Method and device for determining strategy for data placement within ssd

A device for determining a strategy for data placement within an SSD, comprising:

• a processor configured to
• acquire an optimization target and a first workload metric data that is pre-collected for a time period;
• select a machine learning model and a training data strategy according to the optimization target;
• select feature data from the first workload metric data for the time period according to the selected training data strategy, and train the selected machine learning model based on the selected feature data;
• and
• determine in each subsequent predicting time, a strategy for data placement for a predicting time period corresponding to the predicting time according to the first workload metric data for the time period and a second workload metric data that is collected in the predicting time by using the trained machine learning model.

A Solid State Drive (SSD), comprising:

• a memory cell storing computer-readable instructions;
• a processor configured to execute the computer-readable instructions to
• acquire an optimization target and a first workload metric data that is pre-collected for a time period;
• select a machine learning model and a training data strategy according to the optimization target;
• select feature data from the first workload metric data for the time period according to the selected training data strategy, and training the selected machine learning model based on the selected feature data;
• and
• determine, in a plurality of subsequent predicting time periods, a strategy for data placement for a one of the plurality of subsequent predicting time periods according to the first workload metric data for the time period and a second workload metric data that is collected in the one of the plurality of subsequent predicting time periods by using the trained machine learning model.