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1. 发明申请

US20220100739A1 DISTRIBUTED SEQUENTIAL TRANSACTIONAL DATABASE SELECTION 有权
公开(公告)号：US20220100739A1
公开(公告)日：2022-03-31
申请号：US17593622
申请日：2020-03-18
申请人： BRITISH TELECOMMUNICATIONS PUBLIC LIMITED COMPANY
发明人： Jonathan ROSCOE , Alexander HEALING , Daniel JOSHUA
IPC分类号： G06F16/23
摘要： A computer implemented method of provisioning a distributed sequential transactional database for a software application. The method includes receiving a descriptor for the application specifying characteristics of the database required for the application, accessing a registry of distributed sequential transactional databases and filtering the registry based on the descriptor to define a subset of databases, accessing each of at least some of the databases in the subset to verify an extent to which each accessed database complies with the characteristics in the descriptor, and associating a degree of compliance with each accessed database, such that databases in a subset of accessed databases having a degree of compliance meeting a threshold degree of compliance are determined to be compliant databases, and ranking the compliant databases in terms of the degree of compliance to select a database for access by the application.

2. 发明申请

US20220147513A1 CONFIGURING DISTRIBUTED SEQUENTIAL TRANSACTIONAL DATABASES 有权
公开(公告)号：US20220147513A1
公开(公告)日：2022-05-12
申请号：US17593623
申请日：2020-03-18
申请人： BRITISH TELECOMMUNICATIONS PUBLIC LIMITED COMPANY
发明人： Jonathan ROSCOE , Alexander HEALING , Joshua DANIEL
IPC分类号： G06F16/23 , G06F16/27
摘要： A computer implemented method of configuring a distributed sequential transactional database for a software application operating with the database. The method including receiving a descriptor for the application specifying characteristics of the database required for the application and accessing the databases to determine an extent to which each the database complies with the characteristics in the descriptor. The method further including, responsive to the determination, identifying one or more attributes of the database for adjustment based on the characteristics in the descriptor so as to improve the extent of compliance of the database with the characteristics in the descriptor, the one or more attributes being determined by a machine learning algorithm trained to categorize database characteristics in terms of suitable adjustments, and adjusting the database in accordance with the determined attributes.

3. 发明申请

US20180198718A1 NETWORK OPERATION 审中-公开
公开(公告)号：US20180198718A1
公开(公告)日：2018-07-12
申请号：US15563018
申请日：2016-03-30
申请人： BRITISH TELECOMMUNICATIONS PUBLIC LIMITED COMPANY
发明人： Michael TURNER , Alexander HEALING
IPC分类号： H04L12/851 , H04L12/24
CPC分类号： H04L47/2441 , H04L41/0631 , H04L41/0816 , H04L41/145 , H04L41/28
摘要： A method of operating a communications network is disclosed. In order to manage a network, it is first necessary to establish the state the network is in. This is difficult in practice because the network operational data stored and transmitted in the network takes a myriad of forms owing to the variety of suppliers and types of network equipment. There is a need to distil that network operational data down to aggregate network operational data which can be taken to provide an indication of the state of the network which is of a manageable size, and to which network management apparatus can react by sending control commands to the network. The problem of generating aggregate network operational data is difficult because of the heterogeneity of network operational data items. By finding attribute names in different network operational data items which match one another, and then comparing attribute values provided from those matching attribute names, a comparison of heterogeneous network operational data items is enabled. This enables the production of network aggregate data which more accurately reflects the operational state of the network. This in turn leads to the network management apparatus controlling the network to operate in a more efficient manner than has hitherto been possible.

4. 发明申请

US20180091377A1 NETWORK OPERATION 审中-公开
公开(公告)号：US20180091377A1
公开(公告)日：2018-03-29
申请号：US15562682
申请日：2016-03-30
申请人： BRITISH TELECOMMUNICATIONS PUBLIC LIMITED COMPANY
发明人： Michael TURNER , Alexander HEALING
IPC分类号： H04L12/24 , H04L29/06
CPC分类号： H04L41/142 , H04L41/18 , H04L63/1408 , H04L63/20
摘要： A method of operating a communications network is disclosed. In order to manage a network, it is first necessary to establish the state the network is in. This is difficult in practice because the network operational data stored and transmitted in the network takes a myriad of forms owing to the variety of suppliers and types of network equipment. There is a need to distil that network operational data down to aggregate network operational data which can be taken to provide an indication of the state of the network which is of a manageable size, and to which network management apparatus can react by sending control commands to the network. The problem of generating aggregate network operational data is tackled by identifying the type of each attribute found in each network operational data item, and classifying the network operational data items in a manner which takes account of the identified types and thus provides network aggregate data which more accurately reflects the operational state of the network. This in turn leads to the network management apparatus controlling the network to operate in a more efficient manner than has hitherto been possible.

