FuzzySkyline:  QoS-Aware Fuzzy Skyline Parking Recommendation Using Edge Traffic Facilities

Yinglong Li; Jiaye Zhang; Tieming Chen; Weiru Liu

doi:10.1109/IWQOS52092.2021.9521357

FuzzySkyline: QoS-Aware Fuzzy Skyline Parking Recommendation Using Edge Traffic Facilities

Yinglong Li, Jiaye Zhang, Tieming Chen, Weiru Liu

Department of Engineering Mathematics

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

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Abstract

Drivers always confront parking difficulties when driving on urban roads, especially in crowded downtown or beauty spots. Some of the existing literatures concentrate on multi-consideration optimization for parking decision by collecting the nearby real-time parking-related data. Others provide online parking navigation services through outsourced storage and cloud computing. Massive (raw) data transmission and complex processing are always involved in the existing methods, which results in undesired QoS such as real-time performance and privacy protection. In this paper, we propose a fuzzy skyline parking recommendation scheme for real-time parking
recommendation based on roadside traffic facilities. Linguistic parking information instead of raw parking-related data is used in fuzzy skyline fusion. We evaluated our solution with real-world data sets collected from edge parking facilities in Wulin
downtown, Hangzhou city, China. The evaluation results show that our approaches achieve an average accuracy of parking recommendation over 91%, low data transmission, and quick response time with privacy protection.

Original language	English
Title of host publication	2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)	9781665414944
ISBN (Print)	9781665430548
DOIs	https://doi.org/10.1109/IWQOS52092.2021.9521357
Publication status	Published - 26 Aug 2021
Event	IEEE/ACM International Symposium on Quality of Service - Tokyo, Japan, and Virtual Duration: 25 Jun 2021 → 28 Jun 2021 https://iwqos2021.ieee-iwqos.org/

Publication series

Name	2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021

Conference

Conference	IEEE/ACM International Symposium on Quality of Service
Abbreviated title	IWQoS 2021
Period	25/06/21 → 28/06/21
Internet address	https://iwqos2021.ieee-iwqos.org/

Bibliographical note

Funding Information:
The corresponding author is Tieming Chen. This research is supported in part by the Zhejiang Natural Science Foundation of China under Grant LY19F020024, in part by the Key R&D Project of Zhejiang Province under Grant 2021C01117, in part by the 2020 Industrial Internet Innovation and Development Project under Grant TC200H01V, and in part by the Zhejiang Postdoctoral research project under Grant ZJ2020089.

Publisher Copyright:
© 2021 IEEE.

Keywords

Parking recommendation
Skyline fusion
Fuzzy sets
Privacy protection

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Li, Y., Zhang, J., Chen, T., & Liu, W. (2021). FuzzySkyline: QoS-Aware Fuzzy Skyline Parking Recommendation Using Edge Traffic Facilities. In 2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021 (2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021). Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/IWQOS52092.2021.9521357

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abstract = "Drivers always confront parking difficulties when driving on urban roads, especially in crowded downtown or beauty spots. Some of the existing literatures concentrate on multi-consideration optimization for parking decision by collecting the nearby real-time parking-related data. Others provide online parking navigation services through outsourced storage and cloud computing. Massive (raw) data transmission and complex processing are always involved in the existing methods, which results in undesired QoS such as real-time performance and privacy protection. In this paper, we propose a fuzzy skyline parking recommendation scheme for real-time parkingrecommendation based on roadside traffic facilities. Linguistic parking information instead of raw parking-related data is used in fuzzy skyline fusion. We evaluated our solution with real-world data sets collected from edge parking facilities in Wulindowntown, Hangzhou city, China. The evaluation results show that our approaches achieve an average accuracy of parking recommendation over 91%, low data transmission, and quick response time with privacy protection.",

keywords = "Parking recommendation, Skyline fusion, Fuzzy sets, Privacy protection",

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note = "Funding Information: The corresponding author is Tieming Chen. This research is supported in part by the Zhejiang Natural Science Foundation of China under Grant LY19F020024, in part by the Key R&D Project of Zhejiang Province under Grant 2021C01117, in part by the 2020 Industrial Internet Innovation and Development Project under Grant TC200H01V, and in part by the Zhejiang Postdoctoral research project under Grant ZJ2020089. Publisher Copyright: {\textcopyright} 2021 IEEE.; IEEE/ACM International Symposium on Quality of Service, IWQoS 2021 ; Conference date: 25-06-2021 Through 28-06-2021",

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Li, Y, Zhang, J, Chen, T & Liu, W 2021, FuzzySkyline: QoS-Aware Fuzzy Skyline Parking Recommendation Using Edge Traffic Facilities. in 2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021. 2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021, Institute of Electrical and Electronics Engineers (IEEE), IEEE/ACM International Symposium on Quality of Service, 25/06/21. https://doi.org/10.1109/IWQOS52092.2021.9521357

FuzzySkyline: QoS-Aware Fuzzy Skyline Parking Recommendation Using Edge Traffic Facilities. / Li, Yinglong; Zhang, Jiaye; Chen, Tieming et al.
2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021. Institute of Electrical and Electronics Engineers (IEEE), 2021. (2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021).

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

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N1 - Funding Information: The corresponding author is Tieming Chen. This research is supported in part by the Zhejiang Natural Science Foundation of China under Grant LY19F020024, in part by the Key R&D Project of Zhejiang Province under Grant 2021C01117, in part by the 2020 Industrial Internet Innovation and Development Project under Grant TC200H01V, and in part by the Zhejiang Postdoctoral research project under Grant ZJ2020089. Publisher Copyright: © 2021 IEEE.

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N2 - Drivers always confront parking difficulties when driving on urban roads, especially in crowded downtown or beauty spots. Some of the existing literatures concentrate on multi-consideration optimization for parking decision by collecting the nearby real-time parking-related data. Others provide online parking navigation services through outsourced storage and cloud computing. Massive (raw) data transmission and complex processing are always involved in the existing methods, which results in undesired QoS such as real-time performance and privacy protection. In this paper, we propose a fuzzy skyline parking recommendation scheme for real-time parkingrecommendation based on roadside traffic facilities. Linguistic parking information instead of raw parking-related data is used in fuzzy skyline fusion. We evaluated our solution with real-world data sets collected from edge parking facilities in Wulindowntown, Hangzhou city, China. The evaluation results show that our approaches achieve an average accuracy of parking recommendation over 91%, low data transmission, and quick response time with privacy protection.

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Li Y, Zhang J, Chen T, Liu W. FuzzySkyline: QoS-Aware Fuzzy Skyline Parking Recommendation Using Edge Traffic Facilities. In 2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021. Institute of Electrical and Electronics Engineers (IEEE). 2021. (2021 IEEE/ACM 29th International Symposium on Quality of Service, IWQOS 2021). doi: 10.1109/IWQOS52092.2021.9521357