EVALUATING THE PERFORMANCE OF GZIP ALGORITHMS FOR HTTP TRAFFIC COMPRESSION IN MOBILE APPLICATIONS: A COMPARATIVE STUDY ON IOS AND ANDROID

Study investigates the efficacy of the gzip compression algorithm in optimizing HTTP traffic for mobile applications on iOS and Android platforms. With the exponential growth of mobile data consumption, efficient data transmission remains critical for enhancing user experience, reducing latency, and minimizing cellular data costs. We evaluate gzip’s compression ratios, computational overhead, and energy efficiency across diverse network conditions and data types (e.g., JSON, XML). Our experiments, conducted on real devices and emulated environments, demonstrate that gzip reduces payload sizes by 60–80% for text-based data, with marginal CPU utilization (5–15% increase). However, performance trade-offs emerge at higher compression levels, particularly on low-end devices. This article provides actionable insights for developers to balance compression efficiency and resource consumption in mobile ecosystems.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-11
DOI
https://doi.org/10.5281/zenodo.15004459
Primary Topic
Green IT and Sustainability
Type
article
Field-Weighted Citation Impact
0.00
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article

EVALUATING THE PERFORMANCE OF GZIP ALGORITHMS FOR HTTP TRAFFIC COMPRESSION IN MOBILE APPLICATIONS: A COMPARATIVE STUDY ON IOS AND ANDROID

Zenodo (CERN European Organization for Nuclear Research)
Green IT and Sustainability
article

EVALUATING THE PERFORMANCE OF GZIP ALGORITHMS FOR HTTP TRAFFIC COMPRESSION IN MOBILE APPLICATIONS: A COMPARATIVE STUDY ON IOS AND ANDROID

article en

Abstract

Study investigates the efficacy of the gzip compression algorithm in optimizing HTTP traffic for mobile applications on iOS and Android platforms. With the exponential growth of mobile data consumption, efficient data transmission remains critical for enhancing user experience, reducing latency, and minimizing cellular data costs. We evaluate gzip’s compression ratios, computational overhead, and energy efficiency across diverse network conditions and data types (e.g., JSON, XML). Our experiments, conducted on real devices and emulated environments, demonstrate that gzip reduces payload sizes by 60–80% for text-based data, with marginal CPU utilization (5–15% increase). However, performance trade-offs emerge at higher compression levels, particularly on low-end devices. This article provides actionable insights for developers to balance compression efficiency and resource consumption in mobile ecosystems.

Zenodo (CERN European Organization for Nuclear Research)
Decent work and economic growth
Openalex Percentile: Top 56%
Green IT and Sustainability
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