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In this paper we introduce Spatio-TEmporal Parametric Stepping (STEPS) - a simple parametric mobility model which can cover a large spectrum of human mobility patterns. STEPS makes abstraction of spatio-temporal preferences in human mobility by using a power law to rule the nodes movement. Nodes in STEPS have preferential attachment to favorite locations where they spend most of their time. Via simulations, we show that STEPS is able, not only to express the peer to peer properties such as inter-contact/contact time and to reflect accurately realistic routing performance, but also to express the structural properties of the underlying interaction graph such as small-world phenomenon. Moreover, STEPS is easy to implement, flexible to configure and also theoretically tractable. © 2011 IFIP International Federation for Information Processing.
Nguyen, A. D., Sénac, P., Ramiro, V., & Diaz, M. (2011). STEPS - An approach for human mobility modeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6640 LNCS, pp. 254–265). https://doi.org/10.1007/978-3-642-20757-0_20