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- Once the all the training data are acquired, the training module performs preprocessing to convert the data from json JSON format into Dictionary format
- In Preprocessing the training Data is normalised normalized and Transformed.
- The preprocessed data (PM data Parameters data content) for all slices and cells which are in time series are converted into forcast forecast series.
- The forecast series is cells PM data parameters for current time instance, Plus the previous past or last four time instance data.
- Similar forecast series data is prepared for all the cells in the slice.
- Data are split into training and validation datasets
- The expected results for each time instance cell data are synthetically generated based on rule conditions and the cell intends.
- Sample training data referred at following source code location components/ml-prediction-ms/train/ExampleSample_train_data_s1.xlsx
Spreadsheets containerType page documentId ExampleSample_train_data_s1_smaller.xlsx.ssc isNew false containerId 137199794 title ExampleSample_train_data_s1_smaller.xlsx
- The training module perform Training against an LSTM model.
- The Training model file are archived.
- The results are manually verified .
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- The data from above topics are used to acquire the current time instance and also the previous last four time instance data for all cells and slice.
- The collected data are parsed, normalisednormalized, transformed and converted into forcase forecast series, the steps followed here are almost the same to the input preprocessing steps used in Training module.
- The preprocess forecast series along with the intend are fed to the ML model to perform prediction for the resource allocation for each cells. The predicted results are further optimised by the 25% +/- on cell config and 10% +/- on slice config thresholds.
- Recommendation for each cell can be maximum of 5120 and the aggregation of maximumNoOfConnections recommended for a slice (sNSSAI) can be upto 110% (10 % buffer) of the intent.
- Now predict recommend suggestions for the cell level configurations (maxNumberOfConns) for a slice. A new micro service will be introduced to do the data processing and prediction for the dynamic data.
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