Abstract—
Mobile ad-hoc sensor networks are very beneficial in
many ubiquitous computing applications and situations such as military operations, construction sites, stadiums, convention centers, emergency services, inhospitable physical environments, music festivals, automobile race tracks, trade fair and shopping mall. Validation of mobile ad-hoc and delay tolerant network protocols for such environments is problematic. It relies almost exclusively on simulations which make use of movement models.
Furthermore, each scenario is characterized by its own distinctive mobility model. It is very difficult collecting real mobility data and in the recent years many efforts have been made aiming to build realistic mobility models. In order to conduct informed and realistic design of forwarding policies and algorithms for mobile ad-hoc sensor networks, it is important to gather real human mobility data. In this paper we study human mobility in a shopping mall environment. From this we make recommendations for the design of opportunistic forwarding algorithms for such environments.
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