International Business Machines Corporation

Juniper Networks, Inc.

Sonus Networks, Inc.

Iqlect Software Solutions Pvt Ltd.

Rajeev Gupta

Sriram Kolinjivadi Padmanabhan

Himanshu Gupta

Mukesh Kumar Mohania

Prasan Roy

Prasad Manikarao Deshpande

Manoj Kumar Agarwal

Sanjeev K Gupta

Ullas Balan Nambiar

Atreyee Dey

Natwar Modani

Laurent Sebastien Mignet

Salil Joshi

Prasad V

Samta Rangare

Padmashree Ravindra

Manish Anand Bhide

Guy Maring Lohman

Ravi Shekhar

Mark Francis Wilding

Sankar Ramamoorthi

Sriram Raghavan

Nagesh Kumar Bollapalli

Apurva Kumar

Kaushik Dutta Majumdar

Venkata Rajasekharu Athreyapurapu

Ashu Gupta

Tanveer Fathima Mahmood

Mahesh Dhabade

Sachin Sinha

Mohan Kumar A P

Anish Sharma

Sandeep Patel

Pranav Koushik

Mangesh Kute

An example network device includes a memory configured to store a plurality of counts of packets of a data flow. The network device also includes one or more processors in communication with the memory. The one or more processors are configured to determine the plurality of counts of packets of the data flow, wherein each count of the plurality of counts includes a number of packets occurring in a predetermined time period. The one or more processors are configured to assign a corresponding range to each count of the plurality of counts, so as to assign a plurality of corresponding ranges. The one or more processors are also configured to determine a pattern in the plurality of corresponding ranges and send a number of active probe packets based on the determined pattern.

Synthesizing probe parameters based on historical data

Techniques are described for policy driven on-demand tunnel creation and deletion between end points in a software-defined wide area network (SD-WAN) having a hub-and-spoke topology. A software-defined networking (SDN) controller that facilitates cloud-based services of a service provider network that sets up the SD-WAN is configured to determine whether a tunnel between end-points is to be created or deleted based on information indicative of the traffic, such as amount, time, application generating the traffic, and the like, between end-points.

Policy-driven on-demand tunnel creation/deletion based on traffic information in a wide area network (WAN)

The present disclosure provides a method and system for a scalable complex event processing of event streams. The method includes reception of one or more input event streams and collection of one or more output event streams. Further, the method includes modeling of each instance of each input event stream and each instance of the plurality of instances for intermediate states as records of a database table. The method includes indexing of each record of the database table and distribution of a first set of records in temporary memory and the second set of records in one or more persistent storage devices. The method includes flushing the second set of records of the database table in one or more persistent storage devices and querying of the plurality of records of the database table. The method includes inferring one or more complex events from transition of a plurality of states.

Method and system for scalable complex event processing of event streams

Entity mappings that produce matching entities for a first data asset having attributes and a second data asset having attributes are generated by: generating entity mappings that produce matching entities for a first data asset having attributes with attribute values and a second data asset having attributes with attribute values by: matching the attribute values of the attributes of the first data asset with the attribute values of the attributes of the second data asset, using the matching attribute values to generate matching attribute pairs, and using the matching attribute pairs to identify entity mappings; computing an entity mapping score for each of the entity mappings based on a combination of factors; ranking the entity mappings based on each entity mapping score; and using some of the ranked entity mappings to determine whether a same real-world entity is described by the first data asset and the second data asset.

Identifying entity mappings across data assets

Methods, systems, and computer program products for distributed iceberg cubing over ordered dimensions are provided herein. A method includes calculating, from input data derived from a search query, a set of multiple cube measures for one or more combinations of multiple non-ordered dimensions; pruning the set of multiple cube measures based on one or more iceberg conditions to generate a sub-set of the cube measures; and determining a range for a set of ordered dimensions over a distributed processing platform based on (i) the sub-set of the cube measures and (ii) the one or more iceberg conditions.

Distributed iceberg cubing over ordered dimensions

Methods and arrangements for identifying related data in different data sets to assist in searching the data sets. A first data asset and a second data asset are accessed. Common entities are identified between the first and second data assets. A score is determined for the relationship between the first and second data assets, based on the identified common entities. One or more relationship contexts are determined for the relationship between the first and second data assets, and the relationship score and one or more relationship contexts are used to join at least a portion of each of the first and second data assets as a basis for subsequent searching. Other variants and embodiments are broadly contemplated herein.

Contextualization of entity relationships

Methods and arrangements performing fuzzy search. A contemplated method includes: establishing an edit distance threshold for the fuzzy search; generating an index of items to be searched, via: storing at least one string; and creating substrings corresponding to the at least one string; providing a query string for use in searching; creating substrings corresponding to the query string; comparing substrings of the query string with substrings in the index; designating at least one candidate string based on said comparing; verifying whether each candidate string satisfies the edit distance threshold; and outputting at least one matching string for each candidate string that satisfies the edit distance threshold. Other variants and embodiments are broadly contemplated herein.

Distributed fuzzy search and join with edit distance guarantees

An embodiment provides intermediate data derived in the form of column stores which are in turn based on hierarchical data stores. This intermediate data represents a reduced subset of data matched appropriately to a query (or modified query) such that the amount of data handled in a query processing task on large data is greatly reduced. An embodiment may appropriately choose column data stores and/or modify queries in order leverage parallelization techniques such as map-reduce in order to query large data. The result is the ability to query large data stores in parallel while reducing the amount of data that must be handled.

System and a method for hierarchical data column storage and efficient query processing

A system for receiving a declarative specification including a plurality of stages. Each stage specifies an atomic operation, a data input to the atomic operation, and a data output from the atomic operation. The data input is characterized by a data type. Links between at least two of the stages are generated to create a data integration workflow. The data integration workflow is compiled to generate computer code for execution on a parallel processing platform. The computer code configured to perform at least one of data preparation and data analysis.

Declarative specification of data integration workflows for execution on parallel processing platforms

A method for receiving a declarative specification including a plurality of stages. Each stage specifies an atomic operation, a data input to the atomic operation, and a data output from the atomic operation. The data input is characterized by a data type. Links between at least two of the stages are generated to create a data integration workflow. The data integration workflow is compiled to generate computer code for execution on a parallel processing platform. The computer code configured to perform at least one of data preparation and data analysis.

A method, computer program product, and computer system for shared execution of mixed data flows, performed by one or more computing devices, comprises identifying one or more resource sharing opportunities across a plurality of parallel tasks. The plurality of parallel tasks includes zero or more relational operations and at least one non-relational operation. The plurality of parallel tasks relative to the relational operations and the at least one non-relational operation are executed. In response to executing the plurality of parallel tasks, one or more resources of the identified resource sharing opportunities is shared across the relational operations and the at least one non-relational operation.

System and method for shared execution of mixed data flows

Methods and arrangements for processing hierarchical data in a map-reduce framework. Hierarchical data is accepted, and a map-reduce job is performed on the hierarchical data. This performing of a map-reduce job includes determining a cost of partitioning the data, determining a cost of redefining the job and thereupon selectively performing at least one step taken from the group consisting of: partitioning the data and redefining the job.

Processing hierarchical data in a map-reduce framework

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Noida, India

Rajeev Gupta