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Enabling Fine-Grained Edge Offloading for IoT

Authors:

Vittorio Cozzolino,

Aaron Yi Ding,

Jorg Ott,

Dirk KutscherAuthors Info & Claims

SIGCOMM Posters and Demos '17: Proceedings of the SIGCOMM Posters and Demos

Pages 124 - 126

https://doi.org/10.1145/3123878.3132009

Published: 22 August 2017 Publication History

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Abstract

In this paper we make the case for IoT edge offloading, which strives to exploit the resources on edge computing devices by offloading fine-grained computation tasks from the cloud closer to the users and data generators (i.e., IoT devices). The key motive is to enhance performance, security and privacy for IoT services. Our proposal bridges the gap between cloud computing and IoT by applying a divide and conquer approach over the multi-level (cloud, edge and IoT) information pipeline. To validate the design of IoT edge offloading, we developed a unikernel-based prototype and evaluated the system under various hardware and network conditions. Our experimentation has shown promising results and revealed the limitation of existing IoT hardware and virtualization platforms, shedding light on future research of edge computing and IoT.

References

[1]

Bhardwaj et al. 2016. Fast, scalable and secure onloading of edge functions using AirBox. In IEEE/ACM Symposium on Edge Computing (SEC). IEEE.

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Google Scholar

[2]

Kumar et al. 2013. A survey of computation offloading for mobile systems. Mobile Networks and Applications 18, 1 (2013), 129--140.

Digital Library

Google Scholar

[3]

Madhavapeddy et al. 2013. Unikernels: Library operating systems for the cloud. In ACM SIGPLAN Notices, Vol. 48. ACM.

Digital Library

Google Scholar

[4]

Madhavapeddy et al. 2015. Jitsu: Just-In-Time Summoning of Unikernels. In Proceedings of NSDI '15.

Digital Library

Google Scholar

Cited By

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Chifor BArseni ȘBica I(2021)IoT Cloud Security Design PatternsBig Data Platforms and Applications10.1007/978-3-030-38836-2_6(113-164)Online publication date: 29-Sep-2021
https://doi.org/10.1007/978-3-030-38836-2_6
Hawthorne DKapralos MBlaine RMatthews S(2020)Evaluating Cryptographic Performance of Raspberry Pi Clusters2020 IEEE High Performance Extreme Computing Conference (HPEC)10.1109/HPEC43674.2020.9286247(1-9)Online publication date: 22-Sep-2020
https://doi.org/10.1109/HPEC43674.2020.9286247
Silva DSofia R(2020)A Discussion on Context-Awareness to Better Support the IoT Cloud/Edge ContinuumIEEE Access10.1109/ACCESS.2020.30323888(193686-193694)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3032388
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Enabling Fine-Grained Edge Offloading for IoT

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Information

Published In

SIGCOMM Posters and Demos '17: Proceedings of the SIGCOMM Posters and Demos

August 2017

158 pages

ISBN:9781450350570

DOI:10.1145/3123878

Co-chairs:
Jeff Burke
UCLA
,
Matthias Wählisch
Freie Universität Berlin
,
Nicholas Zhang
Huawei Technologies, China
,
David Meyer
University of Oregon/Brocade
,
Puneet Sharma
Hewlett Packard Labs

Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 August 2017

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Poster
Research
Refereed limited

Conference

SIGCOMM '17

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SIGCOMM

SIGCOMM '17: ACM SIGCOMM 2017 Conference

August 22 - 24, 2017

CA, Los Angeles, USA

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Overall Acceptance Rate 92 of 158 submissions, 58%

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Cited By

View all

Chifor BArseni ȘBica I(2021)IoT Cloud Security Design PatternsBig Data Platforms and Applications10.1007/978-3-030-38836-2_6(113-164)Online publication date: 29-Sep-2021
https://doi.org/10.1007/978-3-030-38836-2_6
Hawthorne DKapralos MBlaine RMatthews S(2020)Evaluating Cryptographic Performance of Raspberry Pi Clusters2020 IEEE High Performance Extreme Computing Conference (HPEC)10.1109/HPEC43674.2020.9286247(1-9)Online publication date: 22-Sep-2020
https://doi.org/10.1109/HPEC43674.2020.9286247
Silva DSofia R(2020)A Discussion on Context-Awareness to Better Support the IoT Cloud/Edge ContinuumIEEE Access10.1109/ACCESS.2020.30323888(193686-193694)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3032388
Cao XWang FXu JZhang RCui S(2019)Joint Computation and Communication Cooperation for Energy-Efficient Mobile Edge ComputingIEEE Internet of Things Journal10.1109/JIOT.2018.28752466:3(4188-4200)Online publication date: Jun-2019
https://doi.org/10.1109/JIOT.2018.2875246
Constantinou GSankar Ramachandran GAlfarrarjeh AKim SKrishnamachari BShahabi C(2019)A Crowd-Based Image Learning Framework using Edge Computing for Smart City Applications2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM)10.1109/BigMM.2019.00-47(11-20)Online publication date: Sep-2019
https://doi.org/10.1109/BigMM.2019.00-47
Goethals TSebrechts MAtrey AVolckaert BDe Turck F(2018)Unikernels vs Containers: An In-Depth Benchmarking Study in the Context of Microservice Applications2018 IEEE 8th International Symposium on Cloud and Service Computing (SC2)10.1109/SC2.2018.00008(1-8)Online publication date: Nov-2018
https://doi.org/10.1109/SC2.2018.00008
Mahmoudi CMourlin F(2018)MOCP: An Offloading Protocol for Mobile Cloud and IoT virtualization2018 International Conference on Selected Topics in Mobile and Wireless Networking (MoWNeT)10.1109/MoWNet.2018.8428923(1-8)Online publication date: Jun-2018
https://doi.org/10.1109/MoWNet.2018.8428923
Yu ZWang JQi QLiao JXu J(2018)Boundless Application and Resource Based on Container TechnologyEdge Computing – EDGE 201810.1007/978-3-319-94340-4_3(34-48)Online publication date: 16-Jun-2018
https://doi.org/10.1007/978-3-319-94340-4_3

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