relation: https://khub.utp.edu.my/scholars/6205/
title: A lossless compression technique to increase robustness in big data transmission system
creator: Bhattacharjee, S.
creator: Rahim, L.B.A.
creator: Aziz, I.B.A.
description: Data loss during big data transmission is an important issue. Data loss occurs due to various transmission errors, channel noises and huge data size, which increases channel congestion and transmission delay. However, these issues can be controlled by using data compression. Generally, these compression techniques are lossy and lossless in nature. The lossy technique degrades data quality during compression while in lossless compression, the output remains the same as the input. Among the two types of lossless compression, variable length coding (VLC) is efficient to compress data while fixed length coding (FLC) produces poor efficiencies in big data compression. Furthermore, VLCs offer poor robustness against various errors and channel noises during transmission. Hence, to solve the problem of compression efficiency, robustness and time delay in big data transmission, we have designed a FLC based compression. Efficiencies of the proposed technique in various aspects are measured using standard files of various types and sizes as inputs. The result shows that it offers better compression efficiencies by producing lower compression ratio and better compression percentage than other existing techniques. Its capacity to produce better signal to noise ratio (SNR) and throughput justify its capacity to increase robustness and reduce time delay.
publisher: International Center for Scientific Research and Studies
date: 2015
type: Article
type: PeerReviewed
identifier:   Bhattacharjee, S. and Rahim, L.B.A. and Aziz, I.B.A.  (2015) A lossless compression technique to increase robustness in big data transmission system.  International Journal of Advances in Soft Computing and its Applications, 7 (3).  pp. 126-145.  ISSN 20748523     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949794923&partnerID=40&md5=a48d41c5d0191ff9ecfe6cc32cd9c779