Efficient reachability query evaluation in large spatiotemporal contact datasets

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, mobile devices, and vehicles. 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 penetrate 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 reachability queries in large (i.e., disk-resident) contact datasets which record the movement of a (potentially large) set of objects moving in a spatial environment over an extended time period. A reachability query verifies whether two objects are "reachable" through the evolving contact network represented by such contact datasets. We propose two contact-dataset indexes that enable efficient evaluation of such queries despite the potentially humongous size of the contact datasets. With the first index, termed ReachGrid, at the query time only a small necessary portion of the contact network which is required for reachability evaluation is constructed and traversed. With the second approach, termed ReachGraph, we precompute reachability at different scales and leverage these precalculations at the query time for efficient query processing. We optimize the placement of both indexes on disk to enable efficient index traversal during query processing. We study the pros and cons of our proposed approaches by performing extensive experiments with both real and synthetic data. Based on our experimental results, our proposed approaches outperform existing reachability query processing techniques in contact networks by 76% on average.

Simple, fast, and scalable reachability oracle

“…As one of the most fundamental graph operators, reachability has drawn much research interest in recent years [6,36,9,34,21,10,7,20,39,37,5,35,19,8] and seems to continue fascinating researchers with new focuses [23,38,22] and new variants [15,12,31]. The basic reachability query answers whether a vertex u can reach another vertex v using a simple path (?u → v) in a directed graph.…”

Privacy-preserving inference of social relationships from location data

“…• Reachability: If two people have come in close contact with each other or there exists a contact path between them through other people, we can infer one is "reachable" from the other for delivering a package, or contracting a disease [15]. • Social Strength: If two people have been to the same places at the same time, i.e., co-occurred, we can infer that they are socially connected.…”

“…However, due to the nature of the utilized dataset, these studies were confined to behaviors that were observed in the online world. Recently, due to the availability of high-resolution spatiotemporal location data collected by GPS-enabled mobile devices through mobile apps, e.g., Google Maps, Facebook, Foursquare, and WhatsApp, or through online services, such as geo-tagged contents (tweets from Twitter, pictures from Instagram, Flickr or Google+ Photo), etc., it has become possible to study social behaviors by observing people's behaviors in the real world, especially via location history [15,13]. For example, if two people were seen at the same places and at the same time, i.e., cooccurred, we can infer that they are socially connected [13].…”

Opportunistic data services in least developed countries

“…So, we should adopt the open-world assumption, admit the possibility of approximate answers, decide how to identify the relevant data sources without overloading the network (e.g., based on spatial conditions), how to route queries and results to their recipients (while preserving autonomy) using geographic routing and the physical mobility of nodes, and how to determine when a query and its associated routing tasks have to be finished. Moreover, new types of queries could be of interest in this context, requiring new query processing techniques; for example, reachability queries [36] could be used to study the possibility of propagation of a disease by analyzing past trajectories.…”