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Article

Supporting energy-efficient uploading strategies for continuous sensing applications on mobile phones

Authors:

Mirco Musolesi,

Mattia Piraccini,

Antonio Corradi,

Andrew T. CampbellAuthors Info & Claims

Pervasive'10: Proceedings of the 8th international conference on Pervasive Computing

Pages 355 - 372

https://doi.org/10.1007/978-3-642-12654-3_21

Published: 17 May 2010 Publication History

Abstract

Continuous sensing applications (e.g., mobile social networking applications) are appearing on new sensor-enabled mobile phones such as the Apple iPhone, Nokia and Android phones. These applications present significant challenges to the phone's operations given the phone's limited computational and energy resources and the need for applications to share real-time continuous sensed data with back-end servers. System designers have to deal with a trade-off between data accuracy (i.e., application fidelity) and energy constraints in the design of uploading strategies between phones and back-end servers. In this paper, we present the design, implementation and evaluation of several techniques to optimize the information uploading process for continuous sensing on mobile phones. We analyze the cases of continuous and intermittent connectivity imposed by low-duty cycle design considerations or poor wireless network coverage in order to drive down energy consumption and extend the lifetime of the phone. We also show how location prediction can be integrated into this forecasting framework. We present the implementation and the experimental evaluation of these uploading techniques based on measurements from the deployment of a continuous sensing application on 20 Nokia N95 phones used by 20 people for a period of 2 weeks. Our results show that we can make significant energy savings while limiting the impact on the application fidelity, making continuous sensing a viable application for mobile phones. For example, we show that it is possible to achieve an accuracy of 80% with respect to ground-truth data while saving 60% of the traffic sent over-the-air.

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Cited By

Álvarez FAlmon LLieser PMeuser TDylla YRicherzhagen BHollick MSteinmetz RFeldmann MHassan M(2018)Conducting a Large-scale Field Test of a Smartphone-based Communication Network for Emergency ResponseProceedings of the 13th Workshop on Challenged Networks10.1145/3264844.3264845(3-10)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1145/3264844.3264845
Ghosh SGhosh SBarrett RCummings RAgichtein EGabrilovich E(2017)Modeling of Human Movement Behavioral Knowledge from GPS Traces for Categorizing Mobile UsersProceedings of the 26th International Conference on World Wide Web Companion10.1145/3041021.3054150(51-58)Online publication date: 3-Apr-2017
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Wamburu JKaguma DTatsubori MWalcott-Bryant ABryant RWeldemariam KGrundy JHalfond WBuhnova BAutili MMuccini H(2017)Roaming Nairobi roadsProceedings of the 4th International Conference on Mobile Software Engineering and Systems10.1109/MOBILESoft.2017.8(100-109)Online publication date: 20-May-2017
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Information & Contributors

Information

Published In

cover image Guide Proceedings

Pervasive'10: Proceedings of the 8th international conference on Pervasive Computing

May 2010

446 pages

ISBN:3642126537

Editors:
Patrik Floréen
Helsinki Institute for Information Technology – HIIT, Department of Computer Science,, University of Helsinki, Finland
,
Antonio Krüger
Helsinki Institute for Information Technology – HIIT, Department of Computer Science,, German Research Center for Artificial Intelligence (DFKI), Stuhlsatzenhausweg 3, Saarbrücken, Germany
,
Mirjana Spasojevic
Helsinki Institute for Information Technology – HIIT, Department of Computer Science,, Nokia Research Center, Stuhlsatzenhausweg 3, Palo Alto, CA, Germany

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 17 May 2010

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Cited By

Álvarez FAlmon LLieser PMeuser TDylla YRicherzhagen BHollick MSteinmetz RFeldmann MHassan M(2018)Conducting a Large-scale Field Test of a Smartphone-based Communication Network for Emergency ResponseProceedings of the 13th Workshop on Challenged Networks10.1145/3264844.3264845(3-10)Online publication date: 1-Oct-2018
https://dl.acm.org/doi/10.1145/3264844.3264845
Ghosh SGhosh SBarrett RCummings RAgichtein EGabrilovich E(2017)Modeling of Human Movement Behavioral Knowledge from GPS Traces for Categorizing Mobile UsersProceedings of the 26th International Conference on World Wide Web Companion10.1145/3041021.3054150(51-58)Online publication date: 3-Apr-2017
https://dl.acm.org/doi/10.1145/3041021.3054150
Wamburu JKaguma DTatsubori MWalcott-Bryant ABryant RWeldemariam KGrundy JHalfond WBuhnova BAutili MMuccini H(2017)Roaming Nairobi roadsProceedings of the 4th International Conference on Mobile Software Engineering and Systems10.1109/MOBILESoft.2017.8(100-109)Online publication date: 20-May-2017
https://dl.acm.org/doi/10.1109/MOBILESoft.2017.8
Maqsood TKhalid OIrfan RMadani SKhan S(2016)Scalability Issues in Online Social NetworksACM Computing Surveys10.1145/296821649:2(1-42)Online publication date: 16-Sep-2016
https://dl.acm.org/doi/10.1145/2968216
(2016)Power management techniques in smartphone-based mobility sensing systemsPervasive and Mobile Computing10.1016/j.pmcj.2016.01.01031:C(1-21)Online publication date: 1-Sep-2016
https://dl.acm.org/doi/10.1016/j.pmcj.2016.01.010
Xiong HZhang DWang LGibson JZhu J(2015)EEMCACM Transactions on Intelligent Systems and Technology10.1145/26448276:3(1-26)Online publication date: 30-Apr-2015
https://dl.acm.org/doi/10.1145/2644827
Tsujimori TThepvilojanapong NOhta YZhao YTobe YAkerkar RIshikawa FYonezawa TRiedel TNeumann M(2014)History-based Incentive for Crowd SensingProceedings of the 2014 International Workshop on Web Intelligence and Smart Sensing10.1145/2637064.2637089(1-6)Online publication date: 1-Sep-2014
https://dl.acm.org/doi/10.1145/2637064.2637089
Zhang DXiong HWang LChen GBrush AFriday AKientz JScott JSong J(2014)CrowdRecruiterProceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing10.1145/2632048.2632059(703-714)Online publication date: 13-Sep-2014
https://dl.acm.org/doi/10.1145/2632048.2632059
Sarma SVenkatasubramanian NDutt N(2014)Sense-making from Distributed and Mobile Sensing DataProceedings of the 51st Annual Design Automation Conference10.1145/2593069.2596688(1-6)Online publication date: 1-Jun-2014
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Nikzad NChipara OGriswold WJalote PBriand LHoek A(2014)APE: an annotation language and middleware for energy-efficient mobile application developmentProceedings of the 36th International Conference on Software Engineering10.1145/2568225.2568288(515-526)Online publication date: 31-May-2014
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