West Malling, United Kingdom
West Malling, United Kingdom

Tieto Oyj is an IT service company providing IT and product engineering services. Active in more than 20 countries with approximately 16,000 employees, Tieto is one of the largest IT service providers in Europe. Tieto is domiciled in Helsinki, Finland, and the company's shares are listed on the NASDAQ OMX Helsinki and Stockholm.The company provides services to the following sectors: financial services; manufacturing, retail & logistics; public, healthcare & welfare; telecom, media and energy.The number of full-time employees amounted to 15,700 at the end of March 2014. Of Tieto's personnel, 33% is located in Finland, 18% in Sweden, 13% in Czech Republic,11% in India, 6% in China, and the rest spread across other countries. 28% of the 14,699 employees worldwide are women. Net sales by country was Finland 48%, Sweden 33%, and International 19%. As of 2013, 50% of Tieto's shareholders are Finnish and 3% are Swedish. Wikipedia.


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Patent
Tieto | Date: 2017-01-04

Improved methods and arrangements for making measurements for load balancing and network management are disclosed for software defined networking components. In a software defined network component a monitoring module is provided in the kernel side of the component. The monitoring module may be used for making measurements in the kernel side or transmitting measurement packets directly to peer entities in other software defined network components.


Grant
Agency: Cordis | Branch: H2020 | Program: ECSEL-IA | Phase: ECSEL-17-2015 | Award Amount: 64.82M | Year: 2016

ENABLE-S3 will pave the way for accelerated application of highly automated and autonomous systems in the mobility domains automotive, aerospace, rail and maritime as well as in the health care domain. Virtual testing, verification and coverage-oriented test selection methods will enable validation with reasonable efforts. The resulting validation framework will ensure Europeans Industry competitiveness in the global race of automated systems with an expected market potential of 60B in 2025. Project results will be used to propose standardized validation procedures for highly automated systems (ACPS). The technical objectives addressed are: 1. Provision of a test and validation framework that proves the functionality, safety and security of ACPS with at least 50% less test effort than required in classical testing. 2. Promotion of a new technique for testing of automated systems with physical sensor signal stimuli generators, which will be demonstrated for at least 3 physical stimuli generators. 3. Raising significantly the level of dependability of automated systems due to provision of a holistic test and validation platform and systematic coverage measures, which will reduce the probability of malfunction behavior of automated systems to 10E-9/h. 4. Provision of a validation environment for rapid re-qualification, which will allow reuse of validation scenarios in at least 3 development stages. 5. Establish open standards to speed up the adoption of the new validation tools and methods for ACPS. 6. Enabling safe, secure and functional ACPS across domains. 7. Creation of an eco-system for the validation and verification of automated systems in the European industry. ENABLE-S3 is strongly industry-driven. Realistic and relevant industrial use-cases from smart mobility and smart health will define the requirements to be addressed and assess the benefits of the technological progress.


Grant
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: SPIRE-02-2016 | Award Amount: 5.74M | Year: 2016

Machine learning have revolutionized the way we use computers and is a key technology in the analysis of large data sets. The FUDIPO project will integrate machine learning functions on a wide scale into several critical process industries, showcasing radical improvements in energy and resource efficiency and increasing the competitiveness of European industry. The project will develop three larger site-wide system demonstrators as well as two small-scale technology demonstrators. For this aim, FUDIPO brings together five end-user industries within the pulp and paper, refinery and power production sectors, one automation industry (LE), two research institutes and one university. A direct output is a set of tools for diagnostics, data reconciliation, and decision support, production planning and process optimization including model-based control. The approach is to construct physical process models, which then are continuously adapted using good data while bad data is used for fault diagnostics. After learning, classification of data can be automated. Further, statistical models are built from measurements with several new types of sensors combined with standard process sensors. Operators and process engineers are interacting with the system to both learn and to improve the system performance. There are three new sensors included (TOM, FOM and RF) and new functionality of one (NIR). The platform will have an open platform as the base functionality, as well as more advanced functions as add-ons. The base platform can be linked to major automation platforms and data bases. The model library also is used to evaluate impact of process modifications. By using well proven simulation models with new components and connect to the process optimization system developed we can get a good picture of the actual operations of the modified plant, and hereby get concurrent engineering process design together with development of process automation.


