|Decentralized Partitioning Over Adaptive Networks|
|Sahar Khawatmi, Technische Universitšt Darmstadt |
Abdelhak M. Zoubir, Technische Universitšt Darmstadt
There arises the need in many wireless network applications to infer and track different models of interest. Some nodes in the network are informed, where they observe the different models and send information to the uninformed ones. Each uninformed node responds to one informed node and joins its group. In this work, we suggest an adaptive and distributed clustering and partitioning approach that allows the informed nodes in the network to be clustered into many groups according to the observed models; then we apply a decentralized strategy to part the uninformed nodes into groups of approximately equal size around the informed nodes.