Towards Intelligent and Generic LBS for Drivers and Mobile Users

In this talk I will focus on Location-Based Services (LBS) for hybrid networks composed of both vehicles and mobile users. The motivation is the interest of studying data management solutions that take into account a generic environment where different types of moving objects share different types of data and possibly using different communication technologies (ad hoc wireless communications forming a pure mobile P2P network, hybrid mobile P2P network with support infrastructure nodes, wide-area communications like 3G, etc.). I will start by summarizing some data management challenges for vehicular networks, related to the exchange of events (efficient and effective content-based data dissemination for push-based data access), query processing (pull-based data access by using query dissemination or mobile agent technology), data item relevance evaluation, management of information about scarce resources (like available parking spaces or charge stations for electric vehicles), semantic data management, automatic knowledge extraction from the data items, multimedia data management, incentives, and trust. Then ..

Modeling mobile agents in vehicular networks

Vehicular networks (VANETs) are mobile ad hoc networkswhere vehicles that are near each other can exchange data by usingwireless communications. Advances in mobile communication technolo-gies have spurred significant research in the exploitation of these types ofnetworks to develop different kinds of data services for drivers. However,these networks are also highly-dynamic and several data managementchallenges arise to realize their full potential.We have proposed the use of mobile agent technology for efficient dis-tributed query processing in VANETs. Mobile agents are software entitieswith the capability to hop among nearby cars in such a way that theycan transport themselves to the vehicles storing relevant data. In thispaper, using Petri nets, we present a formal model of our approach

Distributed data processing in vehicular networks using mobile agents

In a vehicular network, vehicles can exchange interesting information (e.g., about accidents, traffic status, etc.) using short-range wireless communications. Besides, the vehicles can be equipped with additional sensors that can directly obtain data from the environment. How to efficiently process and collect these data is an open problem. We argue that mobile agent technology could be helpful

Distributed Data Processing in Vehicular Networks using Mobile Agents

In a vehicular network, vehicles can exchange interesting information (e.g., about accidents, traffic status, etc.) using short-range wireless communications. Besides, the vehicles can be equipped with additional sensors that can directly obtain data from the environment. How to efficiently process and collect these data is an open problem. We argue that mobile agent technology could be helpful

Distributed Data Management in Vehicular Networks Using Mobile Agents

En los últimos años, las tecnologías de la información y las comunicaciones se han incorporado al mundo de la automoción gracias a sus avances, y han permitido la creación de dispositivos cada vez más pequeños y potentes. De esta forma, los vehículos pueden ahora incorporar por un precio asequible equipos informáticos y de comunicaciones.En este escenario, los vehículos que circulan por una determinada zona (como una ciudad o una autopista) pueden comunicarse entre ellos usando dispositivos inalámbricos que les permiten intercambiar información con otros vehículos cercanos, formando así una red vehicular ad hoc, o VANET (Vehicular Ad hoc Network). En este tipo de redes, las comunicaciones se establecen con conexiones punto a punto por medio de dispositivos tipo Wi-Fi, que permiten la comunicación con otros del mismo tipo dentro de su alcance, sin que sea necesaria la existencia previa de una infraestructura de comunicaciones como ocurre con las tecnologías de telefonía móvil (como 3G/4G), que además requieren de una suscripción y el pago de una tarifa para poder usarlas.Cada vehículo puede enviar información y recibirla de diversos orígenes, como el propio vehículo (por medio de los sensores que lleva incorporados), otros vehículos que se encuentran cerca, así como de la infraestructura de tráfico presente en las carreteras (como semáforos, señales, paneles electrónicos de información, cámaras de vigilancia, etc.). Todos estas fuentes pueden transmitir datos de diversa índole, como información de interés para los conductores (por ejemplo, atascos de tráfico o accidentes en la vía), o de cualquier otro tipo, mientras sea posible digitalizarla y enviarla a través de una red.Todos esos datos pueden ser almacenados localmente en los ordenadores que llevan los vehículos a medida que son recibidos, y sería muy interesante poder sacarles partido por medio de alguna aplicación que los explotara. Por ejemplo, podrían utilizarse los vehículos como plataformas móviles de sensores que obtengan datos de los lugares por los que viajan. Otro ejemplo de aplicación sería la de ayudar a encontrar plazas de aparcamiento libres en una zona de una ciudad, usando la información que suministrarían los vehículos que dejan una plaza libre.Con este fin, en esta tesis se ha desarrollado una propuesta de la gestión de datos basada en el uso de agentes móviles para poder hacer uso de la información presente en una VANET de forma eficiente y flexible. Esta no es una tarea trivial, ya que los datos se encuentran dispersos entre los vehículos que forman la red, y dichos vehículos están constantemente moviéndose y cambiando de posición. Esto hace que las conexiones de red establecidas entre ellos sean inestables y de corta duración, ya que están constantemente creándose y destruyéndose a medida que los vehículos entran y salen del alcance de sus comunicaciones debido a sus movimientos.En un escenario tan complicado, la aproximación que proponemos permite que los datos sean localizados, y que se puedan hacer consultas sobre ellos y transmitirlos de un sitio cualquiera de la VANET a otro, usando estrategias multi-salto que se adaptan a las siempre cambiantes posiciones de los vehículos. Esto es posible gracias a la utilización de agentes móviles para el procesamiento de datos, ya que cuentan con una serie de propiedades (como su movilidad, autonomía, adaptabilidad, o inteligencia), que hace que sean una elección muy apropiada para este tipo de entorno móvil y con un elevado grado de incertidumbre.La solución propuesta ha sido extensamente evaluada y probada por medio de simulaciones, que demuestran su buen rendimiento y fiabilidad en redes vehiculares con diferentes condiciones y en diversos escenarios.<br /

