传感网流数据处理技术

传感网流数据处理技术》课程介绍

 

《传感网流数据处理技术》是物联网工程专业的专业选修课。该课程内容是一个全新的研究领域,主要包含两个方面:数据流管理和数据流分析/挖掘。

该课程主要介绍传感器网络中的数据流处理技术,使学生对该领域的原理、技术及研究现状有一个全面、深刻的了解。主要内容包括四个部分。第一部分,数据流处理和传感器网络概述,包括:传感器网络在技术和计算方面的背景知识,数据流模型、算法,传感器网络中数据流处理的分类、问题和挑战;第二部分,传感器网络中数据流管理的关键技术,包括数据流管理系统的特征、传感器网络的查询处理、数据流的汇聚和概括;第三部分,数据流挖掘算法,包括聚类技术、集中和分布的预测学习、传感器网络的张量分析;第四部分,介绍传感器网络在安全、科学和教育方面的典型应用。

通过本课程的学习,使学生对该领域的原理、技术、研究和应用的现状有一个深刻的理解,为今后的实际应用奠定扎实的基础。

 

The Introduction of Course ---

Data Streams Processing Techniques in Sensor Networks

《Data Streams Processing Techniques in Sensor Networks》is an optional specialty course of Internet of Things Engineering. The content of this course, mainly including data stream management and data stream analysis/mining, is a brand new research field.

The emphasis of this course is to introduce data stream processing technology in sensor networks so that the students can have a comprehensive and profound understanding of the theory, technology and research status about the field. The main content includes four parts. The first part presents an overview of the field of data stream processing and sensor networks including a background about sensor networks from technological and computational points of view; data stream models and algorithms; classification of data stream processing in sensor networks; research issues and challenges that face sensor networks with relation to data stream processing. The second part discusses data stream management techniques in sensor networks including the features of data stream management system; the query processing in sensor networks; the aggregation and summarization of sensor data streams. The third part concerns with data stream mining in sensor networks including clustering techniques, centralized and distributed predictive learning, tensor analysis in sensor networks. The last part presents some of the exciting applications on security, science and education.

By learning this course, students may profoundly understand the principle, technology and the state of art of the research and application and lay a solid foundation for future practical application.

 

 

 

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