NCAR was launched in April 2016 and is a joint research center with University of Helsinki, Aalto University, and Nokia.


NCAR has the mission of developing and exploring radical new ideas and techniques for scalable, robust, and efficient software for future networks and mobile solutions. Meeting the new Big Data and connectivity challenges will require new approaches and methodologies that combine the expertise of various fields such as networking, software, databases, machine learning and data analytics.


We envisage a world in which billions of users and hundreds of billions of things are connected and form the basis for new personalized, adaptive, attentive, social and smart services. The requirements for massive scalability in terms of data and connectivity, dynamic operation, and machine intelligence present a number of difficult problems that will be addressed by the center.

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Ongoing Projects

Edge Computing: Technologies, Enablers, Use Cases

Key People: Sasu Tarkoma, Antti Ylä-Jääski, and Hannu Flinck
Summary: The objective of this work package is to investigate and develop open “Internet of Things” platform that is leveraging the concepts of edge computing.

Low Latency Transport Protocols

Key People: Hannu Flinck, Sasu Tarkoma, and Markku Kojo.
Summary: The objective of this work is to study how suitable the current transport protocols are for low latency applications, what should be done to improve their performance, and what kind of application-specific latency reduction mechanisms are needed.

Network Function Virtualization and Cloud Computing

Key People: Antti Ylä-Jääski, Hannu Flinck, and Sasu Tarkoma.
Summary:The objective of this work is to investigate cloud computing techniques, such as OpenStack and Docker, for scalable and elastic virtualized resource provisioning and management.

Distributed and Cognitive Processing

Key People: Vilho Räisänen, Sasu Tarkoma, and Jukka Corander.
Summary:The objective of this work is to build a novel data distribution and processing framework for base station data gathering and analysis, and a user interface for a data analytics system with machine learning and statistical inference components.

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