Big data processing framework of road traffic collision using distributed CEP

In Lee
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引用次数: 12

Abstract

The traffic information is a big data comes from varying sources, such as, social sites, mobile phone GPS signals and so on. The Hadoop and HBase can store and analyze real-time collision data in a distributed processing framework. This framework can be designed as flexible and scalable framework using distributed CEP that process massive real-time traffic data and ESB that integrates other services. In this paper, we propose a new architecture for distributed processing that enables big data processing on the road traffic data and its related information analysis. We tested the proposed framework on road traffic data on 400km from Seoul to Busan freeway section in Korea. By integrating freeway traffic big data and collision data over a seven-year period (1TB Size), we obtained the collision probability data.
基于分布式CEP的道路交通碰撞大数据处理框架
交通信息是一个大数据,来源多种多样,如社交网站、手机GPS信号等。Hadoop和HBase可以在分布式处理框架下存储和分析实时碰撞数据。可以使用分布式CEP(处理大量实时流量数据)和集成其他服务的ESB将该框架设计为灵活且可扩展的框架。本文提出了一种新的分布式处理架构,实现道路交通数据的大数据处理及其相关信息分析。我们在首尔至釜山高速公路400公里区间的道路交通数据上进行了测试。通过整合高速公路交通大数据和7年(1TB Size)的碰撞数据,我们得到了碰撞概率数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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