Title :
Extracting Trends of Traffic Congestion Using a NoSQL Database
Author :
Damaiyanti, Titus Irma ; Imawan, Ardi ; Joonho Kwon
Author_Institution :
Dept. of Electr. & Comput. Eng., Pusan Nat. Univ., Busan, South Korea
Abstract :
Recently, there has been growing interest in monitoring the road traffic data. Most of the work focused on real-time traffic data. In this paper, we propose an Extrac system which extracts trend of traffic congestions from historical traffic data and answers the queries about the trends. In Extrac system, we first convert the historical traffic data into traffic patterns then summarize it by applying MapReduce style algorithms. These traffic patterns are store into a NoSQL database. Our implementation demonstrates the feasibility of Extrac for querying traffic information and generating the result.
Keywords :
SQL; query processing; real-time systems; road traffic; traffic engineering computing; Extrac system; MapReduce style algorithms; NoSQL database; historical traffic data; real-time traffic data; road traffic data; traffic congestion; traffic information; Data models; Data visualization; Databases; Heating; Market research; Matrix converters; Roads; NoSQL database; historical traffic data; traffic patterns; trends of traffic congestions;
Conference_Titel :
Big Data and Cloud Computing (BdCloud), 2014 IEEE Fourth International Conference on
Conference_Location :
Sydney, NSW
DOI :
10.1109/BDCloud.2014.97