Distributed decision-making over mobile adaptive networks
Sahar Khawatmi, Xinxin Huang, Abdelhak M. Zoubir
Abstract
In this paper, we study distributed decision-making over mobile adaptive networks where nodes in the network collect data generated by two different models. The nodes need to decide which model to estimate and track. However, they do not know beforehand which model they observe. Therefore, an effective clustering technique is needed. We apply a clustering technique that reduces the clustering error. Furthermore, introduce an additional term to the motion model to ensure that the nodes move coherently without fragmentation in the network during the decision-making process. Once the network reaches agreement on the desired model, the cooperation among nodes enhances the performance of the estimation task by relaying data throughout the network.
BibTeX
@inproceedings{icassp2017_distributeddecis,
title = {Distributed decision-making over mobile adaptive networks},
author = {Sahar Khawatmi and Xinxin Huang and Abdelhak M. Zoubir},
booktitle = {ICASSP 2017},
year = {2017}
}