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Opportunistic routing is being investigated to enable
the proliferation of low-cost wireless applications. A recent trend is looking at social structures, inferred from the social nature of human mobility, to bring messages close to a destination. To have a better picture of social structures, social-based opportunistic routing solutions should consider the dynamism of users’ behavior resulting from their daily routines. We address this challenge by presenting dLife, a routing algorithm able to capture thedynamics of the network represented by time-evolving social ties between pair of nodes. Experimental results based on synthetic mobility models and real human traces show that dLife has better delivery probability, latency, and cost than proposals based on social structures.
This presentation was given in the 6th IEEE WoWMoM Workshop on Autonomic and Opportunistic Communications (AOC 2012), on June 25th, 2012 in San Francisco, USA.