Thematic Research Areas
Architectures and Concepts
Future communication infrastructures will consist of many different
networks. The challenge is to provide the enabling technology needed to offer seemlessly integrated services over these networks, and to provide the user with a transparent interface to the system regardless of her actual physical connection. Enabling the convergence of heterogenous networks and building a reliable infrastructure, tolerant to subsystem failures, is therefore critical.
Computation and Algorithms
Research in this thematic area focuses on analysis, design, evaluation of and experimentation with networked system in various application areas including vehicular networks, mobile services and cloud infrastructure. The projects exploit synergies from different disciplines, such as teletraffic systems, algorithms, and statistical physics, and the work combines theoretical studies with experimentation.
The faculty active in this thematic area: Erik Aurell (CB), Sonja Buchegger (TCS), Mads Dam (TCS), György Dán (LCN), Gunnar Karlsson (LCN), Supriya Krishnamurthy (TCS), Panagiotis Papadimitratos (LCN), Maria Papadopouli (visiting), Alexandre Proutiere (ACL), Rolf Stadler (LCN), Viktoria Fodor (LCN).
Sensing and Actuation
Our networked information systems have to deal with a continuously growing number of participating units, like smart cameras, handheld devices, and wireless sensors. These units themselves become more and more capable of monitoring their local environment, as well as interacting with it. Moreover, these units are covering larger and larger geographic areas. This growth makes it more difficult for networked information systems to handle the complex information these units generate. To maintain high reliability and availability of our expanding networked information systems, we have to meet challenges in the area of distributed processing and communication of information signals as well as distributed control of information actions.
Transmission and Radio
In the future much of the signal processing in sensor networks will have to be done in a decentralized way. More precisely, sensors (video cameras, chemical sensors, for instance) will be intelligent and perform preprocessing of measurement data instead of transmitting raw data over a bandwidth and power consuming link to a central processing unit in the network. There are many reasons for this trend. One is that the number of sensors and the amount of data they generate grows fast. Another is that decentralization in itself is a system design methodology, to achieve modularity and to increase reliability by reducing explicit dependence on a few central nodes.