A Data Compression Manager (DCM) that can help a data provider (DP) and a data consumer (DC) to establish a data transfer using an advantageous data compression method. In one embodiment, when a DC wants to get some data from a DC, the DP will contact the DCM and the DCM will then choose data compression information based on (i.e., based at least on), for example, current conditions within the network (e.g., a maximum available network bandwidth), information about the data to be compressed (e.g., the type of the data), and/or the DC's data error tolerance. Then the DCM will indicate to the DP the chosen data compression information. The DP will then i) inform the DC of the compression information that is needed by the DC to decompress the data and ii) provide the requested data to the DC in compressed form.

To facilitate storage of data from plural data sources of an industrial automation control system, power distribution system or power generation system, a decision making device executes a machine learning algorithm to determine a compression technique in dependence on the data source from which data originates.

An image compression method and an image compressor are provided. The image compression method compresses the image data based on the fixed-length code (FLC) to generate the compressed data, and includes the following steps: determining whether a characteristic value of the image data meets a condition; encoding only the luminance component of the image data to generate the compressed data when the characteristic value meets the condition; encoding the luminance and chrominance components of the image data to generate the compressed data when the characteristic value does not meet the condition; and storing the compressed data.

A method for managing data includes obtaining a compression algorithm selection request for a data object, wherein the data object is generated by a production host, identifying, in response to the compression algorithm selection request, a set of production host performance objectives of the production host, performing a compression algorithm selection analysis using the set of production host performance objectives and a compression selection model to obtain a compression algorithm selection for a compression algorithm, specifying the compression algorithm to the production host using a data agent, wherein the data agent is operatively connected to the production host, initiating a compression on the data object using the data agent by applying the compression algorithm to obtain a compressed data object, and initiating a storage of the compressed data object.

A data model is trained to determine whether data is raw, compressed, and/or encrypted. The data model may also be trained to recognize which compression algorithm was used to compress data and predict compression ratios for the data using different compression algorithms. A storage system uses the data model to independently identify raw data. The raw data is grouped based on similarity of statistical features and group members are compressed with the same compression algorithm and may be encrypted after compression with the same encryption algorithm. The data model may also be used to identify sub-optimally compressed data, which may be uncompressed and grouped for compression using a different compression algorithm.

This application provides a data compression method and apparatus, and relates to the field of storage technologies. The method includes: after receiving to-be-stored first data, a storage device may determine whether the first data is hot write data, and compress the first data using a selected compression algorithm if the first data is not hot write data.

A data processing device communicating with a memory device via a memory interface includes: at least one data processor configured to generate first data; a data converter configured to generate second data written to the memory device from the first data; and a controller configured to enable the data converter to generate the second data having a size less than that of the first data to reduce power consumption in at least one of the memory device or the memory interface.

A data processing device communicating with a memory device via a memory interface includes: at least one data processor configured to generate first data; a data converter configured to generate second data written to the memory device from the first data; and a controller configured to enable the data converter to generate the second data having a size less than that of the first data.

A computer system includes a plurality of hardware processors, and a hardware accelerator. A first processor among the plurality of processor runs an application that issues a data compression request to compress or decompress a data stream. The hardware accelerator selectively operates in different modes to compresses or decompresses the data stream. Based on a selected mode, the hardware accelerator can utilize a different number of processors among the plurality of hardware to compress or decompress the data stream.

A data encoding system includes a non-transitory memory, a processor, a digital-to-analog converter (DAC) and a transmitter. The non-transitory memory stores a predetermined file size threshold. The processor is in operable communication with the memory, and is configured to receive data. The processor detects a file size associated with the data. When the file size is below the predetermined file size threshold, the processor compresses the data using a variable length codeword (VLC) encoder. When the file size is not below the predetermined file size threshold, the processor compresses the data, using a hash table algorithm. The DAC is configured to receive a digital representation of the compressed data from the processor and convert the digital representation of the compressed data into an analog representation of the compressed data. The transmitter is coupled to the DAC and configured to transmit the analog representation of the compressed data.