摘要：With the rapid development and growing popularity of Internet of Things (IoT), edge-assisted crowdsensing has emerged as a new mode of data collection and data processing. In an edge-assisted crowdsensing system, a reasonable data task allocation and pricing mechanism is urgently required to promote the active participation of each part of the system. However, existing mechanisms either did not consider the impact of data quality on participant profits or ignored some parts of the whole system. We therefore propose a novel task allocation and pricing mechanism based on the Stackelberg game model, considering all four parties (data requesters, crowdsensing platform, edge servers and IoT sensors) in an edge-assisted crowdsensing system. Specifically, we decompose the problem into three game sub-problems, and design our mechanism using KKT conditional approaches, with the aim of maximising the benefits of each party in the crowdsensing system. We demonstrate mathematically that the Stackelberg equilibrium can be achieved in all three games, and validate its performance through simulation experiments.

关键字：Edge-assisted crowdsensing; Stackelberg game; Task allocation; Pricing mechanism

ISSN号：1022-0038

卷、期、页：网络发表

影响因子：0.000000

期刊分区（SCI为中科院分区）：四区

收录情况：SCI（科学引文索引印刷版）,EI（工程索引）,SCIE（科学引文索引网络版）

发表期刊名称：WIRELESS NETWORKS

参与作者：赵卓峰

通讯作者：高煜洲,马博闻,冷亚静

第一作者：黄霁崴

论文类型：期刊论文

论文概要：高煜洲,马博闻,冷亚静,赵卓峰,黄霁崴，A task allocation and pricing mechanism based on Stackelberg game for edge-assisted crowdsensing，WIRELESS NETWORKS，，网络发表

论文题目：A task allocation and pricing mechanism based on Stackelberg game for edge-assisted crowdsensing