Efficient and Timely Querying of Massive Trajectory Data in Internet of Vehicles

摘要

The Internet of Vehicles (IoV) has become an indispensable part of a smart city, which can provide useful traffic information to supervise and guide drivers in metropolis. However, as the traffic data scales to a great volume, it becomes difficult for conventional database management tools to meet the requirement of massive data analysis. HBase is an open source, non-relational, distributed database running on top of Hadoop Distributed File System (HDFS). It can solve the problems in massive data querying that an IoV system faces nowadays. In this paper, we propose a massive traffic data querying solution using HBase to analyze the data collected in practice. In this solution, we firstly preprocess the original data and then propose a schema for the HBase table, especially a row key structure design to storage data effectively. Based on the schema, several querying patterns are designed to realize various functions that are meaningful in IoV applications. The performance of the proposed row key design is compared with the strategy without row key design on an experimental evaluation, and the results show that the proposed schema has a promising performance in time consumption.