Compressing the Data Densely by New Geflochtener to Accelerate Web

TL;DR

This paper introduces a new data compression algorithm based on the LZ77 family that efficiently reduces web page size by removing redundancies, achieving significant compression ratios to enhance web speed.

Contribution

A novel compression algorithm utilizing greedy parsing and shortest path techniques to improve data density for web content.

Findings

Achieves 70% redundancy removal in web pages.

Attains 23.75-35% compression ratio.

Reduces bandwidth usage for faster web access.

Abstract

At the present scenario of the internet, there exist many optimization techniques to improve the Web speed but almost expensive in terms of bandwidth. So after a long investigation on different techniques to compress the data without any loss, a new algorithm is proposed based on L Z 77 family which selectively models the references with backward movement and encodes the longest matches through greedy parsing with the shortest path technique to compresses the data with high density. This idea seems to be useful since the single Web Page contains many repetitive words which create havoc in consuming space, so let it removes such unnecessary redundancies with 70% efficiency and compress the pages with 23.75 - 35% compression ratio.