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-# SDFVAE
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+# SDFVAE
+
+# Exp_datasets
+Two multivariate time series (structured CDN KPIs) datasets are used in our work (folders named dataset1 and dataset2) which span 78 days and 64 days respectively. <br> 
+These two datasets are collected from two different provincial-level CDN edge sites of a top ISP-operated CDN. <br>
+There are 7 abnormal sequences in dataset 1 and 5 abnormal sequences in dataset 2. <br>
+These labelled abnormal sequences are confirmed by human operators. So they can be considered as the ground truth. <br>
+The KPIs in the datasets include the out-bound traffic and in-bound traffic of CDN servers, cache hit ratio, average bitrate, and so on. <br>
+For privacy reasons, these KPIs are anonymized and normalized. <br>
+
+
+## Dataset Information
+
+### Dataset1
+#### Basic Statistics
+
+Statistics | dataset1
+--- | ---
+Number of KPIs | 24
+Durations (day) | 78
+Granularity (min) | 5
+Number of points | 22,356
+Number of anomaly sequences | 7
+Anomaly ratio (%) | 1.6
+Train period | 1 ∼ 10,656
+Test period | 10,657 ∼ 22,356
+
+#### Data format
+There are 24 CSV files and each file corresponds to a KPI. <br>
+The CSV has the following format: <br>
+* First column is the timestamp <br>
+* Second column is the value <br>
+* Third column is the label. 0 for normal and 1 for abnormal <br>
+
+Timestamp | Value | Label
+--- | --- | ---
+20181001000500 | 0.46444977152338346 | 0
+20181001001000 | 0.4423121844530866 | 0
+20181001001500 | 0.4186436700242946 | 0
+20181001002000 | 0.39892597116922146 | 1
+20181001002500 | 0.37977501905111494 | 1
+20181001003000 | 0.36615750635812155 | 1
+
+### Dataset2
+
+#### Basic Statistics
+
+Statistics | dataset2
+--- | ---
+Number of KPIs | 16
+Durations (day) | 64
+Granularity (min) | 1
+Number of points | 91,507
+Number of anomaly sequences | 5
+Anomaly ratio (%) | 0.32
+Train period | 1 ∼ 51,336
+Test period | 51,337 ∼ 91,507
+
+#### Data format
+There are 2 CSV files in the folder named "dataset2". <br>
+The file named "dataset2.csv" is the full data, and "dataset2_sample.csv" is the sample which contains 1000 records. <br>
+The CSV has the following format: <br>
+* First column is the timestamp <br>
+* 2nd~17th columns are the KPI values which correspond to 16 KPIs <br>
+* The last column is the label. 0 for normal and 1 for abnormal <br>
+
+Timestamp | Kpi1 | ... | Kpi16 | Label
+--- | --- | --- | --- | ---
+20190903000200 | 0.46444977152338346 | ... | -0.588230235 | 0 |
+20190903000300 | 0.4423121844530866 | ... | -0.595955299 | 0 |
+20190903000400 | 0.4186436700242946 | ... | -0.600299795 | 0 |
+20190903000500 | 0.39892597116922146 | ... | -0.604815951 | 1 |
+20190903000600 | 0.37977501905111494 | ... | -0.610974025 | 1 |
+20190903000700 | 0.36615750635812155 | ... | -0.616264816 | 1 |
+
+### Public Dataset 
+The public dataset (SMD) used in our evaluation experiments as well as its detailed description can be found in web sites:
+https://github.com/NetManAIOps/OmniAnomaly
+
+For simplicity, we select 2 of 28 machine data namely "machine-1-2.txt" and "machine-1-3.txt" to conduct evaluation experiments.
+
+**Note that all KPIs are normalized and we omitted the real name of each KPI for confidentiality, but this does not affect the accuracy of the evaluation experiments.**