Contact probing mechanisms for opportunistic sensor data collection in sparse wireless sensor networks

In many emerging wireless sensor network scenarios, the use of a fixed infrastructure of base stations for data collection is either infeasible, or prohibitive in terms of deployment and maintenance costs. Instead, we consider the use of mobile devices (i.e. smartphones) carried by people in their daily life to collect data from sensor nodes opportunistically. As the movement of these mobile nodes is, by definition, not controlled for the purpose of data collection, synchronization through contact probing becomes a challenging task, particularly for sensor nodes, which need to be aggressively duty-cycled to conserve energy and achieve long lifetimes. This paper formulates this important problem, providing an analytical solution framework and systematically investigating the effective use of contact probing for opportunistic data collection. We present two new solutions, Sensor Node-Initiated Probing (SNIP) and SNIP-Rush Hours, the latter taking advantage of the temporal locality of human mobility. These schemes are evaluated using numerical analysis and COOJA network simulations, and the results are validated on a small sensor testbed and with the real-world human mobility traces from Nokia MDC Dataset. Our experimental results quantify the relative performance of alternative solutions on sensor node energy consumption and the efficacy of contact probing for data collection, allowing us to offer insights on this important emerging problem