Block-Split Array Coding Algorithm for Long-Stream Data Compression. (18th February 2020)

• Record Type: Journal Article
• Authors: Jiancheng, Qin; Yiqin, Lu; Yu, Zhong
• Other Names: Ahmad Harith Academic Editor.
• Is Part Of: Journal of sensors. Volume 2020(2020)
• Publication Date: 2020-02-18
• Subjects: Detectors -- Periodicals; 681.205
• DOI: 10.1155/2020/5726527
• Languages: English
• ISSNs: 1687-725X

Abstract

Abstract : With the advent of IR (Industrial Revolution) 4.0, the spread of sensors in IoT (Internet of Things) may generate massive data, which will challenge the limited sensor storage and network bandwidth. Hence, the study of big data compression is valuable in the field of sensors. A problem is how to compress the long-stream data efficiently with the finite memory of a sensor. To maintain the performance, traditional techniques of compression have to treat the data streams on a small and incompetent scale, which will reduce the compression ratio. To solve this problem, this paper proposes a block-split coding algorithm named "CZ-Array algorithm, " and implements it in the shareware named "ComZip." CZ-Array can use a relatively small data window to cover a configurable large scale, which benefits the compression ratio. It is fast with the time complexity O(N ) and fits the big data compression. The experiment results indicate that ComZip with CZ-Array can obtain a better compression ratio than gzip, lz4, bzip2, and p7zip in the multiple stream data compression, and it also has a competent speed among these general data compression software. Besides, CZ-Array is concise and fits the hardware parallel implementation of sensors.