Infosys Limited

Invertit

Steven Schilders

Kaustubh Kishor Madke

An overlay system is provided that includes a storage element and processing circuitry. The storage element stores an executable graph-based model that includes node templates, node instances, and index nodes. Each node template is associated with one or more node instances and one or more index nodes. Further, each index node includes index records. The processing circuitry receives a contextualized stimulus associated with the overlay system and identifies one or more index records that include an index value indicated by the contextualized stimulus. Based on the identified one or more index records, the processing circuitry further identifies one or more node instances required for stimulus processing. Further, the processing circuitry executes an operation associated with the stimulus based on the identified one or more node instances and each node template associated with the identified one or more node instances.

Indexing in graph-based models

An overlay system is provided that includes a primary storage element, a plurality of auxiliary storage elements, and processing circuitry. The primary storage element stores an executable graph-based model having a plurality of nodes. The processing circuitry receives a first stimulus indicative of a data splintering instruction. Based on the first stimulus, the processing circuitry identifies a first node in the executable graph-based model and executes a data splintering operation on the first node to divide the first node into a plurality of splinters. The processing circuitry, based on the first stimulus, instantiates a plurality of location overlay nodes and associates the plurality of location overlay nodes with the plurality of splinters. Based on the association, the processing circuitry stores each splinter of the plurality of splinters in an auxiliary storage element indicated by a corresponding location overlay node.

Data splintering in graph-based models

An overlay system provided, includes processing circuitry and storage circuitry that stores primary executable graph-based models and auxiliary executable graph-based models. Each primary executable graph-based model is mapped to one or more auxiliary executable graph-based models based on various rules. The processing circuitry receives a stimulus associated with the overlay system and identifies, based on the stimulus, a primary executable graph-based model and one or more rules. Further, one or more values associated with an auxiliary executable graph-based model that is mapped to the primary executable graph-based model are retrieved based on the one or more rules. One or more values associated with the primary executable graph-based model are populated based on the retrieved one or more values. The processing circuitry further executes an operation associated with the stimulus based on the primary executable graph-based model that is populated with the one or more values.

In-situ ontology mapping in overlay systems

A method for access management in graph-based model is provided. The graph-based model comprises a plurality of nodes and an overlay structure comprising processing logic. The overlay structure is associated with one or more nodes of the plurality of nodes. Processing circuitry determines a first node group of the graph-based model. The first node group comprises at least one node. The processing circuitry associates a first contract with the first node group such that the first contract is configured to act as a proxy for one or more nodes within the first node group in relation to requests from outside the first node group. The processing circuitry receives a stimulus and a context associated therewith. The stimulus is associated with the first contract. The processing circuitry maps the stimulus to the first contract to determine an access response. The processing circuitry processes the stimulus based on the access response.

Systems and methods for contracts in graph-based models

A method for dynamic execution of sub-graphs within executable graph-based models is provided. Processing circuitry obtains an executable graph-based model comprising a plurality of sub-graphs and an overlay structure comprising processing logic associated with the plurality of sub-graphs. Each sub-graph defines a hierarchical structure of related nodes. The processing circuitry receives a stimulus and a context associated with the stimulus. In response to the stimulus being received and based on the context, the processing circuitry maps the stimulus to a first sub-graph of the executable graph-based model. The processing circuitry causes execution of processing logic within the overlay structure based on the mapping. The processing logic is associated with one or more nodes of the first sub-graph.

Systems and methods for sub-graph processing in executable graph-based models

A system for executing a search in a dataset is provided. The system includes a storage element that stores a directed property graph derived from the dataset. The directed property graph includes entity vertices corresponding to entities of the dataset, edges corresponding to properties of the entities, and value vertices corresponding to data values of the properties. Each edge couples an entity vertex to a value vertex and includes a label indicating an association therebetween. The system further includes processing circuitry that receives a search query including a reference value. The processing circuitry identifies a value vertex having a data value that is associated with the reference value and generates a response to the search query based on labels of edges coupled to the value vertex, and entities of the dataset represented by entity vertices coupled to the value vertex by way of the edges.

System and method for executing searches using directed property graphs

An overlay system is provided that includes a plurality of storage elements and processing circuitry coupled thereto. The plurality of storage elements store a plurality of executable graph-based models such that first and second storage elements store first and second executable graph-based models, respectively. Each executable graph-based model includes a plurality of nodes. The processing circuitry receives a stimulus to share a first node of the first executable graph-based model with a second node of the second executable graph-based model. The processing circuitry instantiates a tenant overlay node that is associated with the second node and includes a set of constraints to be adhered to by the second node while sharing the first node. The processing circuitry creates a sharing channel as a medium between the first and second storage elements. The sharing channel and the tenant overlay node enable sharing of the first node with the second node.

In-situ tenancy in graph-based models

An overlay system including a storage element and processing circuitry is provided. The storage element stores an executable graph-based model that includes various active nodes and various micro-overlay nodes. Further, each active node includes multiple node elements, where each micro-overlay node is associated with at least one node element, and extends the functionality of the corresponding node element. The processing circuitry receives a contextualized stimulus. Further, the processing circuitry identifies an active node, node elements of the active node associated with the processing of the contextualized stimulus, and one or more micro-overlay nodes associated with each identified node element. The processing circuitry executes an operation associated with the contextualized stimulus based on the identified node elements and one or more micro-overlay nodes associated with each identified node element.

In-situ data processing in overlay systems using micro-overlays

A system comprises an executable graph-based model. The executable graph-based model comprises a first overlay node. The first overlay node comprises processing logic that is operable to interact with one or more associated nodes of the executable graph-based model. Further, the executable graph-based model comprises a first node that has the first overlay node associated therewith. The system further comprises a processing unit configured to receive a first stimulus associated with the first overlay node and, in response to the first stimulus being received, cause execution of said processing logic of the first overlay node. Execution of said processing logic of the first overlay node is based on the first node.

Systems and methods for in-situ graph-based data processing

An overlay system is provided that includes a storage element and processing circuitry coupled thereto. The storage element stores an executable graph-based model including a plurality of nodes, a plurality of rule overlay nodes, and a plurality of data analysis overlay nodes. The processing circuitry receives a stimulus indicative of a data analysis operation and identifies a first node, a rule overlay node associated with the first node, and a data analysis overlay node associated with the first node. The processing circuitry executes a set of rules associated with the rule overlay node on a composition of the first node to generate a set of outputs. The data analysis overlay node uses the set of outputs to determine whether a data analysis score associated with the first node exceeds a data analysis score threshold.

In-situ data analysis in graph-based models

A method discloses obtaining a node template comprising a predetermined node structure and rules governing generation of node instances based on the node template. Data elements are received. A run-time node is generated in response to the reception of the data elements. The run-time node comprises the node template and a node instance. The node instance comprises the data elements mapped to the node template based on the rules of the node template. A run-time overlay comprising an overlay template and an overlay instance comprising processing logic implementing at least one generic rule of the overlay template are obtained. The executable run-time node is generated. It comprises a composition of the run-time node and the run-time overlay such that the processing logic of the run-time overlay is operable to interact with the run time node during execution of the executable run-time node.

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Columbus, IN, United States of America

Steven Schilders