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物联网环境下的重点车辆监控海量信息处理研究
引用本文:聂佩林,程智锋,赵力萱,詹承志. 物联网环境下的重点车辆监控海量信息处理研究[J]. 交通标准化, 2013, 0(21): 8-11
作者姓名:聂佩林  程智锋  赵力萱  詹承志
作者单位:[1]佛山科学技术学院环境与土木建筑学院,广东佛山528000 [2]中山大学工学院智能交通研究中心,广东广州510006 [3]广东警官学院治安系交通管理学教研室,广东广州510230
基金项目:2011年公安部公安理论及软科学研究计划项目(2011LLYZGDST062);国家自然科学基金项目(41271181)
摘    要:重点车辆监控是借助物联网技术,通过感知设备对重点监控车辆进行识别、定位、跟踪、监控和管理。重点车辆监控平台需面对海量数据的处理问题.云计算信息处理模式为重点车辆信息管理提供了新思路。借助云计算的概念,提出基于Hadoop分布式并行编程框架的重点车辆信息管理模式和基于MapReduce编程模型的重点车辆海量信息处理方案。然后,采用广东省的重点车辆监控平台的历史数据作为样本,搭建基于Hadoop的重点车辆海量信息处理测试平台。实验结果表明,该平台能够实现物联网环境下的重点车辆海量数据的快速处理与查询.满足实时监控的要求。

关 键 词:重点车辆  物联网  监控  云计算  Hadoop

Immense Amount Data Processing of Key Vehicle Supervision under Internet of Things
NIE Pei-lin,CHENG Zhi-feng,ZHAO Li-xuan and ZHAN Cheng-zhi. Immense Amount Data Processing of Key Vehicle Supervision under Internet of Things[J]. Communications Standardization, 2013, 0(21): 8-11
Authors:NIE Pei-lin  CHENG Zhi-feng  ZHAO Li-xuan  ZHAN Cheng-zhi
Affiliation:1.Environment and Construction College, Foshan University, Foshan 528000, China; 2.Research Center of Intelligent Transportation System, School of Engineering, SUN Yat-sen University, Guangzhou 510006, China; 3. Division of Traffic Management Studies, Department of Public Security, Guangdong Police College, Guangzhou 510230, China)
Abstract:The key vehicle supervision is recognizing, positioning, tracking, monitoring and managing key vehicles by using sensing devices with the help of the Internet of Things Technology. The key vehicle supervision platform has to face the massive data processing problem. Cloud computing provides a new train of thought for the massive vehicle data management. According to the concept of cloud computing, a vehicle information manage- ment mode based on Hadoop distributed parallel programming framework and a massive data processing scheme based on MapReduce programming model are proposed. Then the historical data of main vehicle supervision sys- tem of Guangdong Province is taken as the sample and a massive data processing test platform based on Hadoop is built. The experimental results show that, the test platform can achieve the goal of fast accessing and querying and meet the requirements of real-time monitoring.
Keywords:key vehicle  Internet of Things  supervision  cloud computing  Hadoop
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