A universal compression strategy using sorting transformation
by Bo Liu; Xi Huang; Xiaoguang Liu; Gang Wang; Ming Xu
International Journal of Computational Science and Engineering (IJCSE), Vol. 18, No. 3, 2019

Abstract: Although traditional universal compression algorithms can effectively utilise repetition located in a slide window, they cannot take their own advantages for some message source in which similar messages are distributed uniformly. In this paper, we come up with a universal segmenting-sorting compression algorithm to solve this problem. The key idea is to reorder the message source before compressing it with Lz77 algorithm. We design transformation methods for two common data types, corpus of webpages and access log. The experimental results show that segmenting-sorting transformation is truly beneficial to compression ratio. Our new algorithm is able to make compression ratio 20% to 50% lower than naive Lz77 algorithm does and takes almost the same decompression time. For some read-heavy source segmenting-sorting compression can reduce space cost while guaranteeing throughput.

Online publication date: Tue, 26-Mar-2019

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com