Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs

Andrea Tassi; Ioannis Mavromatis; Robert Piechocki; Andrew Nix; Christian Compton; Tracey Poole; Wolfgang Schuster

doi:10.1109/VTCSpring.2019.8746302

Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs

Andrea Tassi, Ioannis Mavromatis, Robert Piechocki, Andrew Nix, Christian Compton, Tracey Poole, Wolfgang Schuster

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

12 Citations (Scopus)

225 Downloads (Pure)

Abstract

Future Connected and Automated Vehicles (CAVs) will be supervised by cloud-based systems overseeing the overall security and orchestrating traffic flows. Such systems rely on data collected from CAVs across the whole city operational area. This paper develops a Fog Computing-based infrastructure for future Intelligent Transportation Systems (ITSs) enabling an agile and reliable off-load of CAV data. Since CAVs are expected to generate large quantities of data, it is not feasible to assume data off-loading to be completed while a CAV is in the proximity of a single Road-Side Unit (RSU). CAVs are expected to be in the range of an RSU only for a limited amount of time, necessitating data reconciliation across different RSUs, if traditional approaches to data off-load were to be used. To this end, this paper proposes an agile Fog Computing infrastructure, which interconnects all the RSUs so that the data reconciliation is solved efficiently as a by-product of deploying the Random Linear Network Coding (RLNC) technique. Our numerical results confirm the feasibility of our solution and show its effectiveness when operated in a large-scale urban testbed.

Original language	English
Title of host publication	2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings
Subtitle of host publication	VTC2019-Spring
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	6
ISBN (Electronic)	9781728112176
ISBN (Print)	978-1-7281-1218-3
DOIs	https://doi.org/10.1109/VTCSpring.2019.8746302
Publication status	Published - 27 Jun 2019
Event	89th IEEE Vehicular Technology Conference, VTC Spring 2019 - Kuala Lumpur, Malaysia Duration: 28 Apr 2019 → 1 May 2019

Publication series

Name	Vehicular Technology Conference (VTC Spring)
Publisher	IEEE
ISSN (Print)	1090-3038
ISSN (Electronic)	2577-2465

Conference

Conference	89th IEEE Vehicular Technology Conference, VTC Spring 2019
Country/Territory	Malaysia
City	Kuala Lumpur
Period	28/04/19 → 1/05/19

Keywords

Fog computing
ITS
CAV
V2X
Network coding
Data offloading

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/VTCSpring.2019.8746302

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Accepted author manuscript, 2.97 MB

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Tassi, A., Mavromatis, I., Piechocki, R., Nix, A., Compton, C., Poole, T., & Schuster, W. (2019). Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs. In 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings: VTC2019-Spring Article 8746302 (Vehicular Technology Conference (VTC Spring)). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/VTCSpring.2019.8746302

@inproceedings{a2d29f572bd747fba54f233729705ccc,

title = "Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs",

abstract = " Future Connected and Automated Vehicles (CAVs) will be supervised by cloud-based systems overseeing the overall security and orchestrating traffic flows. Such systems rely on data collected from CAVs across the whole city operational area. This paper develops a Fog Computing-based infrastructure for future Intelligent Transportation Systems (ITSs) enabling an agile and reliable off-load of CAV data. Since CAVs are expected to generate large quantities of data, it is not feasible to assume data off-loading to be completed while a CAV is in the proximity of a single Road-Side Unit (RSU). CAVs are expected to be in the range of an RSU only for a limited amount of time, necessitating data reconciliation across different RSUs, if traditional approaches to data off-load were to be used. To this end, this paper proposes an agile Fog Computing infrastructure, which interconnects all the RSUs so that the data reconciliation is solved efficiently as a by-product of deploying the Random Linear Network Coding (RLNC) technique. Our numerical results confirm the feasibility of our solution and show its effectiveness when operated in a large-scale urban testbed. ",

keywords = "Fog computing, ITS, CAV, V2X, Network coding, Data offloading",

author = "Andrea Tassi and Ioannis Mavromatis and Robert Piechocki and Andrew Nix and Christian Compton and Tracey Poole and Wolfgang Schuster",

year = "2019",

month = jun,

day = "27",

doi = "10.1109/VTCSpring.2019.8746302",

language = "English",

isbn = "978-1-7281-1218-3",

series = "Vehicular Technology Conference (VTC Spring)",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

booktitle = "2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings",

address = "United States",

note = "89th IEEE Vehicular Technology Conference, VTC Spring 2019 ; Conference date: 28-04-2019 Through 01-05-2019",

