IEICE TRANSACTIONS on Communications
Budget Allocation for Incentivizing Mobile Users for Crowdsensing Platform
Summary :
With the popularity of smart devices, mobile crowdsensing, in which the crowdsensing platform gathers useful data from users of smart devices, e.g., smartphones, has become a prevalent paradigm. Various incentive mechanisms have been extensively adopted for the crowdsensing platform to incentivize users of smart devices to offer sensing data. Existing works have concentrated on rewarding smart-device users for their short term effort to provide data without considering the long-term factors of smart-device users and the quality of data. Our previous work has considered the quality of data of smart-device users by incorporating the long-term reputation of smart-device users. However, our previous work only considered a quality maximization problem with budget constraints on one location. In this paper, multiple locations are considered. Stackelberg game is utilized to solve a two-stage optimization problem. In the first stage, the crowdsensing platform allocates the budget to different locations and sets price as incentives for users to maximize the total data quality. In the second stage, the users make efforts to provide data to maximize its utility. Extensive numerical simulations are conducted to evaluate proposed algorithm.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E105-B No.11 pp.1342-1352
- Publication Date
- 2022/11/01
- Publicized
- 2022/05/27
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2021TMP0014
- Type of Manuscript
- Special Section PAPER (Special Section on Towards Management for Future Communications and Services in Conjunction with Main Topics of APNOMS2021)
- Category
Authors
Cheng ZHANG
Ibaraki University
Noriaki KAMIYAMA
Ritsumeikan University
Keyword
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Cheng ZHANG, Noriaki KAMIYAMA, "Budget Allocation for Incentivizing Mobile Users for Crowdsensing Platform" in IEICE TRANSACTIONS on Communications,
vol. E105-B, no. 11, pp. 1342-1352, November 2022, doi: 10.1587/transcom.2021TMP0014.
Abstract: With the popularity of smart devices, mobile crowdsensing, in which the crowdsensing platform gathers useful data from users of smart devices, e.g., smartphones, has become a prevalent paradigm. Various incentive mechanisms have been extensively adopted for the crowdsensing platform to incentivize users of smart devices to offer sensing data. Existing works have concentrated on rewarding smart-device users for their short term effort to provide data without considering the long-term factors of smart-device users and the quality of data. Our previous work has considered the quality of data of smart-device users by incorporating the long-term reputation of smart-device users. However, our previous work only considered a quality maximization problem with budget constraints on one location. In this paper, multiple locations are considered. Stackelberg game is utilized to solve a two-stage optimization problem. In the first stage, the crowdsensing platform allocates the budget to different locations and sets price as incentives for users to maximize the total data quality. In the second stage, the users make efforts to provide data to maximize its utility. Extensive numerical simulations are conducted to evaluate proposed algorithm.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2021TMP0014/_p
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@ARTICLE{e105-b_11_1342,
author={Cheng ZHANG, Noriaki KAMIYAMA, },
journal={IEICE TRANSACTIONS on Communications},
title={Budget Allocation for Incentivizing Mobile Users for Crowdsensing Platform},
year={2022},
volume={E105-B},
number={11},
pages={1342-1352},
abstract={With the popularity of smart devices, mobile crowdsensing, in which the crowdsensing platform gathers useful data from users of smart devices, e.g., smartphones, has become a prevalent paradigm. Various incentive mechanisms have been extensively adopted for the crowdsensing platform to incentivize users of smart devices to offer sensing data. Existing works have concentrated on rewarding smart-device users for their short term effort to provide data without considering the long-term factors of smart-device users and the quality of data. Our previous work has considered the quality of data of smart-device users by incorporating the long-term reputation of smart-device users. However, our previous work only considered a quality maximization problem with budget constraints on one location. In this paper, multiple locations are considered. Stackelberg game is utilized to solve a two-stage optimization problem. In the first stage, the crowdsensing platform allocates the budget to different locations and sets price as incentives for users to maximize the total data quality. In the second stage, the users make efforts to provide data to maximize its utility. Extensive numerical simulations are conducted to evaluate proposed algorithm.},
keywords={},
doi={10.1587/transcom.2021TMP0014},
ISSN={1745-1345},
month={November},}
Copy
TY - JOUR
TI - Budget Allocation for Incentivizing Mobile Users for Crowdsensing Platform
T2 - IEICE TRANSACTIONS on Communications
SP - 1342
EP - 1352
AU - Cheng ZHANG
AU - Noriaki KAMIYAMA
PY - 2022
DO - 10.1587/transcom.2021TMP0014
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E105-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 2022
AB - With the popularity of smart devices, mobile crowdsensing, in which the crowdsensing platform gathers useful data from users of smart devices, e.g., smartphones, has become a prevalent paradigm. Various incentive mechanisms have been extensively adopted for the crowdsensing platform to incentivize users of smart devices to offer sensing data. Existing works have concentrated on rewarding smart-device users for their short term effort to provide data without considering the long-term factors of smart-device users and the quality of data. Our previous work has considered the quality of data of smart-device users by incorporating the long-term reputation of smart-device users. However, our previous work only considered a quality maximization problem with budget constraints on one location. In this paper, multiple locations are considered. Stackelberg game is utilized to solve a two-stage optimization problem. In the first stage, the crowdsensing platform allocates the budget to different locations and sets price as incentives for users to maximize the total data quality. In the second stage, the users make efforts to provide data to maximize its utility. Extensive numerical simulations are conducted to evaluate proposed algorithm.
ER -
English
