16, wherein the characteristic for a particular corresponding DAG to form further indicates a time of day during which the particular corresponding DAG is active.

18. The computer-readable media as in claim 15, wherein the software when executed is further operable to:

adjust the selected optimized root devices based on an updated traffic matrix.

19. The computer-readable media as in claim 15, wherein the selection of the one or more optimized root devices for corresponding DAGs is in response to an event-driven trigger.