Estimating local coverage areas for location dependent queries

Location-Based Services (LBS) are currently attracting many research efforts due to the pervasiveness of mobile devices in our daily life. Mechanisms to monitor distributedly the remote (and sometimes huge or dynamic) geographic areas referenced from location-based constraints are needed in order to retrieve the required data. In some cases (e.g., ad hoc networks), selecting the best places from which to scan a certain area is still an open problem; but moreover, it depends on another open problem: We should know the actual area that each object can scan (i.e., its communication coverage area) from its location in order to be sure that the whole interesting area is actually covered from a certain set of objects. Different disk-based coverage area models are usually adopted; however, knowing the real communication coverage area of an object is a very difficult task. Therefore, when accuracy is important, there is a need of a mechanism that estimates somehow the unknown real coverage area that a certain object is able to see, anytime and anywhere.

In this paper, we face the problem of estimating the real (and unknown) coverage area of a certain (mobile or static) object in a wireless scenario by considering as input data just the location of the devices that can communicate with that object at each time. To do this task we propose different algorithms, including a combination of all of them, and compare their accuracy and efficiency against a set of synthetic and real scenarios with different topologies and obstacles. We show that estimating the real coverage area of an object without assuming a disk of fixed radius is not only possible, but also simple and efficient.