Data Compression Technology Dedicated to Distribution and Embedded Systems

In distribution and embedded systems, data compression is often used to reduce the size of flash RAM and transmission data, while a rapid decompression speed enables faster rebooting of the compressed program code. We have developed a new data compression algorithm with a high decompression speed and a good compression rate that is equivalent to zlib, the standard technology in use today. We created a LZSS-based algorithm by optimizing the parsing of data strings. LZSS is known as a high decompression speed algorithm useful for embedded systems, and optimal parsing is well known as a method for improving compression rates [1]. Previously, this combination had not been implemented because statistical code length varies during optimal parsing [1]. Our algorithm overcomes this problem by calculating the probability of the literal or the code ( distance and length ) solving the shortest path problem first. It then constructs a simple code set that enables fast decompression using those probabilities and solves the shortest path problem again. Experiments on the standard evaluation data and wireless sensor network program [2] demonstrated that we can achieve a high compression rate equivalent to zlib and a decompression speed that is twice as fast.