Results 201 to 210 of about 12,378 (273)

Incentive Mechanisms for Crowdsensing

ACM Transactions on Sensor Networks, 2020
Crowdsensing is a popular method that leverages a crowd of sensor users to collect data. For many crowdsensing applications, the collected raw data need to be preprocessed before further analysis, and the preprocessing work is mainly done by the crowdsourcer.
Zhao Liu, Kenli Li, Xu Zhou, Ningbo Zhu, Keqin Li   +4 more
openaire   +1 more source

CALRA: Practical Conditional Anonymous and Leakage-Resilient Authentication Scheme for Vehicular Crowdsensing Communication

IEEE transactions on intelligent transportation systems (Print)
Vehicular crowdsensing (VCS) has aroused extensive attention because of its ability to provide comprehensive data services for intelligent transportation systems. Wherein, secure data transmission is a prerequisite for realizing the above benefits of VCS.
Jianru Xiao, Yilong Ren, Jiewei Du, Yanan Zhao, Saru Kumari, Mohammed J. F. Alenazi, Haiyang Yu   +6 more
semanticscholar   +1 more source

When Crowdsensing Meets Smart Cities: A Comprehensive Survey and New Perspectives

IEEE Communications Surveys and Tutorials
Crowdsensing has received widespread attention in recent years. It is extensively employed in smart cities and intelligent transportation systems. This paper comprehensively surveys the latest research advancements in crowdsensing for smart cities from a
Zhenning Wang, Yue Cao, Kai Jiang, Huan Zhou, Jiawen Kang, Zhuang Yuan, Daxin Tian, V. Leung   +7 more
semanticscholar   +1 more source

A Lightweight Privacy Preservation Scheme With Efficient Reputation Management for Mobile Crowdsensing in Vehicular Networks

IEEE Transactions on Dependable and Secure Computing, 2023
Mobile crowdsensing (MCS) refers to a group of mobile users utilizing their sensing devices to accomplish the same sensing task. However, in vehicular networks, how to evaluate the reliability of sensing vehicles and achieve lightweight privacy ...
Yudan Cheng, Jianfeng Ma, Zhiquan Liu, Yongdong Wu, Kaimin Wei, Caiqin Dong   +5 more
semanticscholar   +1 more source

Piggyback CrowdSensing (PCS)

Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems, 2013
Fueled by the widespread adoption of sensor-enabled smartphones, mobile crowdsourcing is an area of rapid innovation. Many crowd-powered sensor systems are now part of our daily life -- for example, providing highway congestion information. However, participation in these systems can easily expose users to a significant drain on already limited mobile ...
Nicholas D. Lane, Yohan Chon, Lin Zhou, Yongzhe Zhang, Fan Li, Dongwon Kim, Guanzhong Ding, Feng Zhao, Hojung Cha   +8 more
openaire   +1 more source

A New Data Completion Perspective on Sparse CrowdSensing: Spatiotemporal Evolutionary Inference Approach

IEEE Transactions on Mobile Computing
Mobile CrowdSensing (MCS) has emerged as a popular paradigm to engage mobile users in collaborative sensing tasks. However, its performance is hindered by its limited spatiotemporal range and the cost of data collection.
E. Wang, Zixuan Song, Mengni Wu, Wenbin Liu, Bo Yang, Yongjian Yang, Jie Wu   +6 more
semanticscholar   +1 more source

Privacy-Preserving User Recruitment With Sensing Quality Evaluation in Mobile Crowdsensing

IEEE Transactions on Dependable and Secure Computing
Recruiting users in mobile crowdsensing (MCS) can make the platform obtain high-quality data to provide better services. Although the privacy leakage during the process of user recruitment has received a lot of research attention, none of the existing ...
Jieying An, Yanbing Ren, Xinghua Li, Man Zhang, Bin Luo, Yinbin Miao, Ximeng Liu, R. Deng   +7 more
semanticscholar   +1 more source

Ensuring Threshold AoI for UAV-Assisted Mobile Crowdsensing by Multi-Agent Deep Reinforcement Learning With Transformer

IEEE/ACM Transactions on Networking
Unmanned aerial vehicle (UAV) crowdsensing (UCS) is an emerging data collection paradigm to provide reliable and high quality urban sensing services, with age-of-information (AoI) requirement to measure data freshness in real-time applications.
Hao Wang, C. Liu, Haoming Yang, Guoren Wang, K. Leung   +4 more
semanticscholar   +1 more source

AoI-Guaranteed Incentive Mechanism for Mobile Crowdsensing With Freshness Concerns

IEEE Transactions on Mobile Computing
With the explosive spread of smart mobile devices, Mobile CrowdSensing (MCS) has been becoming a promising paradigm, by which a platform can coordinate a group of workers to complete large-scale data collection tasks using their mobile devices.
Yin Xu, Mingjun Xiao, Yu Zhu, Jie Wu, Shenmin Zhang, Jinrui Zhou   +5 more
semanticscholar   +1 more source

An Ordered Submodularity-Based Budget-Feasible Mechanism for Opportunistic Mobile Crowdsensing Task Allocation and Pricing

IEEE Transactions on Mobile Computing
Mobile crowdsensing services are divided into two categories: opportunistic and participatory. In opportunistic mobile crowdsensing services, users do not need to specify the crowdsensing tasks to be completed.
Jixian Zhang, Yan Zhang, Hao Wu, Weidong Li   +3 more
semanticscholar   +1 more source