Tiphaine Phe-Neau Senior Data Scientist, Engineer, PhD in Computer Science. Let's have fun!

Examining Vicinity Dynamics in Opportunistic Networks

Summary
Examining Vicinity Dynamics in Opportunistic Networks (poster). Tiphaine Phe-Neau, Miguel Elias M. Campista, Marcelo Dias de Amorim, and Vania Conan. In proceedings of The 16th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (ACM MSWiM 2013).

Abstract
Modeling the dynamics of opportunistic networks generally relies on the dual notion of contacts and intercontacts between nodes. We advocate the use of an extended view in which nodes track their vicinity (within a few hops) and not only their direct neighbors. Contrary to existing approaches in the literature in which contact patterns are derived from the spatial mobility of nodes, we directly address the topological properties avoiding any intermediate steps. To the best of our knowledge, this paper presents the first study to ever focus on vicinity motion. We apply our method to several real-world and synthetic datasets to extract interesting patterns of vicinity. We provide an original workflow and intuitive modeling to understand a node’s surroundings. Then, we highlight two main vicinity chains behaviors representing all the datasets we observed. Finally, we identify three main types of movements (birth, death, and sequential). These patterns represent up to 87% of all observed vicinity movements.

Bibtex Entry
@inproceedings{pheneau.mswim13,
author = {Phe-Neau, Tiphaine and Campista, Miguel Elias M. and Dias de Amorim, Marcelo and Conan, Vania},
title = {Examining Vicinity Dynamics in Opportunistic Networks},
booktitle = {ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (ACM MSWiM)},
month = {November},
year = {2013},
location = {Barcelona, Spain},
}

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