}

Tassi, A, Mavromatis, I, Piechocki, R, Nix, A, Compton, C, Poole, T & Schuster, W 2019, Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs. in 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings: VTC2019-Spring., 8746302, Vehicular Technology Conference (VTC Spring), Institute of Electrical and Electronics Engineers (IEEE), 89th IEEE Vehicular Technology Conference, VTC Spring 2019, Kuala Lumpur, Malaysia, 28/04/19. https://doi.org/10.1109/VTCSpring.2019.8746302

Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs. / Tassi, Andrea; Mavromatis, Ioannis; Piechocki, Robert et al.
2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings: VTC2019-Spring. Institute of Electrical and Electronics Engineers (IEEE), 2019. 8746302 (Vehicular Technology Conference (VTC Spring)).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs

AU - Tassi, Andrea

AU - Mavromatis, Ioannis

AU - Piechocki, Robert

AU - Nix, Andrew

AU - Compton, Christian

AU - Poole, Tracey

AU - Schuster, Wolfgang

PY - 2019/6/27

Y1 - 2019/6/27

N2 - Future Connected and Automated Vehicles (CAVs) will be supervised by cloud-based systems overseeing the overall security and orchestrating traffic flows. Such systems rely on data collected from CAVs across the whole city operational area. This paper develops a Fog Computing-based infrastructure for future Intelligent Transportation Systems (ITSs) enabling an agile and reliable off-load of CAV data. Since CAVs are expected to generate large quantities of data, it is not feasible to assume data off-loading to be completed while a CAV is in the proximity of a single Road-Side Unit (RSU). CAVs are expected to be in the range of an RSU only for a limited amount of time, necessitating data reconciliation across different RSUs, if traditional approaches to data off-load were to be used. To this end, this paper proposes an agile Fog Computing infrastructure, which interconnects all the RSUs so that the data reconciliation is solved efficiently as a by-product of deploying the Random Linear Network Coding (RLNC) technique. Our numerical results confirm the feasibility of our solution and show its effectiveness when operated in a large-scale urban testbed.

AB - Future Connected and Automated Vehicles (CAVs) will be supervised by cloud-based systems overseeing the overall security and orchestrating traffic flows. Such systems rely on data collected from CAVs across the whole city operational area. This paper develops a Fog Computing-based infrastructure for future Intelligent Transportation Systems (ITSs) enabling an agile and reliable off-load of CAV data. Since CAVs are expected to generate large quantities of data, it is not feasible to assume data off-loading to be completed while a CAV is in the proximity of a single Road-Side Unit (RSU). CAVs are expected to be in the range of an RSU only for a limited amount of time, necessitating data reconciliation across different RSUs, if traditional approaches to data off-load were to be used. To this end, this paper proposes an agile Fog Computing infrastructure, which interconnects all the RSUs so that the data reconciliation is solved efficiently as a by-product of deploying the Random Linear Network Coding (RLNC) technique. Our numerical results confirm the feasibility of our solution and show its effectiveness when operated in a large-scale urban testbed.

KW - Fog computing

KW - ITS

KW - CAV

KW - V2X

KW - Network coding

KW - Data offloading

UR - http://www.scopus.com/inward/record.url?scp=85069002679&partnerID=8YFLogxK

U2 - 10.1109/VTCSpring.2019.8746302

DO - 10.1109/VTCSpring.2019.8746302

M3 - Conference Contribution (Conference Proceeding)

SN - 978-1-7281-1218-3

T3 - Vehicular Technology Conference (VTC Spring)

BT - 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 89th IEEE Vehicular Technology Conference, VTC Spring 2019

Y2 - 28 April 2019 through 1 May 2019

ER -

Tassi A, Mavromatis I, Piechocki R, Nix A, Compton C, Poole T et al. Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs. In 2019 IEEE 89th Vehicular Technology Conference, VTC Spring 2019 - Proceedings: VTC2019-Spring. Institute of Electrical and Electronics Engineers (IEEE). 2019. 8746302. (Vehicular Technology Conference (VTC Spring)). Epub 2019 Jun 27. doi: 10.1109/VTCSpring.2019.8746302

Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs

Abstract

Publication series

Conference

Keywords

UN SDGs

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IEEE Best Paper Award

Professor Robert J Piechocki

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Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs

Abstract

Publication series

Conference

Keywords

UN SDGs

Access to Document

Handle.net

Other files and links

Fingerprint

Prizes

IEEE Best Paper Award

Profiles

Professor Robert J Piechocki

Cite this