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Characterizing and modeling the impact of wireless signal strength on smartphone battery drain

Published: 17 June 2013 Publication History

Abstract

Despite the tremendous market penetration of smartphones, their utility has been and will remain severely limited by their battery life. A major source of smartphone battery drain is accessing the Internet over cellular or WiFi connection when running various apps and services. Despite much anecdotal evidence of smartphone users experiencing quicker battery drain in poor signal strength, there has been limited understanding of how often smartphone users experience poor signal strength and the quantitative impact of poor signal strength on the phone battery drain. The answers to such questions are essential for diagnosing and improving cellular network services and smartphone battery life and help to build more accurate online power models for smartphones, which are building blocks for energy profiling and optimization of smartphone apps. In this paper, we conduct the first measurement and modeling study of the impact of wireless signal strength on smartphone energy consumption. Our study makes four contributions. First, through analyzing traces collected on 3785 smartphones for at least one month, we show that poor signal strength of both 3G and WiFi is routinely experienced by smartphone users, both spatially and temporally. Second, we quantify the extra energy consumption on data transfer induced by poor wireless signal strength. Third, we develop a new power model for WiFi and 3G that incorporates the signal strength factor and significantly improves the modeling accuracy over the previous state of the art. Finally, we perform what-if analysis to quantify the potential energy savings from opportunistically delaying network traffic by exploring the dynamics of signal strength experienced by users.

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      Published In

      cover image ACM SIGMETRICS Performance Evaluation Review
      ACM SIGMETRICS Performance Evaluation Review  Volume 41, Issue 1
      Performance evaluation review
      June 2013
      385 pages
      ISSN:0163-5999
      DOI:10.1145/2494232
      Issue’s Table of Contents
      • cover image ACM Conferences
        SIGMETRICS '13: Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
        June 2013
        406 pages
        ISBN:9781450319003
        DOI:10.1145/2465529
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 17 June 2013
      Published in SIGMETRICS Volume 41, Issue 1

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      Author Tags

      1. battery drain
      2. energy
      3. power model
      4. signal strength
      5. smartphone

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      Cited By

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      • (2024)EdgStr: Automating Client-Cloud to Client-Edge-Cloud Transformation2024 IEEE 44th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS60910.2024.00061(589-600)Online publication date: 23-Jul-2024
      • (2024)A Learning-Based and Network-Aware Power Management for Mobile Devices2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC)10.1109/COMPSAC61105.2024.00123(894-899)Online publication date: 2-Jul-2024
      • (2023)The Integration of WoT and Edge Computing: Issues and ChallengesSustainability10.3390/su1507598315:7(5983)Online publication date: 30-Mar-2023
      • (2023)Comparison of Cumulative Power Consumption with Signal Strength Variations in New Generation Wireless NetworksWireless Personal Communications: An International Journal10.1007/s11277-023-10171-3129:2(1025-1048)Online publication date: 15-Feb-2023
      • (2023)Lowering and Analyzing the Power Consumption of SmartphonesIntelligent Computing and Optimization10.1007/978-3-031-50327-6_29(274-288)Online publication date: 16-Dec-2023
      • (2022)A Survey of Performance Optimization for Mobile ApplicationsIEEE Transactions on Software Engineering10.1109/TSE.2021.307119348:8(2879-2904)Online publication date: 1-Aug-2022
      • (2022)Optimizing NB-IoT Power Consumption via Adaptive Radio AccessIEEE Internet of Things Journal10.1109/JIOT.2021.31075089:6(4693-4703)Online publication date: 15-Mar-2022
      • (2022)Use of real time localization systems (RTLS) in the automotive production and the prospects of 5G – A literature reviewProduction & Manufacturing Research10.1080/21693277.2022.214452210:1(840-874)Online publication date: 17-Nov-2022
      • (2022)A framework to improve smartphone supply chain defects: social media analytics approachSocial Network Analysis and Mining10.1007/s13278-022-00982-w12:1Online publication date: 25-Oct-2022
      • (2022)A GPU Accelerated Hyperspectral 3D Convolutional Neural Network Classification at the Edge with Principal Component Analysis PreprocessingParallel Processing and Applied Mathematics10.1007/978-3-031-30445-3_11(127-138)Online publication date: 11-Sep-2022
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