Paper Info
Title
Efficient Graph-Oriented Smart Transportation Using Internet of Things Generated Big Data.
Abstract
The rapid growth in the population density inurban cities and the advancement in technology demands real-time provision of services and infrastructure. Citizens, especially travelers, want to be reached within time to the destination. Consequently, they require to be facilitated with smart and real-time traffic information depending on the current traffic scenario. Therefore, in this paper, we proposed a graph-oriented mechanism to achieve the smarttransportation system in the city. We proposed to deploy road sensors to get the overall traffic information as well as the vehicular network to obtain location and speed information of the individual vehicle. These Internet of Things (IoT) based networks generate enormous volume of data, termed as Big Data, depicting the traffic information of the city. To process incoming Big Data from IoT devices, then generating big graphs from the data, and processing them, we proposed an efficient architecture that uses the Giraph tool with parallel processing servers to achieve real-time efficiency. Later, various graph algorithms are used to achieve smart transportation by making real-time intelligentdecisions to facilitate the citizens as well as the metropolitan authorities. Vehicular Datasets from various reliable resources representing the real city traffic are used for analysis and evaluation purpose. The system is implemented using Giraph and Spark tool at the top of the Hadoop parallel nodes to generate and process graphs with near real-time. Moreover, the system is evaluated in terms of efficiency by considering the system throughput and processing time. The results show that the proposed system is more scalable and efficient.
Year
DOI
Venue
2015
10.1109/SITIS.2015.121
SITIS
Keywords
Field
DocType
IoT, Big Data, Smart Transportation, Graph
Spark (mathematics),Computer science,Server,Computer network,Artificial intelligence,Throughput,Metropolitan area,Computer vision,Architecture,Internet of Things,Big data,Database,Scalability
Conference
Citations 
PageRank 
References 
11
0.53
8
Authors
4
Name
Order
Citations
PageRank
muhammad mazhar ullah rathore130121.15
Awais Ahmad237945.85
Anand Paul352746.32
Gwanggil Jeon4596117.99