Load on demand network analysis

• US 20090063516A1
• Filed: 08/31/2007
• Published: 03/05/2009
• Est. Priority Date: 08/31/2007
• Status: Active Grant

• Current Assignee: Oracle International Corporation (Oracle Corporation)
• Original Assignee: Oracle International Corporation (Oracle Corporation)
• Inventors: Wang, Cheng-Hua, Gong, Huiling
• Granted Patent: US 8,429,199 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• 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 41/145 involving simulating, designing, planning or modelling of a network

Abstract

Systems, methodologies, media, and other embodiments associated with load on demand network analysis are described. One method embodiment includes accessing a network analysis request and data associated with a set of network partitions associated with a network. The request describes a function to be performed on the network. A set of partitions subdivides the network and a data model stores data describing the network and its partitions. Thus, the example method may include identifying a member of the set of network partitions associated with the network analysis request and selectively loading data associated that member. The method may then perform the network analysis function on the data associated with the member rather than on data describing the entire network.

Claims

1. A computer-readable medium storing processor executable instructions that when executed by a processor cause the processor to perform a method, the method comprising:

accessing a network analysis request to identify a network analysis function to be performed on a network, where the network is associated with a network model, and where the network is a graph representation of a set of objects of interest and a set of relationships between objects of interest;

accessing data associated with a set of network partitions that logically partition the network into two or more parts;

identifying a member of the set of network partitions associated with the network analysis request;

selectively loading data associated with the member into a memory associated with the processor;

performing the network analysis function on the data associated with the member; and

storing in a computer-readable medium a result obtained by performing the network analysis function on the member.

2. The computer-readable medium of claim 1, the network data model comprising a network metadata, a node table, a link table, a path table, and a partition table.

3. The computer-readable medium of claim 2, where data describing a node associated with an object of interest includes a node identifier, the node identifier being a foreign key in the partition table.

4. The computer-readable medium of claim 1, where selectively loading data associated with the member includes loading data from a relational database upon determining that data associated with the member is not already loaded in the memory associated with the processor.

5. The computer-readable medium of claim 4, where loading data from the relational database includes acquiring data individually on an element-by-element basis from one or more database tables.

6. The computer-readable medium of claim 4, where loading data from the relational database includes acquiring a partition data as an aggregate, the partition data being stored as a binary large object (BLOB).

7. The computer-readable medium of claim 1, the network being one of, a geographic information system network, a social network, a biologic network, a physical network, and a logical network.

8. The computer-readable medium of claim 1, where the network analysis function is one of, a spatial analysis, a path analysis, and a cost analysis.

9. The computer-readable medium of claim 1, where the network analysis function is one of, a shortest path function, an all paths function, a connected components function, a within-cost function, a nearest neighbor function, and a minimum cost spanning tree function.

10. The computer-readable medium of claim 2, the method including determining the set of network partitions and storing data associated with set of network partitions.

11. The computer-readable medium of claim 10, where storing data associated with the set of network partitions includes automatically updating the partition table in the network data model, the updating being based, at least in part, on one or more user inputs.

12. The computer-readable medium of claim 11, the user inputs comprising a maximum number of nodes for a network partition, and a network partition to remain loaded in the memory.

13. The computer-readable medium of claim 1, the method including selectively unloading data associated with a network partition from the memory associated with the processor.

14. The computer-readable medium of claim 1, the method including selectively pre-loading data associated with a second member of the set of network partitions into the memory based, at least in part, on a relationship between the second member and a previously loaded member.

15. The computer-readable medium of claim 1, where the network analysis request includes a user-specified network constraint.

16. A system, comprising:

a first memory to store a data model and to store data associated with a graph, the graph comprising a set of sub-graphs, the graph being described, at least in part, by data associated with the data model, the sub-graphs being described, at least in part, by data associated with the data model;

a second memory to store data associated with a selected sub-graph upon which an analytic function is to be performed;

a load logic to selectively load data associated with a sub-graph into the second memory based, at least in part, on the analytic function to be performed; and

an analytic logic to perform the analytic function on data in the second memory.

17. The system of claim 16, the data model including a graph metadata to describe the graph, a node table to store data describing nodes in the graph, a link table to store data describing graph links, a path table to store data describing graph paths, and a sub-graph table to store data describing graph sub-graphs.

18. The system of claim 16, including:

a dynamic data set logic to identify one or more changes in the graph and to selectively provide data concerning the one or more changes to the load logic.

19. The system of claim 17, including:

a sub-graph logic to create the set of sub-graphs, where creating a sub-graph includes manipulating data associated with the data model and manipulating one or more of, data in the node table, and data in the sub-graph table.

20. The system of claim 16, including:

a user interface logic to communicate inputs including a graph partitioning parameter, a caching policy, and a loading policy;

the user interface logic to communicate outputs including an analytic function result.

21. A system, comprising:

means for storing data concerning a network and a set of network partitions that sub-divide the network;

means for identifying a network partition upon which an analysis function is to be performed;

means for selectively loading data associated with an identified network partition; and

means for performing the analysis function on the selectively loaded data.