Understanding the social dynamics of a group of people can give new insights into social behavior. Physical proximity between individuals results from the interactions between them. Hence, measuring physical proximity is an important step towards a better understanding of social behavior. We discuss a novel approach to sense proximity from within the social dynamics. Our primary objective is to construct a spatio-temporal social graph from noisy proximity data. We address the technical and algorithmic challenges of measuring proximity reliably and accurately. Simulations and real world experiments demonstrate the feasibility and scalability of our approach. Our algorithms doubles the sensitivity of proximity detections at the cost of a slight reduction in specificity.

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Energy is the scarcest resource in ad hoc wireless networks, particularly in wireless sensor networks requiring a long lifetime. Intermittently switching the radio on and off is widely adopted as the most effective way to keep energy consumption low. This, however, prevents the very goal of communication, unless nodes switch their radios on at synchronized intervals—a rather nontrivial coordination task. In this article, we address the problem of synchronizing node radios to a single universal schedule in wireless mobile ad hoc networks that can potentially consist of thousands of nodes. More specifically, we are interested in operating the network with duty cycles that can be less than 1% of the total cycle time. We identify the fundamental issues that govern cluster merging and provide a detailed comparison of various policies using extensive simulations based on a variety of mobility patterns. We propose a specific scheme that allows a 4,000-node network to stay synchronized with a duty cycle of approximately 0.7%. Our work is based on an existing, experimental MAC protocol that we use for real-world applications and is validated in a real network of around 120 mobile nodes.

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