Abstract: A storage system may be connected to a machine learning model embedded device that includes a trained simulation model. The simulation model may be trained based on a loss function, where the loss function is based on a comparison of predicted QoS data and real QOS data. The simulation model may be trained to search for a workload for increasing the QoS using a fixed parameter or, conversely, to search for a parameter for maximizing the QoS using a fixed workload. Further, the machine learning model embedded device may include a map table storing the optimized parameters calculated by the trained simulation model so as to maximize QoS relative to each workload.

Abstract: A storage device includes; an interface receiving data and a corresponding LBA from a host, wherein the data includes at least one of first data having a stream ID and second data lacking a stream ID, a nonvolatile memory (NVM) device including at least one nonvolatile memory configured to store the data, and a LBA predictor configured to provide a predicted stream ID for the second data using a neural network model operating in response to at least one feature associated with LBA values received by the storage device from the host, wherein the first data is stored in the NVM device using the stream ID, and the data is stored in the NVM device using the predicted stream ID.

Abstract: A storage device includes; an interface receiving data and a corresponding LBA from a host, wherein the data includes at least one of first data having a stream ID and second data lacking a stream ID, a nonvolatile memory (NVM) device including at least one nonvolatile memory configured to store the data, and a LBA predictor configured to provide a predicted stream ID for the second data using a neural network model operating in response to at least one feature associated with LBA values received by the storage device from the host, wherein the first data is stored in the NVM device using the stream ID, and the data is stored in the NVM device using the predicted stream ID.

Abstract: A data storage device and a method for operating the data storage device are disclosed. The data storage device may include an interface receiving a command and data from a host, a cache temporarily storing the received data, a memory non-temporarily storing the data stored in the cache, and a controller controlling the memory and the cache based on the command received from the host. The command may include charge rate of a battery supplying a power to the data storage device. The controller may determine whether or not the data storage device is an idle state, and determine an active operation mode of the data storage device based on the charge rate of the battery, when the data storage device is the idle state.

Abstract: A data storage device and a method for operating the data storage device are disclosed. The data storage device may include an interface receiving a command and data from a host, a cache temporarily storing the received data, a memory non-temporarily storing the data stored in the cache, and a controller controlling the memory and the cache based on the command received from the host. The command may include charge rate of a battery supplying a power to the data storage device. The controller may determine whether or not the data storage device is an idle state, and determine an active operation mode of the data storage device based on the charge rate of the battery, when the data storage device is the idle state.