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资源分布-Aware在线数据挖掘的无线传感器网络

Resource -aware distributed online data mining for wireless sensor networks
课程网址: http://videolectures.net/ecml07_mohamed_radod/  
主讲教师: Mohamed Medhat Gaber
开课单位: 莫纳什大学
开课时间: 2008-01-29
课程语种: 英语
中文简介:
无线传感器网络中的在线数据挖掘涉及到用网络内处理模式从大量连续的数据流中提取知识的问题。与其他类型的网络不同, 有限的计算资源要求挖掘算法高效且紧凑。提出了一种分布式资源感知在线数据挖掘框架, 用于将现有挖掘技术应用于传感器网络环境。在新的 sun microsystemtm 小型可编程对象技术 sun spot 平台上, 应用该框架开发并实现了分布式资源自适应在线聚类算法。我们对该算法在实际传感器节点上的性能进行了评估。实验结果表明, 聚类算法在保持可接受的精度水平的同时, 能显著提高资源利用率。
课程简介: Online data mining in wireless sensor networks is concerned with the problem of extracting knowledge from a large continuous amount of data streams with an in-network processing mode. Unlike other types of networks, the limited computational resources require the mining algorithms to be highly efficient and compact.We propose a distributed resource-aware online data mining framework for wireless sensor networks which can be used to enable existing mining techniques to be applied to sensor network environments. We have applied the framework to develop and implement a distributed resource adaptive online clustering algorithm on the novel Sun MicrosystemTM Small Programmable Object Technology Sun SPOT platform. We have evaluated the performance of the algorithm on the actual sensor nodes. Experimental results show that the clustering algorithm can improve significantly in resource utilization while maintaining acceptable accuracy level.
关 键 词: 计算机科学; 数据挖掘; 无线传感器
课程来源: 视频讲座网
最后编审: 2020-06-13:邬启凡(课程编辑志愿者)
阅读次数: 39