Dissertation Defense
Supporting Large Scale Communication Systems on Infrastructureless Networks Composed of Commodity Mobile Devices: Practicality, Scalability, and Security
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Infrastructureless networks composed of commodity mobile devices have the potential to support communication applications resistant to blocking and censorship, as well as certain types of surveillance. We analyze the performance and energy consumption of such networks, and consider the impact of random and targeted denial-of-service and censorship attacks.
We collected the contact traces of 119,055 mobile devices on the U-M campus for a month, nearly twice of the population of the university. We construct a connectivity graph of human contacts and study its basic properties. The human contact graph has significantly higher node degrees (2863), shorter path lengths (2.3), and higher cluster coefficient (0.357) than popular online social networks. We show that its degree distribution has an exponential, instead of power-law, tail. We also report that the human contact network shows strong "assortative mixing".
We report the message delivery performance and energy overhead of this large-scale DTN with 119,055 mobile devices. Using an epidemic flooding protocol, the network achieves an average delivery rate of 0.95 in 72 hours (0.71 in 24 hours) and a median delivery delay of 10.9 hours. Based on a measurement-based energy model, we show that using an energy efficient variant of the epidemic flooding protocol, the network can support text messages while only consuming 13.7% of a typical smartphone battery in 14 hours. We also found that the network delivery rate and delay are robust to denial-of-service and censorship attacks eliminating more than 40% of the participants.