61444 20190709135426.0 doi 10.1016/j.ins.2016.11.007 sideral 97602 ART-2017-97602 eng (orcid)0000-0001-5905-3279 Urra, Oscar An approach driven by mobile agents for data management in vehicular networks 2017 Access copy available to the general public Unrestricted 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. info:eu-repo/grantAgreement/ES/MINECO/TIN2013-46238-C4-4-R info:eu-repo/semantics/openAccess by-nc-nd http://creativecommons.org/licenses/by-nc-nd/3.0/es/ 4.305 2017 COMPUTER SCIENCE, INFORMATION SYSTEMS 12 / 148 = 0.081 2017 Q1 T1 1.635 2017 Artificial Intelligence 2017 Q1 Computer Science Applications 2017 Q1 Theoretical Computer Science 2017 Q1 Information Systems and Management 2017 Q1 Software 2017 Q1 Control and Systems Engineering 2017 Q1 info:eu-repo/semantics/article info:eu-repo/semantics/submittedVersion (orcid)0000-0002-7073-219X Ilarri, Sergio Universidad de Zaragoza (orcid)0000-0001-6008-1138 Trillo-Lado, Raquel Universidad de Zaragoza 5007 570 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Lenguajes y Sistemas Inf. 381 (2017), 55-77 Inf. sci. Information Sciences 0020-0255 1752933 http://zaguan.unizar.es/record/61444/files/texto_completo.pdf Preprint 69310 http://zaguan.unizar.es/record/61444/files/texto_completo.jpg?subformat=icon icon Preprint oai:zaguan.unizar.es:61444 articulos driver 2019-07-09-11:29:38 ARTICLE