Open AccessSolving vehicular ad hoc network challenges with Big Data solutions
Author(s) -
ContrerasCastillo Juan,
Zeadally Sherali,
Guerrero Ibañez Juan Antonio
Publication year - 2016
Publication title -
iet networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.466
H-Index - 21
eISSN - 2047-4962
pISSN - 2047-4954
DOI - 10.1049/iet-net.2016.0001
Subject(s) - vehicular ad hoc network , big data , computer science , wireless ad hoc network , intelligent transportation system , computer security , computer network , data science , telecommunications , transport engineering , engineering , wireless , data mining
The concept of vehicular ad hoc networks (VANETs) has emerged as an efficient way to improve the performance of transportation systems, enhance travel security and help address traffic control problems that modern society is facing today. Large amounts of VANET data are typically collected from highly heterogeneous sources paving the way for a new era of VANET‐Big Data. This data must be processed rapidly, efficiently and cost‐effectively by different users and systems to make timely decisions about traffic and transportation. VANET‐Big Data is causing a shift from technology‐driven to data‐driven VANETs. The authors analyse and discuss Big Data solutions that can be leveraged to address some of the emerging challenges of VANETs.