Double Cross: A Double-Blind Data Discovery Scheme for Large-Scale Wireless Sensor Networks

In this paper, we consider the double-blindness problem in large-scale wireless sensor networks (WSNs) with mobile sinks, where the mobile sink(s) and data do not know the locations of each other a priori. We first propose a random line walk mechanism for message forwarding and based on this forwarding mechanism we further propose an efficient data discovery scheme called Double Cross to address the double-blindness problem. Double Cross exploits a simple geometric property of a planar, i.e., for a couple of pairs of orthogonal lines in a planar, the probability that they intersect within the planar is larger than 99%. However, it does not depend on the geographic location or directional information of a node, which is difficult to obtain in such networks. Instead, each sensor only needs to know the distances between neighbor nodes within its transmission range. Analytical and simulation results show that Double Cross can achieve a high successful discovery rate with low energy consumption.