Research Topics

Mobile Ad-Hoc Networks

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Wireless Sensor Networks

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Peer-to-Peer Networks

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Smart Teams: Local, Distributed Strategies for Self-Organizing Robotic Exploration Teams

In this project we aim at laying the algorithmic foundations for a scenario where an exploration team of robots we call it a smart team has to self-organize itself in order to fulfill tasks like exploring an unknown terrain and executing work in this terrain. Examples for such a task are rescue expeditions in dangerous areas or expeditions in the oceans or on planets. The work of such a smart team has to be guided by strategies for exploration, for finding important objects, and for assigning to such an object a subgroup of robots that jointly have the capabilities necessary to process the object. The challenge is that all these tasks have to be executed by local, distributed strategies that act on the mobile network of the moving robots, and have to result in a robust, effective selforganization of the team. None of these robots ever will have more than very restricted, local knowledge about the global state of the system. Their decisions are solely based on their own observations and findings, from which a globally good behavior of the whole team has to emerge. We will analyse the quality of our strategies both theoretically, e.g. by means of competitive analysis, and experimentally by extending SAHNE, our simulation platform for communication in mobile ad hoc networks.

Efficient Message Routing

For position-based routing nodes are identified by their unique geographical positions. The task is to deliver a message from a source node to a target node identified by its position in an unknown wireless ad hoc network.  We try to optimize the number of messages and the time to perform this task in a worst case setting. One obstacle for efficient position based routing is the lack of knowledge about the network structure available at the beginning. In particular, reactive routing protocols that do not know any network structure in advance fail to solve this problem efficiently.

As complexity measures we consider time and traffic for delivering the message from source to target cell. Time is the number of rounds until the message reaches the destination if the node is accessible. Traffic is the total number of messages sent between cells. We investigate the time and traffic under a competitive measure. This research nicely extends to robot motion planning if we restrict ourselves to a single message.

Storage Area Networks

... under construction ...

Mobility in Networks

... under construction ...