Maximizing clearance rate of reputation-aware auctions in mobile crowdsensing

Maggie E. Gendy; Ahmad Al-Kabbany; Ehab F. Badran

doi:10.1109/CCNC.2019.8651693

Maximizing clearance rate of reputation-aware auctions in mobile crowdsensing

Maggie E. Gendy, Ahmad Al-Kabbany, Ehab F. Badran

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

5 Citations (Scopus)

Abstract

This research is concerned with maximizing the clearance rate (CR) of reputation-aware (RA) auctions for assigning tasks in mobile crowdsensing (MCS) systems-CR refers to the percentage of items that are sold over the duration of the auction. Towards maximizing CR during task allocation, we propose two new bidding procedures. Through simulations under varying system parameters, we demonstrate the effectiveness of the suggested methods through consistent and considerable increases in the CR compared to the state-of-the-art.

Original language	English
Title of host publication	CCNC 2019: 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)
Editors	Alan Kaplan
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Number of pages	2
ISBN (Electronic)	9781538655535
ISBN (Print)	9781538655542
DOIs	https://doi.org/10.1109/CCNC.2019.8651693
Publication status	Published - 2019
Externally published	Yes
Event	IEEE Consumer Communications and Networking Conference 2019 - Las Vegas, United States of America Duration: 11 Jan 2019 → 14 Jan 2019 Conference number: 16th https://ieeexplore.ieee.org/xpl/conhome/8648166/proceeding (Proceedings) https://ccnc2019.ieee-ccnc.org/index.html#:~:text=2019%20IEEE%20CCNC%20%7C%20IEEE%20Consumer,%2F%2F%20Las%20Vegas%20%2F%2F%20USA (Website)

Conference

Conference	IEEE Consumer Communications and Networking Conference 2019
Abbreviated title	CCNC 2019
Country/Territory	United States of America
City	Las Vegas
Period	11/01/19 → 14/01/19
Internet address	https://ieeexplore.ieee.org/xpl/conhome/8648166/proceeding (Proceedings) https://ccnc2019.ieee-ccnc.org/index.html#:~:text=2019%20IEEE%20CCNC%20%7C%20IEEE%20Consumer,%2F%2F%20Las%20Vegas%20%2F%2F%20USA (Website)

Keywords

Auctions
Descriptive bidding
Internet of things
Mobile crowdsensing

Access to Document

10.1109/CCNC.2019.8651693

Cite this

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title = "Maximizing clearance rate of reputation-aware auctions in mobile crowdsensing",

abstract = "This research is concerned with maximizing the clearance rate (CR) of reputation-aware (RA) auctions for assigning tasks in mobile crowdsensing (MCS) systems-CR refers to the percentage of items that are sold over the duration of the auction. Towards maximizing CR during task allocation, we propose two new bidding procedures. Through simulations under varying system parameters, we demonstrate the effectiveness of the suggested methods through consistent and considerable increases in the CR compared to the state-of-the-art.",

keywords = "Auctions, Descriptive bidding, Internet of things, Mobile crowdsensing",

author = "Gendy, {Maggie E.} and Ahmad Al-Kabbany and Badran, {Ehab F.}",

note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; IEEE Consumer Communications and Networking Conference 2019, CCNC 2019 ; Conference date: 11-01-2019 Through 14-01-2019",

year = "2019",

doi = "10.1109/CCNC.2019.8651693",

language = "English",

isbn = "9781538655542",

editor = "Alan Kaplan",

booktitle = "CCNC 2019: 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)",

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

address = "United States of America",

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Gendy, ME, Al-Kabbany, A & Badran, EF 2019, Maximizing clearance rate of reputation-aware auctions in mobile crowdsensing. in A Kaplan (ed.), CCNC 2019: 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC)., 8651693, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, IEEE Consumer Communications and Networking Conference 2019, Las Vegas, Nevada, United States of America, 11/01/19. https://doi.org/10.1109/CCNC.2019.8651693

Maximizing clearance rate of reputation-aware auctions in mobile crowdsensing. / Gendy, Maggie E.; Al-Kabbany, Ahmad; Badran, Ehab F.
CCNC 2019: 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC). ed. / Alan Kaplan. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2019. 8651693.

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

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AU - Badran, Ehab F.

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Y1 - 2019

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AB - This research is concerned with maximizing the clearance rate (CR) of reputation-aware (RA) auctions for assigning tasks in mobile crowdsensing (MCS) systems-CR refers to the percentage of items that are sold over the duration of the auction. Towards maximizing CR during task allocation, we propose two new bidding procedures. Through simulations under varying system parameters, we demonstrate the effectiveness of the suggested methods through consistent and considerable increases in the CR compared to the state-of-the-art.

KW - Auctions

KW - Descriptive bidding

KW - Internet of things

KW - Mobile crowdsensing

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Y2 - 11 January 2019 through 14 January 2019

ER -

Maximizing clearance rate of reputation-aware auctions in mobile crowdsensing

Abstract

Conference

Keywords

Access to Document

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