ALE中交易集合事件的处理方法与技术研究

发布时间：2018-01-01 05:38

本文关键词：ALE中交易集合事件的处理方法与技术研究　出处：《北方工业大学》2015年硕士论文　论文类型：学位论文

【摘要】：随着物联网产业的兴起,世界各国(比如美国、日本)分别就物联网产业的研究和发展制定了相应的策略。我国于2009年提出了“感知中国”的战略构想,致力于将物联网科技带来的便利广泛地应用到人们的日常生活中。然而,随着感知设备、摄像头等数据采集设备的大量部署,数据采集的范围和规模不断扩大,使得对感知数据的辨认、分类、存储、利用成为了制约物联网应用发展的一个难题。该问题在相关的技术标准中,如EPCglobal国际标准,也没有提出相应的解决方案。 EPC物联网的感知数据主要来源于各种商品所携带的电子标签,采集该信息的设备--识读器被广泛部署在物流中心的各个区域。识读器在每个读取周期内可以对同一个标签进行快速、重复的扫描,这将使得物流中心的数据量日益增大,从而导致物流中心信息系统的服务功能由于数据量过大而受到影响。并且由于数据增长速度、数据量以及计算需求已经超出了物流中心所配备的服务器的容量以及计算能力,使得传统数据处理方式已经无法满足对数据中心EPC数据进行存储、分析的需求,严重影响了物流中心对外提供的数据订阅服务,而云计算技术的出现为物流中心的大数据数据订阅难题带来了简单高效的解决方式。因此,本文在对大数据处理技术如Hadoep等深入理解的基础上,通过对EPCGlobal国际标准中的集合事件进行了扩展,提出了集合事件的处理方法,并使用Hadoop技术进行实现,用以满足终端用户对交易集合事件数据订阅的需求。实验结果表明,ALE中交易集合事件的处理方法可以对数据中心的海量数据进行高效的存储和分析,并能准确地获取用户的交易集合事件订阅数据,从而可以极大地提高物流中心的服务质量和服务水平。
[Abstract]:With the rise of the Internet of things industry, countries in the world (such as the United States, Japan) have made corresponding strategies for the research and development of the Internet of things industry. In 2009, China put forward the strategic concept of "perceiving China". Devoting to the convenience of Internet of things technology widely used in people's daily life. However, with a large number of deployment of sensing devices, cameras and other data acquisition devices, the scope and scale of data acquisition is expanding. The identification, classification, storage and utilization of perceptual data have become a difficult problem in the development of Internet of things applications. This problem is in the relevant technical standards, such as the EPCglobal international standard. Also did not propose the corresponding solution. The perceptual data of the EPC Internet of things mainly comes from the electronic tags carried by various goods. The device that collects this information, the reader, is widely deployed in all areas of the logistics center. The reader can scan the same label quickly and repeatedly during each reading cycle. This will make the data volume of logistics center increasing day by day, resulting in the service function of logistics center information system is affected because of the large amount of data, and because of the speed of data growth. The amount of data and computing requirements have exceeded the capacity and computing capacity of the server provided by the logistics center, which makes the traditional data processing method can no longer meet the data center EPC data storage. The demand of analysis seriously affects the data subscription service provided by logistics center, and the emergence of cloud computing technology brings a simple and efficient solution to the problem of big data data subscription in logistics center. Therefore, based on the in-depth understanding of big data processing techniques such as Hadoep, this paper extends the set events in the international standard of EPCGlobal. In this paper, a method of dealing with set events is proposed and implemented by using Hadoop technology to meet the demand of end users to subscribe to transaction set event data. The experimental results show that the transaction set event processing method in ale can efficiently store and analyze the massive data in the data center and can accurately obtain user transaction set event subscription data. Thus, the service quality and service level of logistics center can be greatly improved.
【学位授予单位】：北方工业大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP311.13;TP391.44;TN929.5

【参考文献】