Deployment of vehicular edge clouds: Lessons and challenges

Rita Tse; Giovanni Pau

doi:10.1117/12.2245290

Deployment of vehicular edge clouds: Lessons and challenges

Rita Tse
, Giovanni Pau

Faculty of Applied Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

The notion of edge computing has gained much attraction in recent years as an enabling technology for smart city and internet of things applications. In this paper we report the system challenges and solutions encountered when designing and deploying the Macao Polytechnic Institute Smart City sensing system. A small fleet that serves as proof-of-concept for a country wide urban sensing system in Macao, S.A.R. We focus our attention on how a careful system design can ensure smooth operations and mitigate the natural tension between fleet owners and smart city operators. The first are keen to maximize the fleet operations and reduce the downtime, the later are interested in using the fleets to harvest high-quality and fine granularity sensor data. In designing the Macao Polytechnic Institute vehicular cloud we approached the design constraints and proposed system solutions to minimize the impact of the sensing platform on the fleet operations.

Original language	English
Title of host publication	Eighth International Conference on Digital Image Processing, ICDIP 2016
Editors	Xudong Jiang, Charles M. Falco
Publisher	SPIE
ISBN (Electronic)	9781510605039
DOIs	https://doi.org/10.1117/12.2245290
Publication status	Published - 2016
Event	8th International Conference on Digital Image Processing, ICDIP 2016 - Chengu, China Duration: 20 May 2016 → 23 May 2016

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	10033
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	8th International Conference on Digital Image Processing, ICDIP 2016
Country/Territory	China
City	Chengu
Period	20/05/16 → 23/05/16

UN SDGs

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

SDG 11 Sustainable Cities and Communities

Keywords

Edge Cloud Computing
Fog Computing
Human Centric Computing.
Pervasive Computing
Urban Sensing
Vehicular Networks

Access to Document

10.1117/12.2245290

Cite this

@inproceedings{84ac2a77532345df929fd07faf053129,

title = "Deployment of vehicular edge clouds: Lessons and challenges",

abstract = "The notion of edge computing has gained much attraction in recent years as an enabling technology for smart city and internet of things applications. In this paper we report the system challenges and solutions encountered when designing and deploying the Macao Polytechnic Institute Smart City sensing system. A small fleet that serves as proof-of-concept for a country wide urban sensing system in Macao, S.A.R. We focus our attention on how a careful system design can ensure smooth operations and mitigate the natural tension between fleet owners and smart city operators. The first are keen to maximize the fleet operations and reduce the downtime, the later are interested in using the fleets to harvest high-quality and fine granularity sensor data. In designing the Macao Polytechnic Institute vehicular cloud we approached the design constraints and proposed system solutions to minimize the impact of the sensing platform on the fleet operations.",

keywords = "Edge Cloud Computing, Fog Computing, Human Centric Computing., Pervasive Computing, Urban Sensing, Vehicular Networks",

author = "Rita Tse and Giovanni Pau",

note = "Publisher Copyright: {\textcopyright} 2016 SPIE.; 8th International Conference on Digital Image Processing, ICDIP 2016 ; Conference date: 20-05-2016 Through 23-05-2016",

year = "2016",

doi = "10.1117/12.2245290",

language = "English",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

editor = "Xudong Jiang and Falco, \{Charles M.\}",

booktitle = "Eighth International Conference on Digital Image Processing, ICDIP 2016",

address = "United States",

}

Tse, R & Pau, G 2016, Deployment of vehicular edge clouds: Lessons and challenges. in X Jiang & CM Falco (eds), Eighth International Conference on Digital Image Processing, ICDIP 2016., 1003303, Proceedings of SPIE - The International Society for Optical Engineering, vol. 10033, SPIE, 8th International Conference on Digital Image Processing, ICDIP 2016, Chengu, China, 20/05/16. https://doi.org/10.1117/12.2245290

Deployment of vehicular edge clouds: Lessons and challenges. / Tse, Rita; Pau, Giovanni.
Eighth International Conference on Digital Image Processing, ICDIP 2016. ed. / Xudong Jiang; Charles M. Falco. SPIE, 2016. 1003303 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 10033).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Deployment of vehicular edge clouds

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AU - Tse, Rita

AU - Pau, Giovanni

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N2 - The notion of edge computing has gained much attraction in recent years as an enabling technology for smart city and internet of things applications. In this paper we report the system challenges and solutions encountered when designing and deploying the Macao Polytechnic Institute Smart City sensing system. A small fleet that serves as proof-of-concept for a country wide urban sensing system in Macao, S.A.R. We focus our attention on how a careful system design can ensure smooth operations and mitigate the natural tension between fleet owners and smart city operators. The first are keen to maximize the fleet operations and reduce the downtime, the later are interested in using the fleets to harvest high-quality and fine granularity sensor data. In designing the Macao Polytechnic Institute vehicular cloud we approached the design constraints and proposed system solutions to minimize the impact of the sensing platform on the fleet operations.

AB - The notion of edge computing has gained much attraction in recent years as an enabling technology for smart city and internet of things applications. In this paper we report the system challenges and solutions encountered when designing and deploying the Macao Polytechnic Institute Smart City sensing system. A small fleet that serves as proof-of-concept for a country wide urban sensing system in Macao, S.A.R. We focus our attention on how a careful system design can ensure smooth operations and mitigate the natural tension between fleet owners and smart city operators. The first are keen to maximize the fleet operations and reduce the downtime, the later are interested in using the fleets to harvest high-quality and fine granularity sensor data. In designing the Macao Polytechnic Institute vehicular cloud we approached the design constraints and proposed system solutions to minimize the impact of the sensing platform on the fleet operations.

KW - Edge Cloud Computing

KW - Fog Computing

KW - Human Centric Computing.

KW - Pervasive Computing

KW - Urban Sensing

KW - Vehicular Networks

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U2 - 10.1117/12.2245290

DO - 10.1117/12.2245290

M3 - Conference contribution

AN - SCOPUS:85000578307

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Eighth International Conference on Digital Image Processing, ICDIP 2016

A2 - Jiang, Xudong

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PB - SPIE

Y2 - 20 May 2016 through 23 May 2016

ER -

Deployment of vehicular edge clouds: Lessons and challenges

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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