Abstract: Methods, apparatus, and systems for efficient partitioning and construction of graphs for scalable high-performance search applications. A method for partitioning a set of ternary keys having one or more wildcards includes analyzing patterns of the set of ternary keys and storing ternary keys with the same pattern in the same subset. The patterns may include uncompressed patterns and compressed patterns. When there are more patterns than a target number of subgraphs, patterns are repeatedly merged until the number of merged patterns matches the target number of subgraphs. Table entries having ternary keys corresponding to the ternary keys in a final set of merged patterns of ternary keys are generated and partitioned into sub-tables, with each sub-table associated with a respective sub-graph. Tables with hundreds of thousands or millions of entries are supported.

Abstract: A method of measuring (100) metrics of a computer network, comprising the steps of: from a data source collecting (110) sets of data points during a sampling time period, wherein the set of data points constitute a sample, and uploading (120) each sample to a server for further processing (130), wherein from each sample, a fractile information instance is produced (131), wherein the fractile information has a type and each data source is associated (110a) with a fractile information type.

Abstract: A system for Partial Unstructured Information Processing, constituting storing, indexing, querying and retrieval of partially specified unstructured data, the system comprising: Quantum Clustering Algorithm that partitions data records in different dusters such that the data in each cluster can be indexed efficiently, a Compressed Ternary Tree that replaces all conceivable indices for each cluster thereby solving the Unthinkable Query Problem for each cluster, and a Virtual Query Processor that converts traditional data base queries to raw Compressed Ternary Tree queries and appropriate filters.

Abstract: A method of measuring (100) metrics of a computer network, comprising the steps of: —from a data source collecting (110) sets of data points during a sampling time period, wherein the set of data points constitute a sample, and uploading (120) each sample to a server for further processing (130), wherein from each sample, a tractile information instance is produced (131), wherein the tractile information has a type and each data source is associated (110a) with a fractile information type.

Abstract: A method of measuring (100) metrics of a computer network, comprising the steps of: —from a data source collecting (110) sets of data points during a sampling time period, wherein the set of data points constitute a sample, and uploading (120) each sample to a server for further processing (130), wherein from each sample, a tractile information instance is produced (131), wherein the tractile information has a type and each data source is associated (110a) with a fractile information type.

Abstract: A system (100) for Partial Unstructured Information Processing, constituting storing, indexing, querying and retrieval of partially specified unstructured data, the system (100) comprising: Quantum Clustering Algorithm (101) that partitions data records in different clusters such that the data in each cluster can be indexed efficiently, a Compressed Ternary Tree (111, 112, 113) that replaces all conceivable indices for each cluster thereby solving the Unthinkable Query Problem (110) for each cluster, and a Virtual Query Processor (120) that converts traditional data base queries to raw Compressed Ternary Tree queries and appropriate filters (121, 122, 123).

Abstract: A method of measuring (100) metrics of a computer network, comprising the steps of: —from a data source collecting (110) sets of data points during a sampling time period, wherein the set of data points constitute a sample, and uploading (120) each sample to a server for further processing (130), wherein from each sample, a tractile information instance is produced (131), wherein the tractile information has a type and each data source is associated (110a) with a fractile information type.

Abstract: A system (100) for Partial Unstructured Information Processing, constituting storing, indexing, querying and retrieval of partially specified unstructured data, the system (100) comprising: Quantum Clustering Algorithm (101) that partitions data records in different clusters such that the data in each cluster can be indexed efficiently, a Compressed Ternary Tree (111, 112, 113) that replaces all conceivable indices for each cluster thereby solving the Unthinkable Query Problem (110) for each cluster, and a Virtual Query Processor (120) that converts traditional data base queries to raw Compressed Ternary Tree queries and appropriate filters (121, 122, 123).

Abstract: The disclosure relates to a static packet classification engine for data packet classification in a data communications network. There is disclosed a static packet classification engine configured to handle rules comprising wildcards and interval matching which is cell tree forest based configured to search clusters to produce results and comprise a priority encoder configured to process the results in terms of matches.

Abstract: The invention is related to a method, apparatus and a computer program product for data mining and more particularly, but without limitation, including data mining for processing business intelligence reports, which efficiently represent the data records in a way that minimizes storage of redundant information and at the same time enables extremely efficient construction of breakdowns, efficiently represent breakdowns with minimum memory overhead and at the same time facilitate efficient traversal of the tree structures represented to enable fast generation of reports and manage update of the data records to minimize the impact on existing breakdowns as well as minimize the computations required to update reports to reflect the changes after an update.

Abstract: Static packet classification engine (10) configured to handle rules comprising wildcards and interval matching, which is cell tree forest based configured to search clusters to produce results (5) and comprise a priority encoder (7) configured to process the results (5).

Abstract: A method for managing multi-layered data structures in a pipelined memory architecture, comprising the steps of: —providing a multi-level data structure where each level corresponds to a memory access; —storing each level in a separate memory block with respect to the other levels. In this way, a more efficient usage of memory is achieved.

