Results 211 to 220 of about 1,414,604 (271)

Fog-Enabled Privacy-Preserving Multi-Task Data Aggregation for Mobile Crowdsensing

IEEE Transactions on Dependable and Secure Computing
Privacy-preserving data aggregation in mobile crowdsensing (MCS) focuses on mining information from massive sensing data while protecting users’ privacy.
Xingfu Yan, Wing W. Y. Ng, Bowen Zhao, Yuxian Liu, Ying Gao, Xiumin Wang   +5 more
semanticscholar   +1 more source

Jump-start crowdsensing: A three-layer incentive framework for mobile crowdsensing

2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS), 2017
In the past decade, with the rapid development of wireless communication and sensor technology, ubiquitous smartphones equipped with increasingly rich sensors have more powerful computing and sensing abilities. Thus, mobile crowdsensing has received extensive attentions from both industry and academia.
null Yatong Chen, null Huangxun Chen, null Shuo Yang, null Xiaofeng Gao, null Fan Wu   +4 more
openaire   +1 more source

QoI-Aware Mobile Crowdsensing for Metaverse by Multi-Agent Deep Reinforcement Learning

IEEE Journal on Selected Areas in Communications
Metaverse is expected to provide mobile users with emerging applications both in regular situation like intelligent transportation services and in emergencies like wireless search and disaster response.
Yuxiao Ye, Hao Wang, Chi Harold Liu, Zipeng Dai, Guozheng Li, Guoren Wang, Jian Tang   +6 more
semanticscholar   +1 more source

Online Incentive Mechanisms for Socially-Aware and Socially-Unaware Mobile Crowdsensing

IEEE Transactions on Mobile Computing
Mobile crowdsensing (MCS) has been a promising paradigm for gathering sensing data from surrounding environment by leveraging smart devices carried by mobile users and also their subjective initiatives.
Guo Ji, Baoxian Zhang, Guo Zhang, Cheng Li   +3 more
semanticscholar   +1 more source

Research Progress on Incentive Mechanisms in Mobile Crowdsensing

IEEE Internet of Things Journal
With the continuous improvement of the sensing, transmission, storage, and computing capabilities of mobile devices, they have become important tools for perceiving the physical environment and social phenomena.
Enhui Wu, Zhenlong Peng
semanticscholar   +1 more source

Toward Efficient Mechanisms for Mobile Crowdsensing

IEEE Transactions on Vehicular Technology, 2017
Mobile crowdsensing systems aim to provide various novel applications by employing pervasive smartphones. A key factor to enable such systems is substantial participation of normal smartphone users, which requires effective incentive mechanisms. In this paper, we investigate incentive mechanisms for online scenarios, where users arrive and interact ...
Xinglin Zhang, Zheng Yang, Yunhao Liu, Jianqiang Li, Zhong Ming   +4 more
openaire   +1 more source

Multitask Data Collection With Limited Budget in Edge-Assisted Mobile Crowdsensing

IEEE Internet of Things Journal
Due to the swift advancement of edge computing and mobile crowdsensing (MCS), edge-assisted MCS (EAMCS) has emerged as a promising paradigm, leveraging sensor-embedded mobile devices for the collection and sharing of environmental data.
Xiaolong Liu, Honglong Chen, Yuping Liu, Wentao Wei, Huansheng Xue, Feng Xia   +5 more
semanticscholar   +1 more source

Multiagent Deep Reinforcement Learning Based Incentive Mechanism for Mobile Crowdsensing in Intelligent Transportation Systems

IEEE Systems Journal
Mobile crowdsensing in intelligent transportation systems is a new data acquisition mode that utilizes vehicles to sense a changing traffic environment, where incentive mechanisms play a vital role in motivating vehicles to participate.
Mengge Li, Miao Ma, Liang Wang, Zhao Pei, Jie Ren, Bo Yang   +5 more
semanticscholar   +1 more source

Age of Information Optimization for Privacy-Preserving Mobile Crowdsensing

IEEE Transactions on Emerging Topics in Computing
Mobile crowdsensing (MCS)-enabled data collection can be implemented in a cost-effective, scalable, and flexible manner. However, joint sensing data freshness and security assurance have not been fully investigated in the current research.
Yaoqi Yang, Bangning Zhang, D. Guo, Renhui Xu, Chunhua Su, Weizheng Wang   +5 more
semanticscholar   +1 more source

Bi-Objective Incentive Mechanism for Mobile Crowdsensing With Budget/Cost Constraint

IEEE Transactions on Mobile Computing
In recent years, mobile crowdsensing (MCS) has been widely adopted as an efficient method for large-scale data collection. In MCS systems, insufficient participation and unstable data quality have become two crucial issues that prevent crowdsensing from ...
Yuanhang Zhou, Fei Tong, Shibo He
semanticscholar   +1 more source