Reach Me If You Can: Reachability Query in Uncertain Contact Networks

Abstract

With the advent of reliable positioning technologies and prevalence of location-based services, it is now feasible to accurately study the propagation of items such as infectious viruses, sensitive information pieces, and malwares through a population of moving objects, e.g., individuals, vehicles, and mobile devices. In such application scenarios, an item passes between two objects when the objects are sufficiently close (i.e., when they are, so-called, in contact), and hence once an item is initiated, it can propagate in the object population through the evolving network of contacts among objects, termed contact network. In this paper, for the first time we define and study probabilistic reachability queries in large uncertain contact networks, where propagation of items through contacts are uncertain. A probabilistic reachability query verifies whether two objects are "reachable" through the evolving uncertain contact network with a probability greater than a threshold η. For efficient processing of probabilistic queries, we propose a novel index structure, termed spatiotemporal tree cover (STC), which leverages the spatiotemporal properties of the contact network for efficient processing of the queries. Our experiments with real data demonstrate superiority of our proposed solution versus the only other existing solution (based on Monte Carlo sampling) for processing probabilistic reachability queries in generic uncertain graphs, with 300% improvement in query processing time on average.