Abstract: The present invention pertains to a method for performing specific data forwarding actions depending on the nature of data traffic comprising data packets, which method comprises the steps of: —receiving incoming data traffic of a specific nature, belonging to at least a specific class among a number of pre-defined classes, step 101—classifying the data traffic by determining the nature of the data traffic, step 102, provided by a process of inspecting values of one or more selected header field(s) of an address space of a data packet and selecting a first matching class from an ordered list of classes providing multi-dimensional classification, step 103.

Abstract: The present invention pertains to a method for performing specific data forwarding actions depending on the nature of data traffic comprising data packets, which method comprises the steps of:—receiving incoming data traffic of a specific nature, belonging to at least a specific class among a number of pre-defined classes, step 201—classifying the data traffic by determining the nature of the data traffic, provided by a process of inspecting values of a plurality of selected header field(s) of an address space of a data packet, said process providing an input key, step 202, and comprising the step of compressing the rules in the classifier to a list of compressed rules such that the number of bits involved in classification is reduced, step 203, further selecting a first matching class from an ordered list of n rules that identify each class, wherein each rule comprises D fields, step 204 and a preprocessing algorithm for building a decision tree based on the structure of the classifier, said preprocessing al

Abstract: The present invention relates to a method for representing a partition of n w-bit intervals associated to d-bit data in a data communications network, said method comprising the steps of: providing in a memory (102), a datagram forwarding data structure (10) provided for indicating where to forward a datagram in said network, which data structure (10) is in the form of a tree comprising at least one leaf (11) and possibly a number of nodes (13) including partial nodes, said data structure (10) having a height (h), corresponding to a number of memory accesses required for looking up a largest stored non-negative integer smaller than or equal to a query key, step 201, reducing worst storage cost by using a technique for reduction of worst case storage cost that are selectable from: partial block tree compaction, virtual blocks, bit push pulling, block aggregation or split block trees, and variations thereof, step 202, updating the layered data structure partially including by using a technique for scheduling ma

Abstract: The present invention relates to a method for routing in a data communications network, said method comprising the steps of: providing in a memory (102), a datagram forwarding data structure (10) provided for indicating where to forward a datagram in said network, which data structure (10) is in the form of a tree comprising at least one leaf (11) and possibly a number of nodes (13) including partial nodes, said data structure (10) having a height (h), corresponding to a number of memory accesses required for looking up a largest stored non-negative integer smaller than or equal to a query key, step 201, reducing worst storage cost by using a technique for reduction of worst case storage cost that are selectable from: partial block tree compaction, virtual blocks, bit push pulling, block aggregation or split block trees, and variations thereof, step 202, updating the layered data structure partially including by using a technique for scheduling maintenance work that are selectable from: vertical segmentation

Abstract: A method for memory management in a mass storage device, comprising the steps of providing a managed memory area (stockling) of s blocks that can be moved and stored in two parts to prevent fragmentation; repeatedly moving each of stockpiles 1,2, . . . , i-1 one block to the right until all stockpiles to the right of stockpile i have moved si blocks, or the left part of the rightmost stockling to the end of the free area (without changing the order between the blocks); returning the contiguous si blocks area beginning where the rightmost stockling began before its leftmost part was moved; locating the rightmost stockling that is stored in one piece (it is either the rightmost stockling itself or the stockling to the left of the rightmost stockling) and moving it to the location of the stockling to be deallocated, and reversing the allocation procedure.

Abstract: A method for managing multi-layered data structures in a pipelined memory architecture, comprising the steps of:—providing a multi-level data structure where each level corresponds to a memory access;—storing each level in a separate memory block with respect to the other levels. In this way, a more efficient usage of memory is achieved.

Abstract: The present invention relates to a method for routing in a data communications network, comprising the steps of providing in a storage having a certain amount of storage capacity, a datagram forwarding data structure provided for indicating where to forward a datagram in said network, which data structure is in the form of a block tree, or fixed stride trie, comprising at least one leaf and possibly a number of nodes including partial nodes, said data structure having a height, corresponding to a number of memory accesses required for lookup in an arbitrary partition comprising n intervals, step 201 reducing worst storage cost by using a technique for reduction of worst case storage cost that are selectable from: partial block tree compaction, virtual blocks, bit push pulling, block aggregation or split block trees, and variations thereof, step 202 updating the layered data structure partially by using a technique for scheduling maintenance work that are selectable from: vertical segmentation and bucket list

Abstract: The present invention relates to a method for routing in a data communications network, said method comprising the steps of: providing in a memory (102), a datagram forwarding data structure (10) provided for indicating where to forward a datagram in said network, which data structure (10) is in the form of a tree comprising at least one leaf (11) and possibly a number of nodes (13) including partial nodes, said data structure (10) having a height (h), corresponding to a number of memory accesses required for looking up a largest stored non-negative integer smaller than or equal to a query key, step 201, reducing worst storage cost by using a technique for reduction of worst case storage cost that are selectable from: partial block tree compaction, virtual blocks, bit push pulling, block aggregation or split block trees, and variations thereof, step 202, updating the layered data structure partially including by using a technique for scheduling maintenance work that are selectable from: vertical segmentation