CGAM: A community and geography aware mobility model

TitreCGAM: A community and geography aware mobility model
Publication TypeJournal Article
Year of Publication2018
AuthorsMourchid, F, Kobbane, A, Ben Othman, J, M. Koutbi, E
JournalInternational Journal of Communication Systems
Volume31
Abstract

The advances of localization-enabled technologies have led to huge volumes of large-scale human mobility data collected from Call Data Records (CDR), Global Positioning System (GPS) tracking systems, and Location Based Social networks (LBSN). These location data that encompass mobility patterns could generate an important value for building accurate and realistic mobility models and hence important value for fields of application including context-aware advertising, city-wide sensing applications, urban planning, and more. In this paper, we investigate the underlying spatio-temporal and structural properties for human mobility patterns, and propose the Community and Geography Aware Mobility (CGAM) model, which characterizes user mobility knowledge through several properties such as home location distribution, community members' distribution, and radius of gyration. We validate the CGAM synthetic traces against real-world GPS traces and against the traces generated by the baseline mobility model SMOOTH and assess that CGAM is accurate in predicting the performance of flooding-based and community-based routing protocols. Copyright © 2017 John Wiley & Sons, Ltd.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85030319469&doi=10.1002%2fdac.3432&partnerID=40&md5=9e90e1af7674bce27f60e78c6d502044
DOI10.1002/dac.3432
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