Data Compression Limits

Data Compression Has Limited IoT Effectiveness

The only form of data optimization currently available to the industry comes in the form of basic pattern reduction, also referred to as data compression.  A compression algorithm removes consecutive repeated bytes and byte patterns within the data frame and provides a simple control protocol so they can be reinserted when the data payload is eventually decompressed.  While these algorithms can be effective tools for reducing some of the network bandwidth in most IoT implementations, there is not a lot of wasted space in the records sent. Therefore, compression alleviates maybe 10%, and at most 40%, of an IoT average payload.  These gains are meaningless when faced with the data growth curves projected by the next generation of sensor and automated smart systems (100% to 10,000%).  Also, in most sensor implementations where the record size is small, compression does absolutely nothing to reduce the number of network frames needed to be sent.