Multi-scale query processing in vehicular networks

Abstract

In the last decade, a number of wireless and small-sized devices (e.g., PDAs, smartphones, sensors, laptops, etc.) with increasing computing capabilities have appeared in the market at very affordable costs. These devices have started to be embedded in modern cars in the form of on-board computers, GPS navigators, or even multimedia centers. Thus, the vehicles can carry useful information, acting as data sources for other vehicles. Recently, some works have addressed the problem of processing queries in such highly dynamic vehicular networks in order to share information between drivers. The proposed query processing techniques usually rely on a push model. Hence, each vehicle receives data from its neighbors and decides whether they are relevant enough to be stored in a local data cache. Then, the data may be used by a query processor to retrieve relevant data for the driver. In this paper, we look at the problem from a broader perspective and discuss the interest of multi-scale query processing techniques in such context. The goal of such techniques is to exploit, at the mobile device's level, different access modes (e.g., push, pull) and various data sources (e.g., data cached locally, data stored by vehicles nearby, remote Web services, etc.) to provide the users with results for their queries. We highlight the most important challenges and outline some possible approaches. We also present a prototype of a first query evaluator developed using the Microsoft LINQ API.

GeoVanet: A Routing Protocol for Query Processing in Vehicular Networks

“…In [13], the authors focus on multi-scale query processing in vehicular networks. They consider both the pull and push models and claim that different types of data sources (e.g., the local data cache containing data diffused by neighboring vehicles, remote web services, etc.)…”

“…Developing data management techniques that can be useful to build information services for drivers is a hot research topic (e.g., see [13,49]). A key driving force is that, in the last decade, a number of small-sized wireless devices (e.g., PDAs or laptops) with increasing computing capabilities have appeared in the market at very affordable costs.…”

Analyzing the efficiency of context-based grouping on collaboration in VANETs with large-scale simulation

“…Telematic application development has recently been gaining a lot of attention from the research community (Behera and Meher 2002;Indulska et al 2003;Mahajan et al 2007;Kirsch-Pinheiro et al 2008;Leontiadis et al 2009;Iwan and Safar 2010;Nose et al 2010;Delot et al 2011. Application areas include emergency response team notification, congestion monitoring and parking space allocation.…”