Aidong Zhang

US Patent:

7808921, Oct 5, 2010

Filed:

May 18, 2007

Appl. No.:

11/804700

Inventors:

Aidong Zhang - Getzville NY, US
Murali Ramanathan - Amherst NY, US

Assignee:

The Research Foundation of State University of New York - Amherst NY

International Classification:

H04L 12/26
H04L 12/28

US Classification:

370252

Abstract:

A method for identifying a bridge node in a network using a processor and memory unit in a specially programmed special purpose-purpose computer including the steps of, for each node in a plurality of nodes in the network: determining a global metric proportional to total traffic flow in the network and through the node; determining a local metric proportional to traffic flow between the node and each second node in the network connected to the node and traffic flow between each second node and each third node in the network connected to a second node; determining a second local metric proportional to the respective traffic flows between each node and each second node; and calculating a respective combination of the global metric and the first and second local metrics; and selecting, a bridge node from among the plurality of nodes based on the respective combinations.

US Patent:

6882997, Apr 19, 2005

Filed:

Aug 24, 2000

Appl. No.:

09/645630

Inventors:

Aidong Zhang - Getzville NY, US
Gholamhosein Sheikholeslami - Buffalo NY, US
Surojit Chatterjee - Mountain View CA, US

Assignee:

The Research Foundation of SUNY at Buffalo - Amherst NY

International Classification:

G06F017/30

US Classification:

707 6, 7071041, 707103 R, 382225

Abstract:

The method termed WaveCluster for mining spatial data. WaveCluster considers spatial data as a multidimensional signals and applies wavelet transforms, a signal-processing technique, to convert the spatial data into the frequency domain. The wavelet transforms produce a transformed space where natural clusters in the data become more distinguishable. The method quantizes a feature space to determine cells of the feature space, assigns objects to the cells, applies a wavelet transform on the quantized feature space to obtain a transformed feature space, finds connected clusters in sub bands at different levels of the transformed feature space, assigns labels to the cells, creates a look-up table, and maps the objects to the clusters. The method can manage spatial data in a two-dimensional feature space. The method also is applicable to a feature space that is made up of an image taken by a satellite.