Empirical and Statistical Evaluation of the Effectiveness of Four Lossless Data Compression Algorithms

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dc.contributor.authorAZEEZ, Nureni
dc.date.accessioned2019-08-31T17:43:02Z
dc.date.available2019-08-31T17:43:02Z
dc.date.issued2016
dc.description.abstractData compression is the process of reducing the size of a file to effectively reduce storage space and communication cost. The evolvement in technology and digital age has led to an unparalleled usage of digital files in this current decade. The usage of data has resulted to an increase in the amount of data being transmitted via various channels of data communication which has prompted the need to look into the current lossless data compression algorithms to check for their level of effectiveness so as to maximally reduce the bandwidth in communication and transfer of data. Four lossless data compression algorithm:Lempel-Ziv Welch algorithm, Shannon-Fano algorithm, Adaptive Huffman algorithm and Run-Length encoding have been selected for implementation. Their level of efficiency and effectiveness were evaluated using some set of predefined performance evaluation metrics namely compression ratio, compression factor, compression time, saving percentage, entropy and code efficiency. The algorithms implementation was done in the NetBeans Integrated Development Environment using Java as the programming language. Through the statistical analysis performed using Boxplot and ANOVA and comparison made on the four algorithms, Lempel Ziv Welch algorithm was the most efficient and effective based on the metrics used for evaluation.en_US
dc.identifier.urihttps://ir.unilag.edu.ng/handle/123456789/5032
dc.publisherNigerian Journal of Technological Development, UNILORINen_US
dc.subjectData Compression, lossless, evaluation, entropy, algorithmen_US
dc.titleEmpirical and Statistical Evaluation of the Effectiveness of Four Lossless Data Compression Algorithmsen_US
dc.typeArticleen_US
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