Virtual clustering for scalable network control and management

• US 7,996,510 B2
• Filed: 09/28/2007
• Issued: 08/09/2011
• Est. Priority Date: 09/28/2007
• Status: Expired due to Fees

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Vicente, John
• Primary Examiner(s): Caldwell; Andrew
• Assistant Examiner(s): TRAN, LOI H
• Application Number:
  US11/864,805
• Publication Number:
  US 20090089300A1
• Time in Patent Office: 1,411 Days
• Field of Search: 709/223
• US Class Current: 709/223
• CPC Class Codes: H04L 41/044 comprising hierarchical management structures
• CPC Class Codes: H04L 41/0893 Assignment of logical groups to network elements
• CPC Class Codes: H04L 41/0894 Policy-based network configuration management
• CPC Class Codes: H04L 41/40 using virtualisation of network functions or resources, e.g. SDN or NFV entities

Abstract

In some embodiments, the invention involves a system and method relating to a framework to build a new class of network control (policy) and (state) management services. The framework may be used to build a number of self-management services to support decentralized (mesh) networks. In at least one embodiment, the present invention is intended to hybridize centralized and decentralized network models to generate a more stable and robust network environment using clustering. Other embodiments are described and claimed.

Claims

1. A method for virtual clustering and network control in a hierarchical network having a plurality of computing nodes, comprising:

autonomously determining, by a node, whether the node should be promoted, demoted or stay at a same level in the network hierarchy, the promotion and demotion of the node is to a current cluster level from a previous cluster level, wherein a promoted node rises to a cluster level above the previous cluster level and becomes part of a virtual cluster at the level above, while remaining in a virtual cluster of the previous level, and wherein a demoted node falls to a cluster level below the previous cluster level and no longer remains in the virtual cluster at the higher level;

providing management and control service functions to cluster k peer nodes when the node has been promoted to a cluster-head of the cluster k; and

providing management and control service functions to other nodes in cluster levels below the current cluster level of the node from which the node has been promoted,

wherein self-promotion and demotion are based on the node'"'"'s behavior relating to (a) reachability, (b) stability and (c) performance efficiency, and

wherein information used to enable self-promotion and demotion of the node from the previous cluster is based on collected states, and the information is distributed among nodes in the hierarchical network residing with nodes having a relationship to the previous cluster and wherein the information is not guaranteed to be held by any one node in the hierarchical network, and wherein membership of the node in a cluster is irrelevant to a physical network model except when related to the node'"'"'s behavior regarding reachability, stability and performance efficiency, and

wherein there is no prohibition or rule against a cluster having only one member or having as many clusters as there are nodes in the network, and wherein cluster membership is based on self-promotion and demotion.

2. The method as recited in claim 1, wherein the autonomously determining, by a node, executes in one of a secure embedded partition on the node, a virtual machine on the node, or in a second processor on the node, wherein the second processor is one of a baseboard management controller and an active management technology controller.

3. The method as recited in claim 1, wherein stability of a node is determined based on an entropy-based statistical model.

4. The method as recited in claim 1, wherein clusters are identified in the network by a cluster address identifying a cluster level and cluster domain such that a cluster at a physical network level, or a lowest level cluster level n, is labeled as, cluster C(n, 0), where 0<

=n<

y, and y is the number of levels in the emergent hierarchy, and a next level higher cluster is labeled C(n−

1, m) where 0<

=m<

y_cl, and y_cl equals a number of clusters at this hierarchy level.

5. The method as recited in claim 4, further comprising:

configuring nodes in a cluster k and cluster-heads associated with a parent cluster of cluster k using the cluster address for sinking and responding to cluster operational communications, and wherein a global cluster-head uses the cluster address for sourcing operational communications and clustering control and management.

6. The system as recited in claim 5, further comprising:

communicating by the cluster-head node to peer cluster-heads at a same cluster level.

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

receiving by a cluster-hear node cluster state conditions;

performing aggregation and correlation within respective clusters associated with the cluster-head, wherein at each cluster level, control and management behavior is exhibited independently between cluster levels to provide both temporal and spatial aggregation,

performing, by the cluster-head, analysis through statistical computing techniques; and

holding cluster knowledge for state-level assimilation with peer clusters.

8. The method as recited in claim 1, wherein the hierarchical network is a hybrid of both centralized and decentralized network frameworks, centralization to be effected by self-promotion of a node to cluster-head within a virtual cluster in a cluster level and decentralization exists at a lowest cluster level in the network, as well as within each cluster where nodes communicate as if peer-to-peer.

9. The method as recited in claim 1, wherein autonomously determining whether the node should be promoted, demoted or stay at the same level further compromises weighting the node'"'"'s behavior relating to each of (a) reachability, (b) stability and (c) performance efficiency to rank the node for promotion or demotion, and where the weights are pre-determined based on a function of the network.

11. The system as recited in claim 1, wherein the logic for autonomous self-promotion and demotion in the network executes in a secure embedded partition on the node.

12. The system as recited in claim 1, wherein the logic for autonomous self-promotion and demotion in the network executes in a virtual machine on the node.

13. The system as recited in claim 1, wherein the logic for autonomous self-promotion and demotion in the network executes in a second processor on the node, wherein the second processor is one of a baseboard management controller and an active management technology controller.

14. The system as recited in claim 1, wherein stability of a node is determined based on an entropy-based statistical model.

15. The system as recited in claim 1, wherein clusters are identified in the network by a cluster address identifying a cluster level and cluster domain such that a cluster at a physical network level, or a lowest level cluster level n, is labeled as, cluster C(n, 0), where 0<

=n<

y, and y is the number of levels in the emergent hierarchy, and a next level higher cluster is labeled C(n−

1, m) where 0<

=m<

y_cl, and y_cl equals a number of clusters at this hierarchy level.

