The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Dengan populariti peranti pintar, crowdsensing mudah alih, di mana platform crowdsensing mengumpulkan data berguna daripada pengguna peranti pintar, contohnya, telefon pintar, telah menjadi paradigma yang lazim. Pelbagai mekanisme insentif telah digunakan secara meluas untuk platform penderiaan ramai bagi memberi insentif kepada pengguna peranti pintar untuk menawarkan data penderiaan. Kerja-kerja sedia ada telah menumpukan pada memberi ganjaran kepada pengguna peranti pintar untuk usaha jangka pendek mereka untuk menyediakan data tanpa mengambil kira faktor jangka panjang pengguna peranti pintar dan kualiti data. Kerja kami sebelum ini telah mempertimbangkan kualiti data pengguna peranti pintar dengan menggabungkan reputasi jangka panjang pengguna peranti pintar. Walau bagaimanapun, kerja kami sebelum ini hanya menganggap masalah memaksimumkan kualiti dengan kekangan belanjawan di satu lokasi. Dalam kertas ini, beberapa lokasi dipertimbangkan. Permainan Stackelberg digunakan untuk menyelesaikan masalah pengoptimuman dua peringkat. Pada peringkat pertama, platform crowdsensing memperuntukkan belanjawan ke lokasi yang berbeza dan menetapkan harga sebagai insentif untuk pengguna memaksimumkan jumlah kualiti data. Pada peringkat kedua, pengguna berusaha untuk menyediakan data untuk memaksimumkan kegunaannya. Simulasi berangka yang meluas dijalankan untuk menilai algoritma yang dicadangkan.
Cheng ZHANG
Ibaraki University
Noriaki KAMIYAMA
Ritsumeikan University
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Salinan
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
Salinan
@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},}
Salinan
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 -