Collaboration Stability: Quantifying the Success and Failure of Opportunistic Collaboration

Abstract

We quantify the collaboration stability of human mobility and demonstrate its importance for networking applications. We derive a general model for collaboration stability and empirically explore the impact stability has on networking applications using a dataset of device-to-device encounters. We first derive insights on how characteristics of collaboration opportunities vary across everyday contexts and what implications this has on different multi-device scenarios. Among others, our results demonstrate that collaboration opportunities are highly dependent on the context where they take place, with diurnal patterns and spatial characteristics being particularly important. We also demonstrate the practical benefits of collaboration stability by demonstrating how it can be used to improve the selection of collaborators for sensing and computing applications.

Agustin Zuniga

Pervasive Data Science group

Dr. Agustin Zuniga works in the areas of pervasive data science and artificial intelligence of things, especially in low-cost sensing and intelligent sensing pipeline solutions.