Abstract: According to a first aspect of the invention, there is provided a system for optimising data communication between devices connected to a network, the system including: a server configured to: measure application performance metrics of the data communication between the devices; compare the application performance metrics against performance requirements; detect, in response to the application performance metrics being below the performance requirements, nodes having untapped computing resources within the network; determine operation parameters achieving service at the performance requirements; command one or more of the nodes to function at the operation parameters; and migrate at least a portion of workload associated with the data communication amongst the one or more nodes commanded to function at the operation parameters.

Abstract: Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons.

Abstract: Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons.

Abstract: According to a first aspect of the invention, there is provided a system for optimising data communication between devices connected to a network, the system including: a server configured to: measure application performance metrics of the data communication between the devices; compare the application performance metrics against performance requirements; detect, in response to the application performance metrics being below the performance requirements, nodes having untapped computing resources within the network; determine operation parameters achieving service at the performance requirements; command one or more of the nodes to function at the operation parameters; and migrate at least a portion of workload associated with the data communication amongst the one or more nodes commanded to function at the operation parameters.

Abstract: The invention is directed towards a database access coordination arrangement (23) in a federated database system (10) comprising applications (Ai, A2, A3) that access databases (34-50) under the control of a number of query handlers (24-32), the database access coordinating arrangement providing a group of traffic distribution units (16-22), each having connections to corresponding query handlers, and a traffic control unit (TCU), which traffic control unit selects traffic distribution unit for a query (Qi) from an application (Ai) based on at least one connectivity map of the connections existing between traffic distribution units, query handlers and databases and connectivity states of connections between traffic distribution units and query handlers, and schedules the query to the selected traffic distribution unit for accessing a database.

Abstract: Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons.

Abstract: Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons.

Abstract: Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons.

Abstract: Approaches, techniques, and mechanisms are disclosed for generating, enhancing, applying and updating knowledge neurons for providing decision making information to a wide variety of client applications. Domain keywords for knowledge domains are generated from domain data of selected domain data sources, along with keyword values for the domain keywords, and are used to generate knowledge artifacts for inclusion in knowledge neurons. These knowledge neurons may be enhanced by domain knowledge data sets found in various data sources and used to generate neural responses to neural queries received from the client applications. Neural feedbacks may be used to update and/or generate knowledge neurons.

Abstract: The present disclosure is directed towards a data storage setting arrangement in a federated database system that includes applications configured to handle data in corresponding databases. The arrangement includes a communication interface for obtaining application requirement data (AIC) related to database usage, a database determining unit for predicting database type using the application requirement data and selecting database based on the database type prediction, a processing type determining unit for predicting database processing type based on the application requirement data and selecting database processing type based on the processing type prediction, a data model creating unit for creating a data model for storing of data in the database based on the application requirement data and an instantiating unit for instantiating a connection between the application and the selected database based on the selected database processing type and data model.

Abstract: Query handling devices in a federated database system and related methods and computer program products for handling queries in the federated database system are disclosed. The query handling device receives database queries directed towards a group of databases from several applications and filters the queries based on common query rules such as common query syntax, investigates the queries that have passed the filtering, and sends the investigated queries to the databases. The investigation includes prioritising between at least some queries according to a query prioritisation scheme. The prioritised queries are sent according to the query prioritisation scheme.

Abstract: A query handling arrangement is disclosed for a federated database system. The database system includes data storing applications configured to store data in corresponding databases. The query handling arrangement includes a query handling device that receives a database query from a query generating application concerning the obtaining of data from the databases, obtains usage profiles regarding allowed use of the data in the databases provided by a usage profile announcing device, investigates the usage profiles, obtains data from the databases according to the obtained usage profiles, and responds to the query with the obtained data.

Abstract: A stream processing handling arrangement provides a number of data handling blocks, selectable for forming a work flow. The blocks comprise data processing blocks. The arrangement receives selections of data handling blocks, block parameter settings and workflow property objectives, and compares the objectives with corresponding stream processing framework capabilities. The arrangement determines a stream processing framework for the work flow, provides a number software module groups, each corresponding to a different framework and comprising software modules corresponding to the data handling blocks, and chooses a group corresponding to the determined stream processing framework. The arrangement selects, in this group, software modules corresponding to the selected blocks and constructs an application using the selected software modules.

Abstract: The formulation of meta-correlation method as a graph based problem is disclosed. The meta-correlation method utilizes one or more correlation techniques, and also captures latent factors critical for the business utility in hand is described. The method also leverages a small example set to bootstrap for the target utility case. The proposed method can easily work for attribute groups of any size, not just attribute groups consisting of pairs of attributes.

Abstract: A method for propagating user preference information in a communications network, in which the user preference information may be available for a subset of users within the network. The method comprises generating individual user attribute vectors, based on user historical data and estimating user preference information. The method further comprises defining a community structure for the network and generating a stacked representation for users, the representation comprising the user attribute vector augmented with an aggregated vector of estimated user preferences of members of the user's community. The method further comprises learning a function relating the stacked representation to user preference, using the subset of users, and applying the learned function to users outside the subset.

Abstract: A stream processing handling arrangement provides a number of data handling blocks, selectable for forming a work flow. The blocks comprise data processing blocks. The arrangement receives selections of data handling blocks, block parameter settings and workflow property objectives, and compares the objectives with corresponding stream processing framework capabilities. The arrangement determines a stream processing framework for the work flow, provides a number software module groups, each corresponding to a different framework and comprising software modules corresponding to the data handling blocks, and chooses a group corresponding to the determined stream processing framework. The arrangement selects, in this group, software modules corresponding to the selected blocks and constructs an application using the selected software modules.

Abstract: The formulation of meta-correlation method as a graph based problem is disclosed. The meta-correlation method utilizes one or more correlation techniques, and also captures latent factors critical for the business utility in hand is described. The method also leverages a small example set to bootstrap for the target utility case. The proposed method can easily work for attribute groups of any size, not just attribute groups consisting of pairs of attributes.

Abstract: The invention is directed towards a database access coordination arrangement (23) in a federated database system (10) comprising applications (Ai, A2, A3) that access databases (34-50) under the control of a number of query handlers (24-32), the database access coordinating arrangement providing a group of traffic distribution units (16-22), each having connections to corresponding query handlers, and a traffic control unit (TCU), which traffic control unit selects traffic distribution unit for a query (Qi) from an application (Ai) based on at least one connectivity map of the connections existing between traffic distribution units, query handlers and databases and connectivity states of connections between traffic distribution units and query handlers, and schedules the query to the selected traffic distribution unit for accessing a database.

Abstract: The present disclosure is directed towards a data storage setting arrangement in a federated database system that includes applications configured to handle data in corresponding databases. The arrangement includes a communication interface for obtaining application requirement data (AIC) related to database usage, a database determining unit for predicting database type using the application requirement data and selecting database based on the database type prediction, a processing type determining unit for predicting database processing type based on the application requirement data and selecting database processing type based on the processing type prediction, a data model creating unit for creating a data model for storing of data in the database based on the application requirement data and an instantiating unit for instantiating a connection between the application and the selected database based on the selected database processing type and data model.

Abstract: The present disclosure is directed towards a connection tuning arrangement for tuning connection parameters of databases in a federated database system. The database system includes a least one application configured to access one or more databases. The connection tuning arrangement includes a data stream monitoring unit configured to monitor a number of application specific parameters in data streams of an application, the monitoring being performed in at least one context, and learn the behaviour of the data streams. A performance tuning unit is configured to tune connection parameters based on the behaviour.