The continuous development of wireless networks and mobile devices has motivated an intense research in mobile data services. Some of these services provide the user with context-aware information. Specifically, location-based services and location-dependent queries have attracted a lot of interest. In this article, the existing literature in the field of location-dependent query processing is reviewed. The technological context (mobile computing) and support middleware (such as moving object databases and data stream technology) are described, location-based services and location-dependent queries are defined and classified, and different query processing approaches are reviewed and compared.

This paper focuses on intelligent transportation systems and, more precisely, on intervehicle ad hoc networks. A vehicular ad hoc network (VANET) is a highly dynamic network as the vehicles communicate using short-range wireless communications and can move very quickly. Thus, for example, we can only rely on short interactions between vehicles to exchange information about relevant events. In this paper, we describe in detail a dissemination protocol that vehicles can use to share information by using vehicle-to-vehicle communications. The dissemination approach considers the relevance of the data, represented by what we call encounter probability, to decide when a rediffusion is needed. The protocol is able to disseminate data about any type of event in the network (e.g., available parking spaces, accidents or obstacles in the road, information about moving objects such as emergency vehicles that should get the right of way, etc.) by setting appropriate weights for the different factors that affect the computation of the encounter probability. An extensive experimental evaluation with different types of events shows the interest of the proposal: The vehicles receive the relevant messages in time, and the network overload is limited.

The interest of intelligent transportation systems and vehicular ad hoc networks has increased in recent years. As a fundamental building block for the development of applications for vehicular networks, new techniques are needed to handle data appropriately in the vehicles. In this paper, we present a comprehensive overview of data management for vehicular networks, where the vehicle-to-vehicle communications play a key role. We describe the technological context of vehicular networks along with the different types of data managed in that environment, and we analyze several challenges, such as the evaluation of the relevance of data regarding the occurrence of events on the roads (e.g., accidents), the design of appropriate (effective and efficient) content-based data dissemination protocols, the competition in the access to physical resources (e.g., parking spaces), the development of suitable data aggregation techniques specifically adapted to the context of vehicular networks, and query processing. This paper provides an in-depth coverage of data management for vehicular networks but keeps, at the same time, a didactic orientation. Supported by an extensive collection of relevant references, we analyze the state of the art, identify some must-read references, outline research problems, and extract conclusions and lessons learned.

With the current advances of mobile computing technology, we are witnessing an explosion in the development of applications that provide mobile users with a wide range of services. In this paper, we present a system that supports distributed processing of continuous location-dependent queries in mobile environments. The system that we propose presents the following main advantages: 1) it is a general solution for the processing of location-dependent queries in scenarios where not only the users issuing queries, but also other interesting objects can move; 2) it performs an efficient processing of these queries in a continuous way; 3) it is especially well adapted to environments where location data are distributed in a network and processing tasks can be performed in parallel, allowing a high scalability; and 4) it optimizes wireless communications. We use mobile agents to carry the processing tasks wherever they are needed. Thus, agents are in charge of tracking the location of interesting moving objects and refreshing the answer to a query efficiently. We evaluate the usefulness of the presented proposal showing that the system achieves a good precision and scales up well