Fog-based Data Offloading in Urban IoT Scenarios

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

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Fog-based Data Offloading in Urban IoT Scenarios. / Kortoçi, Pranvera; Zheng, Liang; Joe-Wong, Carlee; Di Francesco, Mario; Chiang, Mung.

INFOCOM 2019 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers, 2019. p. 784-792 8737503 (Proceedings - IEEE INFOCOM; Vol. 2019-April).

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Kortoçi, P, Zheng, L, Joe-Wong, C, Di Francesco, M & Chiang, M 2019, Fog-based Data Offloading in Urban IoT Scenarios. in INFOCOM 2019 - IEEE Conference on Computer Communications., 8737503, Proceedings - IEEE INFOCOM, vol. 2019-April, Institute of Electrical and Electronics Engineers, pp. 784-792, IEEE Conference on Computer Communications, Paris, France, 29/04/2019. https://doi.org/10.1109/INFOCOM.2019.8737503

APA

Kortoçi, P., Zheng, L., Joe-Wong, C., Di Francesco, M., & Chiang, M. (2019). Fog-based Data Offloading in Urban IoT Scenarios. In INFOCOM 2019 - IEEE Conference on Computer Communications (pp. 784-792). [8737503] (Proceedings - IEEE INFOCOM; Vol. 2019-April). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/INFOCOM.2019.8737503

Vancouver

Kortoçi P, Zheng L, Joe-Wong C, Di Francesco M, Chiang M. Fog-based Data Offloading in Urban IoT Scenarios. In INFOCOM 2019 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers. 2019. p. 784-792. 8737503. (Proceedings - IEEE INFOCOM). https://doi.org/10.1109/INFOCOM.2019.8737503

Author

Kortoçi, Pranvera ; Zheng, Liang ; Joe-Wong, Carlee ; Di Francesco, Mario ; Chiang, Mung. / Fog-based Data Offloading in Urban IoT Scenarios. INFOCOM 2019 - IEEE Conference on Computer Communications. Institute of Electrical and Electronics Engineers, 2019. pp. 784-792 (Proceedings - IEEE INFOCOM).

Bibtex - Download

@inproceedings{996c4d7b3370464b9f031cc3bd730f92,
title = "Fog-based Data Offloading in Urban IoT Scenarios",
abstract = "Urban environments are a particularly important application scenario for the Internet of Things (IoT). These environments are usually dense and dynamic; in contrast, IoT devices are resource-constrained, thus making reliable data collection and scalable coordination a challenge. This work leverages the fog networking paradigm to devise a multi-tier data offloading protocol suitable for diverse data-centric applications in urban IoT scenarios. Specifically, it takes advantage of heterogeneity in the network so that sensors can collaboratively offload data to each other or to mobile gateways. Second, it evaluates the performance of this offloading process through the amount of data successfully reported to the cloud. In detail, it provides an analytical characterization of data drop-off rates as a random process and derives a light-weight yet efficient method for collaborative data offloading. Finally, it shows that the proposed fog-based solution significantly decreases the data drop-off rate through both analysis and extensive trace-driven simulations based on human mobility data from real urban settings.",
keywords = "collaborative offloading, data drop-off rate, Fog networking, Internet of Things",
author = "Pranvera Korto{\cc}i and Liang Zheng and Carlee Joe-Wong and {Di Francesco}, Mario and Mung Chiang",
year = "2019",
month = "4",
day = "1",
doi = "10.1109/INFOCOM.2019.8737503",
language = "English",
series = "Proceedings - IEEE INFOCOM",
publisher = "Institute of Electrical and Electronics Engineers",
pages = "784--792",
booktitle = "INFOCOM 2019 - IEEE Conference on Computer Communications",
address = "United States",

}

RIS - Download

TY - GEN

T1 - Fog-based Data Offloading in Urban IoT Scenarios

AU - Kortoçi, Pranvera

AU - Zheng, Liang

AU - Joe-Wong, Carlee

AU - Di Francesco, Mario

AU - Chiang, Mung

PY - 2019/4/1

Y1 - 2019/4/1

N2 - Urban environments are a particularly important application scenario for the Internet of Things (IoT). These environments are usually dense and dynamic; in contrast, IoT devices are resource-constrained, thus making reliable data collection and scalable coordination a challenge. This work leverages the fog networking paradigm to devise a multi-tier data offloading protocol suitable for diverse data-centric applications in urban IoT scenarios. Specifically, it takes advantage of heterogeneity in the network so that sensors can collaboratively offload data to each other or to mobile gateways. Second, it evaluates the performance of this offloading process through the amount of data successfully reported to the cloud. In detail, it provides an analytical characterization of data drop-off rates as a random process and derives a light-weight yet efficient method for collaborative data offloading. Finally, it shows that the proposed fog-based solution significantly decreases the data drop-off rate through both analysis and extensive trace-driven simulations based on human mobility data from real urban settings.

AB - Urban environments are a particularly important application scenario for the Internet of Things (IoT). These environments are usually dense and dynamic; in contrast, IoT devices are resource-constrained, thus making reliable data collection and scalable coordination a challenge. This work leverages the fog networking paradigm to devise a multi-tier data offloading protocol suitable for diverse data-centric applications in urban IoT scenarios. Specifically, it takes advantage of heterogeneity in the network so that sensors can collaboratively offload data to each other or to mobile gateways. Second, it evaluates the performance of this offloading process through the amount of data successfully reported to the cloud. In detail, it provides an analytical characterization of data drop-off rates as a random process and derives a light-weight yet efficient method for collaborative data offloading. Finally, it shows that the proposed fog-based solution significantly decreases the data drop-off rate through both analysis and extensive trace-driven simulations based on human mobility data from real urban settings.

KW - collaborative offloading

KW - data drop-off rate

KW - Fog networking

KW - Internet of Things

UR - http://www.scopus.com/inward/record.url?scp=85068219779&partnerID=8YFLogxK

U2 - 10.1109/INFOCOM.2019.8737503

DO - 10.1109/INFOCOM.2019.8737503

M3 - Conference contribution

T3 - Proceedings - IEEE INFOCOM

SP - 784

EP - 792

BT - INFOCOM 2019 - IEEE Conference on Computer Communications

PB - Institute of Electrical and Electronics Engineers

ER -

ID: 35242500