In this University of Helsinki open online course, you learn the fundamental concepts behind mobile networks, focusing in particular on 5G and the envisioned future 6G networks.
The course focuses on core networking themes and problems at the higher layers of the protocol stack. Examples of topics we will cover are reliability (e.g., forward error correction), HTTP, RPC, video delivery, fate sharing (as based on the end-to-end argument), and component-based systems (e.g., containers and dockers). Each iteration of the course will focus on 3-4 key themes which will slightly vary from year to year.
The key focus of the course is a problem-based approach to building reliable networked systems and services. We will study the reliability problem at various protocol levels, illustrating how it can be solved at the different levels, and which level might be the most appropriate one for solving the problem. We will also explore the limits of reliability, i.e., just exactly how much can be achieved in practice. The course has a strong practical orientation and requires active participation in the exercises.
Mobile devices have emerged as one of the main instruments for tracking movement of people through the use of device-embedded motion sensors. By capturing detailed data about movement, i.e., acceleration and rotation of the device, useful information can be extracted. Thus, this information can be used to recognize physical activities and phenomena and can serve a wide variety of use cases.
For example, the Transportation Mode Discovery (TMD) using mobile devices, i.e., simple motion sensors such as accelerometers, gyroscopes and magnetometers can contribute to a large variety
of applications such as smart mobility and activity tracking.
Currently, detecting different motorized transport modes is difficult and is not supported by standard activity tracking API such as Google’s Activity recognition API. Therefore, in this thesis topic we aim to i) develop state-of-the-art method(s) for TMD, ii) implement the method(s) using existing datasets (or collecting new datasets), and iii) evaluate the performance of the develop method(s) against the existing studies in literature.
The candidate will be employed full time for the duration of six months and will be paid based on the salary system of the University of Helsinki. If you are interested in the topic, for more information please contact Dr. Naser Motlagh (firstname.lastname@example.org).
In one of the positions, the doctoral student will research, design, and develop optimized software solutions which can be interoperably used in a wide set of smart devices, for performing actionable data-driven insights aimed to ensure optimized sensing and communication tasks in IoT systems. The R&D activities of the other doctoral student will aim to develop an innovative digital twin framework, which can assess, inter alia, efficiency and functionality of the corresponding physical IoT system through the use of AI-powered analytics.
Both positions will also require the doctoral students to advance research in the context of specific technological areas, including, computing and networking resources management, heterogeneous data sources management, AI for IoT networks and systems. The doctoral researchers will be encouraged to design their own research project within the scope of the overall project in collaboration with the PIs. Furthermore, given the scope of the project and the complementarity between the two positions, high cooperation between the two doctoral researchers is a key requirement for a successful outcome of the project activities. The successful candidates will be principally supervised by Prof. Sasu Tarkoma and Dr. Roberto Morabito. The doctoral researchers will be offered up to a 3-year fully funded contract.
For additional information please contact Roberto Morabito (email@example.com)
The "Network Systems and Security Research Lab" at Nokia Bell Labs in Espoo is looking for thesis worker.