British Telecommunications Public Limited Company

Kjeld Jensen

Stephen A Cassidy

Botond Virginas

David M Rohlfing

Gilbert Kwame Owusu

Carla Di Cairano-Gilfedder

Phil Bull

David Rohlfing

This invention provides a computer-implemented method of modifying an algorithm operating on a computing system, and a device for implementing said method, the method comprising the steps of: applying the algorithm to a first set of inputs; determining a relevance score for a first input of the first set of inputs based on: a first effectiveness value of the first input, wherein the first effectiveness value represents a contribution of first input to the algorithm, and a first computational cost of the first input, wherein the 1 first computational cost represents the computational resources of using the first input in the algorithm; defining a second set of inputs based on the determined relevance score of the first input; and applying the algorithm to the second set of inputs.

Computer-implemented method of modifying an algorithm operating on a computing system

This disclosure relates to a computer-implemented method of controlling an algorithm, and a device for implementing said method, the method including developing the algorithm from a first state to a second state by a machine learning process; determining a second computational cost of executing the algorithm in its second state; determining if the second computational cost satisfies a trigger condition; and, if so, consolidating the algorithm from the second state to a third state, wherein a third computational cost of executing the algorithm in its third state is less than the second computational cost.

Algorithm consolidation

This invention provides an autonomic method for controlling an algorithm on a multi-terminal computing system, wherein the algorithm is configured to analyse diagnostic data for each terminal and an outcome of the analysis is a first action or a second action, and a device for implementing the method, the method comprising the steps of: receiving a first set of data for the multi-terminal computing system; applying the algorithm to the first set of data to classify each terminal in the multi-terminal computing system as being associated with either a first action or second action; re-classifying a first subset of terminals classified as being associated with the first action as being associated with the second action; and applying the first actions, second actions, and reclassified second actions respectively to each terminal in the multi-terminal computing system.

Autonomic method for managing a computing system

A data management process determines, from user-implemented provisional reservations () for data processing resources, a projected total capacity requirement for each said data processing resource, by maintaining a record () recording previous such reservations made by each user and comparing each reservations with records () of the actual resources used, to provide an estimate of resources required to meet the projected capacity requirement, and to provide data for a demand management processor (), which control associated configurable data processing equipment () to provide the resources required to meet the estimated capacity required. The process takes account of over- and under-ordering of capacity by comparing each reservation () with the use actually made (), and includes a record () of ad-hoc (unreserved) usage.

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London, United Kingdom

Kjeld Jensen