Performance and Energy Consumption of Lossless Compression/Decompression Utilities on Mobile Computing Platforms

Abstract

Abstract-Data compression and decompression utilities can be critical in increasing communication throughput, reducing communication latencies, achieving energy-efficient communication, and making effective use of available storage. This paper experimentally evaluates several such utilities for multiple compression levels on systems that represent current mobile platforms. We characterize each utility in terms of its compression ratio, compression and decompression throughput, and energy efficiency. We consider different use cases that are typical for modern mobile environments. We find a wide variety of energy costs associated with data compression and decompression and provide practical guidelines for selecting the most energy efficient configurations for each use case. The best performing configurations provide 6-fold and 4-fold improvements in energy efficiency for compressed uploads and downloads over WLAN, respectively, when compared to uncompressed data transfers.

Quantifying Benefits of Lossless Compression Utilities on Modern Smartphones

“…The importance of lossless compression on consumer devices has been widely recognized [9]. This article complements our earlier study on Linux-based mobile development platforms with limited connectivity [10], [11] and other studies that were conducted about a decade ago [12], [13]. In contrast to these prior studies, here we consider the most recent compression utilities including some with parallel implementations, our setup supports more accurate energy measurements, and we use a state-of-the-art smartphone with four processor cores and wireless and cellular communication interfaces.…”

On effectiveness of lossless compression in transferring mHealth data files

“…A useful metric for describing efficiency of networked data transfers is the effective throughput, Th, expressed in megabytes per second [8]. For uncompressed file uploads Th.UUP is determined as US/T.UUP; for compressed file uploads the effective upload throughput is Th.CUP = US/(T.UUP/CR + T.C), where CR is the compression ratio.…”

Analytical Models for Evaluating Effectiveness of Compressed File Transfers in Mobile Computing

“…The effective upload and download throughputs and energy efficiencies depend on many factors, including the file size and type, selected compression utility, the compression level, network characteristics such as latency and throughput, as well as the smartphone's performance and energyefficiency. Whereas previous studies showed that compressed uploads and downloads can save time and energy in many typical file transfers initiated from smartphones Dzhagaryan and Milenkovic, 2015;Milenkovic et al, 2013b) there is not a single upload or download file transfer method that works the best for all data types and network conditions. To underscore this problem, we conduct a measurement-based study that evaluates the effectiveness of various data transfer options under different network conditions.…”

“…The importance of lossless compression in network data transfers has also been recognized in academia (Barr and Asanović, 2003;2006;Dzhagaryan et al, 2013). Recent studies Milenkovic et al, 2013b) focused on a measurement-based experimental evaluation of compressed and uncompressed file transfers on the state-of-the-art mobile devices.…”