METHOD AND APPARATUS TO SUPPORT APPLICATION AND NETWORK AWARENESS OF COLLABORATIVE APPLICATIONS USING MULTI-ATTRIBUTE CLUSTERING

• US 20090292802A1
• Filed: 08/04/2009
• Published: 11/26/2009
• Est. Priority Date: 12/01/2003
• Status: Active Grant

• Current Assignee: George V. Popescu, Sambit Sahu, Zhen Liu
• Original Assignee: George V. Popescu, Sambit Sahu, Zhen Liu
• Inventors: Liu, Zhen, Popescu, George V., Sahu, Sambit
• Granted Patent: US 7,975,039 B2
• Time in Patent Office: Days
• US Class Current: 709/223
• CPC Class Codes: H04L 41/00 Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
• CPC Class Codes: H04L 69/329 in the application layer [OSI layer 7]

Abstract

A method of clustering communication nodes based on network attributes such as network delays and forwarding capacity; on communication interest attributes; and on application attributes such as quality of service preferences/constraints in providing communications between users and application servers. A multi-attribute communication feature vector is formed. That vector is comprised of network attributes, communication interests attributes, and quality of service requirements and is used to form efficient group communication mechanisms for distributed collaborative applications. Then the multi-attribute communication feature vectors are clustered. The clustering methods for multi-type attribute feature vectors are: iterative clustering using a generalized distance space with normalized attribute subspace metrics; fusion clustering, and nested clustering.

Claims

1. A method of clustering network nodes comprising:

using a processor to perform steps comprising;

forming network attribute maps of network constraints;

forming a communication interest space map of application constraints;

extracting feature vectors from the communication interest space map;

extracting network feature vectors from the network attribute maps;

obtaining network quality of service constraints; and

forming a list of labeled nodes based on the network and the application constraints.

2. The method of claim 1, wherein forming network attribute maps comprises:

forming delay maps from measured network delays;

forming a path loss map based on network path losses;

forming a bandwidth map based on bandwidths of the network nodes; and

forming a forwarding capacity map based on forwarding capacities at the network nodes.

3. The method of claim 1, wherein the clustering is based on the feature vectors and on network quality of service constraints.

4. A computer readable storage medium containing an executable program for clustering a multi-type vector space, where the program performs steps comprising:

forming network attribute maps of network constraints;

forming a communication interest space map of application constraints;

extracting feature vectors from the communication interest space map;

extracting network feature vectors from the network attribute maps;

obtaining network quality of service constraints; and

forming a list of labeled nodes based on the network and the application constraints.

5. The computer readable storage medium of claim 4, wherein forming network attribute maps includes the steps of:

forming delay maps from measured network delays;

forming a path loss map based on network path losses;

forming a bandwidth map based on bandwidths of the network nodes; and

forming a forwarding capacity map based on forwarding capacities at the network nodes.

6. The computer readable storage medium of claim 4, wherein the clustering is based on the feature vectors and on network quality of service constraints.

7. Apparatus for clustering a multi-type vector space, comprising:

means for forming network attribute maps of network constraints;

means for forming a communication interest space map of application constraints;

means for extracting feature vectors from the communication interest space map;

means for extracting network feature vectors from the network attribute maps;

means for obtaining network quality of service constraints; and

means for forming a list of labeled nodes based on the network and the application constraints.