Name
Abstract | ||
|---|---|---|
As a key issue in distributed monitoring, time series data are a series of values collected in terms of sequential time stamps. Requesting them is one of the most frequent requests in a distributed monitoring system. However, the large scale of these data users request may not only cause heavy loads to the clients, but also cost long transmission time. In order to solve the problem, we design an efficient two-step method: first classify various sets of time series according to their sizes, and then compress the time series with relatively large size by appropriate compression algorithms. This two-step approach is able to reduce the users' response time after requesting the monitoring data, and the compression effects of the algorithms designed are satisfactory. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-77018-3_39 | PAKDD Workshops |
Keywords | Field | DocType |
data users request,response time,time series,appropriate compression algorithm,long transmission time,efficient time series data,monitoring data,compression effect,time series data,sequential time stamp,efficient two-step method,algorithm design,compression algorithm | Data mining,Time series,Sequential time,Computer science,Response time,Real-time computing,Discrete wavelet transform,Transmission time,Discrete Fourier transform,Data compression,Fold (higher-order function) | Conference |
Volume | ISSN | ISBN |
4819 | 0302-9743 | 3-540-77016-X |
Citations | PageRank | References |
1 | 0.37 | 15 |
Authors | ||
5 | ||