5. 发明公开

US20240283806A1 NETWORK ANOMALY DETECTION 审中-公开
公开(公告)号：US20240283806A1
公开(公告)日：2024-08-22
申请号：US18581779
申请日：2024-02-20
申请人： BRITISH TELECOMMUNICATIONS PUBLIC LIMITED COMPANY
发明人： Michael GIBSON , Alexander HEALING , Aditya MANOCHA
IPC分类号： H04L9/40
CPC分类号： H04L63/1425 , H04L63/1441
摘要： A computer-implemented method of training a network anomaly detection system is disclosed. The method involves generating synthetic benign network data and synthetic anomalous network data and combining the synthetic benign network data and synthetic anomalous network data to generate combined synthetic network data having a predetermined density of anomalous network data. The combined synthetic network data is provided to a trained anomaly detection model, and an accuracy score is determined that is representative of how accurately the trained anomaly detection model recognizes anomalous activity in the combined synthetic network data. If the accuracy score is less than a threshold value, the anomaly detection model is trained with additional network data and a new accuracy score is determined. Otherwise, the predetermined density of anomalous network data is reduced and a new accuracy score is determined until a predetermined stopping criterion is met.

6. 发明公开

US20240078424A1 NEURAL NETWORK ARRANGEMENT 审中-公开
公开(公告)号：US20240078424A1
公开(公告)日：2024-03-07
申请号：US18258761
申请日：2021-12-01
申请人： BRITISH TELECOMMUNICATIONS PUBLIC LIMITED COMPANY
发明人： Robert HERCOCK , Alexander HEALING
IPC分类号： G06N3/08
CPC分类号： G06N3/08
摘要： A computer implemented method of a machine learning algorithm modelling a target function mapping inputs in an input domain to outputs in an output range, the machine learning algorithm including an array of processing nodes arranged in a network of layers of nodes including an input layer for receiving an input value, an output layer for providing an output value, and one or more intermediate layers between the input and output layers, each node in the processing set being outside the input layer receiving input from at least some adjacent nodes logically closer to the input layer via weighted connections between nodes, and each node being outside the output layer generating output to at least some adjacent nodes logically closer to the output layer via weighted connections between nodes, wherein each node includes: an adjustable weight for application to each input to the node, the adjustment weight being responsive to a threshold function applied to a value of the node input; a combination function for combining outputs of the threshold function; and a node bypass function for selectively mapping one or more of the inputs to the node to the output of the node, the method comprising iteratively training the machine learning algorithm to model the target function by adjustment, at each iteration, of at least weights of connections between at least a subset of the nodes, such that the nodes of the network are programmable during operation of the algorithm by adjustment of the threshold function and the bypass function so as to selectively emphasise subsets of nodes in the network.

7. 发明申请

US20200301922A1 MULTIFORM PERSISTENCE ABSTRACTION 审中-公开
公开(公告)号：US20200301922A1
公开(公告)日：2020-09-24
申请号：US16086186
申请日：2017-03-03
申请人： British Telecommunications Public Limited Company
发明人： Alexander HEALING , Paul FAGAN , Michael TURNER
IPC分类号： G06F16/2458 , G06F16/248 , G06F16/25 , G06F16/23 , G06F9/448
摘要： A computer implemented method of data access to data stored in one or more data stores includes receiving a request to retrieve data from the one or more data stores; extracting characteristics of the request to classify the request according to a request classification; identifying a model for execution of one or more queries to one or more data stores; executing the one or more queries according to the model to formulate a response to the request, wherein the model for execution is identified based on a class of the request and includes an identification of one or more data stores to which the one or more queries are to be directed to formulate the response; and monitoring execution of one or more queries for a class of request and revising the model in accordance with predetermined criteria.

8. 发明申请

US20180227190A1 NETWORK OPERATION 审中-公开
公开(公告)号：US20180227190A1
公开(公告)日：2018-08-09
申请号：US15749151
申请日：2016-07-28
申请人： BRITISH TELECOMMUNICATIONS PUBLIC LIMITED COMPANY
发明人： Alexander HEALING , Michael TURNER
IPC分类号： H04L12/24 , H04L29/06 , G06F17/30
CPC分类号： H04L41/142 , G06F16/285 , G06F16/355 , H04L63/1425
摘要： A method of operating a communications network is disclosed. Modern communications networks produce vast amounts of network operational data which have the potential to provide a useful summary of the operational state of the network. Whilst processes such as clustering are known for arranging the vast amount of data into groups, the clusters themselves do not provide data which might be easily interpreted by network elements or administrators. Network operational data often comprises a plurality of data items, each of which gives a value for each of a set of attributes. By processing a cluster to identify attributes in the cluster whose values vary less in the cluster then they vary outside of the cluster, and then generating a cluster description which is based on a measure of the central tendency of the values of those attribute in the cluster, an easily interpretable general description of the data items in the cluster is provided. The easily interpretable general description of the cluster can then be used to relatively identify data items similar to those present in the cluster (e.g. from a larger database of data items), and elements in the network can then act autonomously on the basis of the cluster description to control the operation of the communications network.

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