HappyParking

There are estimations that indicate that about half of the vehicles on the move are searching for parking and that more than 40% of the total fuel consumption is spent while looking for an available parking space. This also contributes to significant urban traffic congestion. So, it would be interesting to have software tools that can help drivers to park easily. For the application challenge, our group proposed a HappyParking application, which would offer some interesting benefits: It ackowledges the importance of considering parking in the context of a displacement between a source location and a target location. This implies that the final target location has to be considered when deciding an appropriate parking space. Moreover, the application can be integrated into existing GPS-based navigation applications. It considers multimodality, that is, that parking a car could be just a leg within a longer trip using different modes of transportation. It exploits real-time constraints (e.g., time-based parking restrictions). It can accommodate a variety of methods to capture information about available parking spaces (e.g., magnetic sensors on the parkings, crowdsourcing information provided by drivers releasing a spot, cars with different types of sensors able to detect free places, etc.). It supports different types of parking spaces: on-street parking, private parkings and garages, home parking available for rental during specific time periods, etc...

Researching Context-Aware Recommendation Systems in Mobile Environments

The design and implementation of generic frameworks to support an easy development of context-aware recommendation systems has been relatively unexplored. In this paper, we briefly present our ongoing work for the definition of a framework that will support the development of context-aware recommendation systems in distributed and mobile environments. Those systems will allow suggesting relevant items to mobile users

An approach driven by mobile agents for data management in vehicular networks

In the last years, and thanks to improvements on computing and communications technologies, wireless networks formed by vehicles (called vehicular networks) have emerged as a key topic of interest. In these networks, the vehicles can exchange data by using short-range radio signals in order to get useful information related to traffic conditions, road safety, and other aspects. The availability of different types of sensors can be exploited by the vehicles to measure many parameters from their surroundings. These data can then be shared with other drivers who, on the other side, could also explicitly submit queries to retrieve information available in the network. This can be a challenging task, since the data is scattered among the vehicles belonging to the network and the communication links among them have usually a short life due to their constant movement. In this paper, we use mobile agent technology to help to accomplish these tasks, since mobile agents have a number of features that are very well suited for mobile environments, such as autonomy, mobility, and intelligence. Specifically, we analyze the benefits that mobile agents can bring to vehicular networks and the potential difficulties for their adoption. Moreover, we describe a query processing approach based on the use of mobile agents. We focus on range queries that retrieve interesting information from the vehicles located within a geographic area, and perform an extensive experimental evaluation that shows the feasibility and the interest of the proposal

Re-CoSKQ: Towards POIS recommendation using collective spatial keyword queries

The goal of collective spatial keyword queries is to retrieve, from a spatial database, a group of spatial items such that the description of the items included in that set (typically based on the use of keywords) is completely covered by the query’s keywords. Moreover, it ensures that the items retrieved are as near as possible to the query location and have the lowest inter-item distances. We argue that using this concept in the field of recommender systems could be useful. Therefore, in this position paper, we outline the idea of Re-CoSKQ, an adaptation of Collective Spatial Keyword Query (CoSKQ) for recommender systems in the tourism domain to provide the user with a set of Points of Interest (POIs) that satisfy his/her queries both geographically and semantically

Researching context-aware recommendation systems in mobile environments

The design and implementation of generic frameworks to support an easy development of context-aware recommendation systems has been relatively unexplored. In this paper, we briefly present our ongoing work for the definition of a framework that will support the development of context-aware recommendation systems in distributed and mobile environments. Those systems will allow suggesting relevant items to mobile users