MobIPLity: A trace-based mobility scenario generator for mobile applications

Abstract

The understanding of human mobility patterns is key for the development and evaluation of ubiquitous applications. To overcome the scarcity and difficulties in capturing mobility data, models have been devised. In general, each model replicates some of the observed metrics, while neglecting others. However, all tend to ignore diversity, in the roles and goals of the users but also in the devices that are used to access the WiFi network. This paper presents the mobility traces from the access records of 49000 devices to the eduroam WiFi network of IPL for 7 years. Traces are made publicly available in the expectation that its large scale permits to support evaluations base on real mobility data, thus removing the uncertainty that emerges from the use of synthetic mobility models. Traces emphasise differences between device types, with impact on aspects like observed trace duration, speed, pause times, ICTs and availability, which can hardly be replicated on synthetic mobility models.