Results 231 to 240 of about 5,841 (261)

Group Task Recommendation in Mobile Crowdsensing: An Attention-Based Neural Collaborative Approach

IEEE Transactions on Mobile Computing
Collaborative tasks often require the cooperation of multiple individuals to be completed in mobile crowdsensing (MCS). However, previous task recommendations predominantly focused on individuals rather than groups, making them less effective for ...
Kaimin Wei, Guozi Qi, Zhetao Li, Song Guo, Jinpeng Chen   +4 more
semanticscholar   +1 more source

Lightweight and Privacy-Preserving Dual Incentives for Mobile Crowdsensing

IEEE Transactions on Cloud Computing
Incentive plays an important role in mobile crowdsensing (MCS), as it impels mobile users to participate in sensing tasks and provide high-quality sensing data.
Lin Wan, Zhiquan Liu, Yong Ma, Yudan Cheng, Yongdong Wu, Runchuan Li, Jianfeng Ma   +6 more
semanticscholar   +1 more source

Hybrid User-Based Task Assignment for Mobile Crowdsensing: Problem and Algorithm

IEEE Internet of Things Journal
With the rapid growth of Internet of Things and proliferation of handheld smart devices, mobile crowdsensing has been regarded as an effective sensing paradigm due to its high scalability, low cost, and wide coverage.
Kun Liu, Shuo Peng, Wei Gong, Baoxian Zhang, Cheng Li   +4 more
semanticscholar   +1 more source

Cooperative Computing for Mobile Crowdsensing: Design and Optimization

IEEE Transactions on Mobile Computing
With the increasing number of mobile devices, mobile crowdsensing (MCS) has garnered significant attention in research. However, computing infrastructures such as edge/cloud nodes, which are necessary for processing sensor data, are not always readily ...
Xin Xie, Tong Bai, Weiwei Guo, Zhipeng Wang, A. Nallanathan   +4 more
semanticscholar   +1 more source

Fairness-Aware Two-Stage Hybrid Sensing Method in Vehicular Crowdsensing

IEEE Transactions on Mobile Computing
By utilizing on-board sensors and computing resources in intelligent vehicles, vehicular crowdsensing can collect a series of sensing data. Typically, sensing vehicles can be divided into opportunistic vehicles with fixed trajectories and participatory ...
Zhenning Wang, Yue Cao, Huan Zhou, Libing Wu, Wei Wang, Geyong Min   +5 more
semanticscholar   +1 more source

Mobile Crowdsensing

SSRN Electronic Journal, 2014
Michelle Andrews, Xueming Luo, Zheng Fang, Anindya Ghose   +3 more
openaire   +1 more source

A Multi-Leader Multi-Follower Game-Based Analysis for Incentive Mechanisms in Socially-Aware Mobile Crowdsensing

IEEE Transactions on Wireless Communications, 2021
Jiangtian Nie, Jun Luo, Zehui Xiong
exaly  

Mobile Crowdsensing

2016
Cristian Borcea, Manoop Talasila, Reza Curtmola   +2 more
openaire   +1 more source

CrowdBLPS: A Blockchain-Based Location-Privacy-Preserving Mobile Crowdsensing System

IEEE Transactions on Industrial Informatics, 2020
Shihong Zou, Jinwen Xi, Honggang Wang
exaly  

Deep Reinforcement Learning for Partially Observable Data Poisoning Attack in Crowdsensing Systems

IEEE Internet of Things Journal, 2020
Mohan Li, Yanbin Sun, Hui Lu
exaly