Abstract
Simulations of mobile ad-hoc, sensor, and mesh networks strongly rely on mobility models because they have a major influence on the performance of protocols. Results obtained with an unrealistic model may not reflect the true performance of protocols, applications and algorithms in real environments. In this paper, we present a mobility model for shopping mall environments based on real traces. Such environments offer all of the elements required to build large-scale people-centric ad-hoc networks. In many cases, shopping malls are tens of thousands of square metres in area and crowded much of the time. We ran a field trial to collect Bluetooth contact data from shop employees and clerks in a shopping mall over six days. We analysed the collected contact traces to guide the design of our Shopping Mall mobility model. Unlike the majority of existing synthetic mobility models our Shopping Mall mobility model captures heterogeneous behaviour of nodes and several different mobility characteristics at a lower level of abstraction. We show that our synthetic mobility model produces contact traces distributions which approximate those of the collected traces.
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Galati, A., Djemame, K. & Greenhalgh, C. A mobility model for shopping mall environments founded on real traces. Netw.Sci. 2, 1–11 (2013). https://doi.org/10.1007/s13119-012-0011-1
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DOI: https://doi.org/10.1007/s13119-012-0011-1