There are many cities where urbanization occurs at a faster rate than that of communication infrastructure deployment. Mobile users with sophisticated devices are often dissatisfied with this lag in infrastructure deployment; their Internet connection is via opportunistic open Access Points for short durations, or via weak, unreliable, and costly 3G connections. With increased demands on network infrastructure, we believe that opportunistic networking, where user mobility is exploited to increase capacity and augment Internet reachability, can play an active role as a complimentary technology to improve user experience, particularly with delay insensitive data. Opportunistic forwarding solutions were mainly designed using a set of assumptions that have grown in complexity, rendering them unusable outside their intended environment. Figure 1 categorizes sample state-of-the-art opportunistic forwarding solutions based on their assumption complexity. Most of these solutions however are not designed for large scale urban environments. In this work, we believe to be the first to exploit the space syntax paradigm to better guide forwarding decisions in large scale urban environments. Space syntax, initially proposed in the field of architecture to model natural mobility patterns by analyzing spacial configurations, offers a set of measurable metrics that quantify the effect of road maps and architectural configurations on natural movement. By interacting with the pre-built static environment, space syntax predicts natural movement patterns in a given area. Our goal is to leverage space syntax concepts to create efficient opportunistic forwarding distributed solutions for large scale urban environments. We address two communication themes: (1) Mobile-to-Infrastructure: We propose a set of space syntax based algorithms that adapt to a spectrum of simplistic assumptions in urban environments. As depicted in Figure 1, our goal is to gain performance improvement across the spectrum, within each assumption category, when compared to other state-of-the-art solutions. We adopt a data driven approach to evaluate the space syntax based forwarding algorithms we propose, within each of three assumption categories, based on large scale mobility traces capturing vehicle mobility. Overall, our results show that our space syntax based algorithms perform more efficiently within each assumption category. (2) Infrastructure-to-Mobile: We propose a new algorithm, Select&Spray, which leverages space syntax, and enables data transfers to mobile destinations reached directly through the infrastructure or opportunistically via other nodes. This architecture consists of: (i) a select engine that identifies a subset of directly connected nodes with a higher probability to forward messages to destinations, and (ii) a spray engine residing on mobile devices that guide the opportunistic dissemination of messages towards destination devices. We evaluate our algorithm using several mobility traces. Our results show that Select&Spray is more efficient in guiding messages towards their destinations. It helps extend the reach in data dissemination to more than 20% of the interested destinations within very short delays, and successfully reaches almost 90% of the destinations in less than 5 minutes.


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