Continuous queries on trajectories of moving objects

Since navigation systems and tracking devices are becoming ubiquitous in our daily life, the development of efficient methods for processing massive sets of mobile objects are of utmost importance. Although future routes of mobile objects are often known in advance in many applications, this information is not fully utilized in most methods so far. In this paper, we reveal the beneficial effects of exploiting future routes for the early generation of the expected results of spatio-temporal queries. This kind of probable results is important for operative analytics in many applications like smart fleet management or intelligent logistics. For efficiently computing the high number of future trajectory points, a new index structure is presented which allows for a fast maintenance of query results under continuous changes of mobile objects. Our methods make use of specific update patterns, which require substantially less maintenance costs than the most general case of an update. A set of experiments based on a commonly used simulation environment shows the efficiency of our approach.