Mobile Application Benchmarking Based on the Resource Usage Monitoring

Author:

Rawassizadeh Reza1

Affiliation:

1. University of Vienna, Austria

Abstract

There are many mobile applications currently available on the market, which have been developed specifically for smart phones. The operating systems of these smart phones are flexible in order to facilitate the application development for programmers regardless of the lower layers of the operating system. Mobile phones like other pervasive devices suffer from resource shortages. These resources vary from the power (battery) consumption to the network bandwidth consumption. In this research we identify and classify mobile resources and propose a monitoring approach to measure resource utilization. The authors provide a monitoring tool, which generates traces about the resource usage. Then they propose a benchmarking model which studies traces and enables users to extract qualitative information about the application from quantitative resource usage traces. Results of the study could assist quality operators to compare similar applications from their resource usage point of view, or profile a single application resource consumption.

Publisher

IGI Global

Subject

Computer Networks and Communications

Reference23 articles.

1. Alia, M., Eide, V. S. W., Paspallis, N., Eliassen, F., Hallsteinsen, S. O., & Papadopoulos, G. A. (2007). A Utility-Based Adaptivity Model for Mobile Applications. International Conference on Advanced Information Networking and Applications Workshops, 2, 556-563).

2. Benchmarks, S. P. E. C. (Standard Performance Evaluation Corporation). (2006). http://spec.org/benchmarks.html.

3. Boslaugh, S., & Watters, P. (2008). Statistics in a Nutshell: A Desktop Quick Reference. (pp. 118-119). O'Reilly Media, Inc.

4. Burney, K. (2009). New Year's Bustle? Vertical Market Expectations for 2009 ICT Spending in the US- From Crisis to Slow, Long-term Recovery. Compass Intelligence.

5. Chalmers, D., & Sloman, M. (1999). A Survey of Quality of Service in Mobile Computing Environments. IEEE Communications Surveys, 2(2).

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. User satisfaction with Arabic COVID-19 apps: Sentiment analysis of users’ reviews using machine learning techniques;Information Processing & Management;2024-05

2. Tool Support for Green Android Development;Software Sustainability;2021

3. Should energy consumption influence the choice of Android third-party HTTP libraries?;Proceedings of the IEEE/ACM 7th International Conference on Mobile Software Engineering and Systems;2020-07-13

4. Towards greener Android application development;Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings;2020-06-27

5. Using Machine Learning and Thematic Analysis Methods to Evaluate Mental Health Apps Based on User Reviews;IEEE Access;2020

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3