earticle

영어

Files are created for Traffic Analysis, Maintenance, Software debugging, customer management at multiple places like System Services, User Monitoring Applications, Network servers, database management systems which must be kept for long periods of time. These Files may grow to huge sizes in this complex systems and environments. For storage and convenience files must be compressed. Most of the existing algorithms do not take temporal redundancy specific Files into consideration. We propose a Linear Cellular Automaton based Classifier which introduces a multidimensional File compression scheme described in eight variants, differing in complexity and attained compression ratios. This scheme introduces a transformation for File whose compressible output is far better than general purpose algorithms. This proposed method was found lossless and fully automatic. It does not impose any constraint on the size of File.