Grant
Agency: Cordis | Branch: H2020 | Program: RIA | Phase: ICT-06-2016 | Award Amount: 4.61M | Year: 2017

Large-scale computing systems are today built as distributed systems (for reasons of scale, heterogeneity, cost and energy efficiency) where components and services are distributed and accessed remotely through clients and devices. In some systems, in particular latency-sensitive or high availability systems, components are also placed closer to end-users (in, e.g., radio base stations and other systems on the edge of access networks) in order to increase reliability and reduce latency - a style of computing often referred to as edge or fog computing. However, while recent years have seen significant advances in system instrumentation as well as data centre energy efficiency and automation, computational resources and network capacity are often provisioned using best effort provisioning models and coarse-grained quality of service (QoS) mechanisms, even in state-of-the-art data centres. These limitations are seen as a major hindrance in the face of the coming evolution of(IoT and the networked society, and have even today manifested in, e.g., a limited cloud adoption of systems with high reliability requirements such as telecommunications infrastructure and emergency services systems. RECAP goes beyond the current state of the art and develop the next generation of cloud/edge/fog computing capacity provisioning via targeted research advances in cloud infrastructure optimization, simulation and automation. Building on advanced machine learning, optimization and simulation techniques. The overarching result of RECAP is the next generation of agile and optimized cloud computing systems. The outcomes of the project will pave the way for a radically novel concept in the provision of cloud services, where services are instantiated and provisioned close to the users that actually need them by self-configurable cloud computing systems.


An aspect of the present invention provides an in-memory data structure specific to each batch to be processed in a multi-tier application, the data structure for a specific batch designed to contain the data items required for the performance of multiple units of work in the specific batch. On receiving an indication that the specific batch is to be processed, data values for the performance of a unit of work are loaded into the in-memory data structure from a database. The requests directed to the data items that are received during the performance of the unit of work are processed based on the values in the in-memory data structure. The changes made to the values are then persisted to the database after the unit of work is completed. The above process is repeated for other units of work, thereby facilitating efficient batch processing in the multi-tier application.


The invention relates to a method for performing a query to a database system. In the method metadata relating to a database is retrieved from the database system. A search category is determined based on the metadata. The search category represents relationships between tables in the database. Search terms associated with the columns in the tables and received. A search data structure is obtained based on the search category and the search terms. The data structure comprises different parts corresponding to different tables. Search corresponding to the different parts are executed as separate using information in the different parts of the search data structure. A set operation between key column value sets obtained from the searches.


Patent
Tieto | Date: 2014-12-15

In telecommunications service chains are typically implemented as a chain of services implemented in a virtual environment. The service chain may be changed without causing unnecessary long delay to the operation of the chain by configuring the application implementing the service in the chain and then changing the output identifier of the previous application to correspond with the input identifier of the added application. The data traffic flow starts almost immediately to flow according to the new ser vice chain and there will be no long delays caused by restarting the services but only a minimized delay.


Patent
Tieto | Date: 2016-06-22

In telecommunications service chains are typically implemented as a chain of services implemented in a virtual environment. The service chain may be changed without causing unnecessary long delay to the operation of the chain by configuring the application implementing the service in the chain and then changing the output identifier of the previous application to correspond with the input identifier of the added application. The data traffic flow starts almost immediately to flow according to the new service chain and there will be no long delays caused by restarting the services but only a minimized delay.


Patent
Tieto | Date: 2015-06-30

Improved methods and arrangements for making measurements for load balancing and network management are disclosed for software defined networking components. In a software defined network component a monitoring module is provided in the kernel side of the component. The monitoring module may be used for making measurements in the kernel side or transmitting measurement packets directly to peer entities in other software defined network components.


According to an aspect of the invention there is provided a computer system comprising an application at a source execution context for providing latency critical services. The application module comprises a lower layer protocol module for receiving real-time critical data units from a transceiver and for sending real-time critical data units to the transceiver; an upper layer protocol module for receiving information from the lower layer protocol module and for providing information to be sent to the lower layer protocol module; and a scheduling module for dynamically controlling transmission of data units to the transceiver and reception of data units from the transceiver with the lower layer protocol module and the upper layer protocol module; wherein responsibilities of at least one of the lower layer protocol module, upper layer protocol module and scheduling module are configured to be migrated module by module to respective modules in a destination application at a destination execution context.

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