成果信息
Heterogeneous incentive mechanism for time-sensitive and location-dependent crowdsensing networks with random arrivals
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在榜期数::ESI高被引论文(2018年第5期);
文献类型:期刊论文
标题:Heterogeneous incentive mechanism for time-sensitive and location-dependent crowdsensing networks with random arrivals
作者:Wang, Zhibo[1];Tan, Ran[2];Hu, Jiahui[2];Zhao, Jing[2];Wang, Qian[3];Xia, Feng[4];Niu, Xiaoguang[2]
机构:
[1]Wuhan Univ, Sch Natl Cybersecur, Sch Comp, Wuhan, Hubei, Peoples R China.;NJUPT, Jiangsu Key Lab Big Data Secur & Intelligent Proc, Nanjing, Jiangsu, Peoples R China.;
[2]Wuhan Univ, Sch Natl Cybersecur, Sch Comp, Wuhan, Hubei, Peoples R China.;
[3]Wuhan Univ, Sch Natl Cybersecur, Sch Comp, Wuhan, Hubei, Peoples R China.;Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan, Hubei, Peoples R China.;
通讯作者:Wang, Q (reprint author), Wuhan Univ, Sch Natl Cybersecur, Sch Comp, Wuhan, Hubei, Peoples R China.; Wang, Q (reprint author), Wuhan Univ, Collaborat Innovat Ctr Geospatial Technol, Wuhan, Hubei, Peoples R China.
年:2018
期刊名称:COMPUTER NETWORKS影响因子和分区
来源信息:年:2018  卷:131  页码范围:96-109  
期刊信息:COMPUTER NETWORKS影响因子和分区  ISSN:1389-1286
卷:131
页码范围:96-109
增刊:正刊
学科:计算机科学
收录情况:SCIE(WOS:000424727300007)  EI(20180104599782)  
所属部门:软件学院
重要成果类型:ESI高被引
语言:外文
ISSN:1389-1286
发表时间:2018-02-11
全文链接:全文下载DOI百度学术
被引频次:5
人气指数:136
浏览次数:136
基金:National Natural Science Foundation of China [61502352, 61373167, U1636219]; National Basic Research Program of China [2014CB340600]; National High-tech Research and Development Program [2015AA016004, 2015AA016002]; Natural Science Foundation of Hubei Province [2017CFA007, 2017CFA047, 2017CFB503]; Natural Science Foundation of Jiangsu Province [BK20150383]; Fundamental Research Funds for the Central Universities [413000035]
关键词:Crowdsensing; Incentive; Time-sensitive; Location-dependent; Randomly arriving participants
摘要:With the rapid development and ubiquity of mobile devices, crowdsensing has become an effective technique by taking advantages of mobile users to collect massive sensing data. Many incentive mechanisms have been proposed to encourage mobile users to participate in crowdsensing tasks. However, most of them allocate homogeneous rewards to sensing tasks and assume a fixed set of participants, while inherent inequality among tasks and randomness of participants' arrival have been ignored for a long time, especially for time-sensitive and location-dependent crowdsensing systems. In this paper, we focus on time-sensitive and location-dependent crowdsensing systems with random arrivals, and propose a two level heterogeneous pricing mechanism to balance the participation of participants among tasks. In particular, the reward budget of each task is determined based on its relative popularity among tasks by considering the spatio-temporal inequality of tasks at the inter-task level, and the reward of a task to each participation dynamically changes as the demand of measurements changes at the intra-task level. Moreover, we prove that the task selection problem for randomly arriving participants with time budget is NP-hard, and further propose several efficiently greedy task selection algorithms to help each participant select tasks to maximize its total payoff. Experimental results show that the proposed heterogeneous incentive mechanism outperforms existing incentive mechanisms. (C) 2017 Elsevier B.V. All rights reserved.
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