Abstract: A system for and method of, increasing provisionable bandwidth in a multiplexed communication link and a network management system incorporating the system or the method. In one embodiment, the system includes: (1) a defragmentation calculator that calculates a defragmentation of the communication link, the defragmentation containing at least one granularity, (2) a candidate slot selector, associated with the defragmentation calculator, that finds reduced cost candidate slots for the at least one granularity and (3) a circuit mover, associated with the candidate slot selector, that identifies target slots into which circuits occupying the candidate slots can be moved.

Abstract: A method for data path provisioning in a reconfigurable data network is disclosed. A data path between a source IP router and a destination IP router is determined taking into account the IP-subnets of the network interfaces of the IP routers included in the path. In one embodiment, the requirement that two IP routers can send packets via their connected interface if and only if the two interfaces are on the same subnet (i.e., the subnet constraint) is completely honored during the data path determination. In another embodiment, the data path is determined while allowing some number of violations of the subnet constraint. A transform network graph is computed and is used to determine the data path taking into account the IP-subnets.

Abstract: The present invention is an apparatus and method for classifying high-dimensional sparse datasets. A raw data training set is flattened by converting it from categorical representation to a boolean representation. The flattened data is then used to build a class model on which new data not in the training set may be classified. In one embodiment, the class model takes the form of a decision tree, and large itemsets and cluster information are used as attributes for classification. In another embodiment, the class model is based on the nearest neighbors of the data to be classified. An advantage of the invention is that, by flattening the data, classification accuracy is increased by eliminating artificial ordering induced on the attributes. Another advantage is that the use of large itemsets and clustering increases classification accuracy.

Abstract: A method and apparatus for managing and updating distributed directory objects is disclosed. The object oriented directory has a schema which has a first and second class. The schema has a schema engine which contains the method for managing and updating the distributed directory objects utilizing semantic and structural comparisons. The schema engine utilizes and updates the first and second classes of the object oriented directory.

Abstract: A method and system for generating a decision-tree classifier from a training set of records, independent of the system memory size. The method includes the steps of: generating an attribute list for each attribute of the records, sorting the attribute lists for numeric attributes, and generating a decision tree by repeatedly partitioning the records using the attribute lists. For each node, split points are evaluated to determine the best split test for partitioning the records at the node. Preferably, a gini index and class histograms are used in determining the best splits. The gini index indicates how well a split point separates the records while the class histograms reflect the class distribution of the records at the node. Also, a hash table is built as the attribute list of the split attribute is divided among the child nodes, which is then used for splitting the remaining attribute lists of the node.