摘要
为解决日益增加的监测数据的高效存储问题,提出了一种基于数据敏感度自适应的旋转门压缩改进算法,根据数据敏感度及数据波动状态来自适应调整容差参数。经过性能测试和实际应用,该算法与标准旋转门压缩算法相比,在基本未增加复杂度的情况下,提高了压缩率,降低了压缩误差。
To solve the problem of storing massive monitoring data effectively,an improved SDT（ Swing Door Trending） algorithm based on data sensitivity adaptation is proposed. Its tolerance parameters was changed adaptively by the sensitivity and fluctuations of data. After performance testing and application,this algorithm had similar complexity with the standard SDT algorithm. And this algorithm had higher compression ratio and lower compression error than the standard SDT algorithm.
作者
张涵笑
慕福奇
吕欣岩
Zhang Hanxiao1,2, Mu Fuqi2,3 ,Lv Xinyan3(CAS R＆D Center for Internet of Things, Wuxi 214135, China; 2. School of Microelectronics, University of Chinese Academy of Sciences, Beijing 100049, China;3. Jiangsu Zhongke Yilian Communication Technology Co. , Ltd. , Wuxi 214135, Chin)
出处
《信息技术与网络安全》
2018年第6期64-67,共4页
Information Technology and Network Security
基金
新疆科技厅重大专项项目(2016A3007-5)
关键词
数据压缩
旋转门压缩算法
自适应
容差调整
有损压缩
data compression
Swinging Door Trending （SDT）
adaptation
tolerance adjustment
lossy compression
