Section: New Results
Fast self-stabilization in large scale wireless networks
Participants : Katy Paroux, Bruno Sericola.
In large-scale wireless networks, distributed self-organization is more convenient than centralized planification. Self-stabilization protocols are a useful technique to provide self-organization but their stabilizing time is related to the size of the network. A wide range of problems such as TDMA assignment or clustering may be solved thanks to local coloring on a graph model but with a tradeoff between the coloring time and the stabilization time of the protocol using the coloring. This stabilization time is related to the height of a directed acyclic graph induced by the colors, thus to the longest strictly ascending sequence of colors. In  , we model this height by the longest increasing contiguous sequence of non-independent uniform random variables. Then using a Markov chain approach, we obtain a theoretical upper bound on the stabilization time. More precisely, our results show the scalability properties of such a protocol, but also that using a large number of colors does not impact its stabilization time.