16. The system as recited in claim 15, wherein nodes in a cluster k and cluster-heads associated with a parent cluster of cluster k are configured to use the cluster address for sinking and responding to cluster operational communications, and wherein a global cluster-head uses the cluster address for sourcing operational communications and clustering control and management.

17. The system as recited in claim 16, wherein a cluster-head node communicates to peer cluster-heads at a same cluster level.

18. The system as recited in claim 17, wherein the cluster-head node is to receive cluster state conditions and to perform aggregation and correlation within respective clusters associated with the cluster-head, and wherein the cluster-head is to perform cluster state analysis through statistical computing techniques, and to hold cluster knowledge for state-level assimilation with peer clusters, wherein at each cluster level, control and management behavior is performed independently between cluster levels to provide both temporal and spatial aggregation.

19. The system as recited in claim 1, wherein the hierarchical network is a hybrid of both centralized and decentralized network frameworks, centralization to be effected by self-promotion of a node to cluster-head within a virtual cluster in a cluster level and decentralization exists at a lowest cluster level in the network, as well as within each cluster where nodes communicate as if peer-to-peer.

20. The system as recited in claim 1, wherein the logic for autonomous self-promotion and demotion in the network is configured to weight the node'"'"'s behavior relating to each of (a) reachability, (b) stability and (c) performance efficiency to rank the node for promotion or demotion, and where the weights are pre-determined based on a function of the network.

10. A system for virtual clustering and network control, comprising:

a plurality of computing nodes in a hierarchical network, each node comprising;

logic for autonomous self-promotion and demotion in the network, the promotion and demotion of the node is to a current cluster level from a previous cluster level, wherein a promoted node rises to a cluster level above the previous cluster level and becomes part of a virtual cluster at the cluster level above, while remaining in a virtual cluster of the previous cluster level, and wherein a demoted node falls to a cluster level below the previous cluster level and no longer remains in the virtual cluster at the higher level;

logic to provide management and control service functions to cluster k peer nodes in a node that has been promoted to a cluster-head of the cluster k;

logic to provide management and control service functions to other nodes in cluster levels below the current cluster level of the node from which the node has been promoted,

wherein self-promotion and demotion are based on a node'"'"'s behavior relating to (a) reachability, (b) stability and (c) performance efficiency, and wherein information used to enable self-promotion and demotion of the node from the previous cluster is based on collected states, and the information is distributed among nodes in the hierarchical network residing with nodes having a relationship to the previous cluster and wherein the information is not guaranteed to be held by any one node in the hierarchical network, and wherein membership of the node in a cluster is irrelevant to a physical network model except when related to the node'"'"'s behavior regarding reachability, stability and performance efficiency, and

wherein there is no prohibition or rule against a cluster having only one member or having as many clusters as there are nodes in the network, and wherein cluster membership is based on self-promotion and demotion.

21. A non-transitory machine readable storage medium having instructions stored therein, the instructions for virtual clustering and network control in a hierarchical network having a plurality of computing nodes, that when the instructions are executed in a machine, cause the machine to:

autonomously determine, by a node, whether the node should be promoted, demoted or stay at a same level in the network hierarchy, the promotion and demotion of the node is to a current cluster level from a previous cluster level, wherein a promoted node rises to a cluster level above the previous cluster level and becomes part of a virtual cluster at the level above, while remaining in a virtual cluster of the previous level, and wherein a demoted node falls to a cluster level below the previous cluster level and no longer remains in the virtual cluster at the higher level;

provide management and control service functions to cluster k peer nodes when the node has been promoted to a cluster-head of the cluster k; and

provide management and control service functions to other nodes in cluster levels below the current cluster level of the node from which the node has been promoted,

wherein self-promotion and demotion are based on a node'"'"'s behavior relating to (a) reachability, (b) stability and (c) performance efficiency, and

wherein information used to enable self-promotion and demotion of the node from the previous cluster is based on collected states, and the information is distributed among nodes in the hierarchical network residing with nodes having a relationship to the previous cluster and wherein the information is not guaranteed to be held by any one node in the hierarchical network, and wherein membership of the node in a cluster is irrelevant to a physical network model except when related to the node'"'"'s behavior regarding reachability, stability and performance efficiency, and

wherein there is no prohibition or rule against a cluster having only one member or having as many clusters as there are nodes in the network, and wherein cluster membership is based on self-promotion and demotion.

22. The non-transitory medium as recited in claim 21, wherein the autonomously determining, by a node, executes in one of a secure embedded partition on the node, a virtual machine on the node, or in a second processor on the node, wherein the second processor is one of a baseboard management controller and an active management technology controller.

23. The non-transitory medium as recited in claim 21, wherein stability of a node is determined based on an entropy-based statistical model.

24. The non-transitory medium as recited in claim 21, wherein clusters are identified in the network by a cluster address identifying a cluster level and cluster domain such that a cluster at a physical network level, or a lowest level cluster level n, is labeled as, cluster C(n, 0), where 0<

=n<

y, and y is the number of levels in the emergent hierarchy, and a next level higher cluster is labeled C(n−

1, m) where 0<

=m<

y_cl, and y_cl equals a number of clusters at this hierarchy level.

25. The non-transitory medium as recited in claim 21, wherein autonomously determining whether the node should be promoted, demoted or stay at the same level further compromises instructions to weight the node'"'"'s behavior relating to each of (a) reachability, (b) stability and (c) performance efficiency to rank the node for promotion or demotion, and where the weights are pre-determined based on a function of the network.