research-article

SymPhoney: a coordinated sensing flow execution engine for concurrent mobile sensing applications

Authors:

Junehwa SongAuthors Info & Claims

SenSys '12: Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems

Pages 211 - 224

https://doi.org/10.1145/2426656.2426678

Published: 06 November 2012 Publication History

Abstract

Emerging mobile sensing applications are changing the characteristics of smartphone workloads. Whereas typical mobile applications run alone in the foreground interacting with users, sensing applications concurrently run in the background, providing unobtrusive monitoring services. Such concurrent sensing workloads raise a new challenge incurring severe resource contention among themselves and with other foreground applications. To address the challenge, we develop SymPhoney, a coordinated sensing flow execution engine to support concurrent sensing applications. As its key approach, we develop a novel sensing-flow-aware coordination. We first introduce the new concept of frame externalization i.e., to identify and externalize semantic structures embedded in otherwise flat sensing data streams. Leveraging the identified frame structures, SymPhoney develops frame-based coordination and scheduling mechanisms, which effectively coordinates the resource use of concurrent contending applications and maximize their utilities even under severe resource contention. We implemented several sensing applications on top of the SymPhoney engine and performed extensive experiments, showing effective coordination capability of SymPhoney.

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Cited By

Min CLee YYoo CHwang IJu YSong JKang S(2020)Scalable Power Impact Prediction of Mobile Sensing Applications at Pre-Installation TimeIEEE Transactions on Mobile Computing10.1109/TMC.2019.290989719:6(1448-1464)Online publication date: 1-Jun-2020
https://doi.org/10.1109/TMC.2019.2909897
Taleb SHajj HDawy Z(2019)EGO: Optimized Sensor Selection for Multi-Context Aware Applications with an Ontology for Recognition ModelsIEEE Transactions on Mobile Computing10.1109/TMC.2018.287986418:11(2518-2535)Online publication date: 1-Nov-2019
https://doi.org/10.1109/TMC.2018.2879864
Lai FRadi MChipara OGriswold W(2018)Workload Shaping Energy Optimizations with Predictable Performance for Mobile Sensing2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)10.1109/IoTDI.2018.00026(177-188)Online publication date: Apr-2018
https://doi.org/10.1109/IoTDI.2018.00026
Show More Cited By

Index Terms

SymPhoney: a coordinated sensing flow execution engine for concurrent mobile sensing applications
1. Computer systems organization
  1. Embedded and cyber-physical systems
  2. Real-time systems

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Published In

cover image ACM Conferences

SenSys '12: Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems

November 2012

404 pages

ISBN:9781450311694

DOI:10.1145/2426656

General Chair:
Rasit Eskicioglu
University of Manitoba
,
Program Chairs:
Andrew Campbell
Dartmouth College
,
Koen Langendoen
Delft University of Technology

Copyright © 2012 ACM.

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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Published: 06 November 2012

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SenSys '12

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SenSys '12: The 10th ACM Conference on Embedded Network Sensor Systems

November 6 - 9, 2012

Ontario, Toronto, Canada

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Overall Acceptance Rate 174 of 867 submissions, 20%

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Cited By

Min CLee YYoo CHwang IJu YSong JKang S(2020)Scalable Power Impact Prediction of Mobile Sensing Applications at Pre-Installation TimeIEEE Transactions on Mobile Computing10.1109/TMC.2019.290989719:6(1448-1464)Online publication date: 1-Jun-2020
https://doi.org/10.1109/TMC.2019.2909897
Taleb SHajj HDawy Z(2019)EGO: Optimized Sensor Selection for Multi-Context Aware Applications with an Ontology for Recognition ModelsIEEE Transactions on Mobile Computing10.1109/TMC.2018.287986418:11(2518-2535)Online publication date: 1-Nov-2019
https://doi.org/10.1109/TMC.2018.2879864
Lai FRadi MChipara OGriswold W(2018)Workload Shaping Energy Optimizations with Predictable Performance for Mobile Sensing2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI)10.1109/IoTDI.2018.00026(177-188)Online publication date: Apr-2018
https://doi.org/10.1109/IoTDI.2018.00026
Fang ZLuo MYu TMengshoel OSrivastava MGupta R(2018)Mitigating Multi-tenant Interference in Continuous Mobile OffloadingCloud Computing – CLOUD 201810.1007/978-3-319-94295-7_2(20-36)Online publication date: 19-Jun-2018
https://doi.org/10.1007/978-3-319-94295-7_2
Kantarci BMouftah H(2017)Sensing as a Service in Cloud-Centric Internet of Things ArchitectureThe Internet of Things10.4018/978-1-5225-1832-7.ch022(460-490)Online publication date: 2017
https://doi.org/10.4018/978-1-5225-1832-7.ch022
Ardekani MSingh RAgrawal NTerry DSuminto RJayaram KGandhi AKemme BPietzuch P(2017)RivuletProceedings of the 18th ACM/IFIP/USENIX Middleware Conference10.1145/3135974.3135988(41-54)Online publication date: 11-Dec-2017
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Morrison ABakayov V(2017)Stickers for StepsProceedings of the ACM on Human-Computer Interaction10.1145/31347171:CSCW(1-10)Online publication date: 6-Dec-2017
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Alvarado Garcia AYoung ADombrowski L(2017)On Making Data ActionableProceedings of the ACM on Human-Computer Interaction10.1145/31346541:CSCW(1-19)Online publication date: 6-Dec-2017
https://dl.acm.org/doi/10.1145/3134654
Bakst AGleissenthall KKıcı RJhala R(2017)Verifying distributed programs via canonical sequentializationProceedings of the ACM on Programming Languages10.1145/31339341:OOPSLA(1-27)Online publication date: 12-Oct-2017
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Bhattacharya SLane N(2016)Sparsification and Separation of Deep Learning Layers for Constrained Resource Inference on WearablesProceedings of the 14th ACM Conference on Embedded Network Sensor Systems CD-ROM10.1145/2994551.2994564(176-189)Online publication date: 14-Nov-2016
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