Results 151 to 160 of about 5,365 (199)

When Mobile Crowdsensing Meets Privacy

IEEE Communications Magazine, 2019
Mobile crowdsensing (MCS) has now become an effective paradigm to collect massive data for various sensing applications. However, the interactions between mobile users and the platform, and the data release to third parties, pose severe challenges of privacy leakage for MCS systems, such as the leakage of users' identities and locations.
Zhibo Wang 0001, Xiaoyi Pang, Jiahui Hu, Wenxin Liu, Qian Wang 0002, Yanjun Li 0004, Honglong Chen   +6 more
openaire   +1 more source

Sparse mobile crowdsensing: challenges and opportunities

IEEE Communications Magazine, 2016
Sensing cost and data quality are two primary concerns in mobile crowdsensing. In this article, we propose a new crowdsensing paradigm, sparse mobile crowdsensing, which leverages the spatial and temporal correlation among the data sensed in different sub-areas to significantly reduce the required number of sensing tasks allocated, thus lowering ...
Leye Wang, Daqing Zhang 0001, Yasha Wang, Chao Chen 0004, Xiao Han 0001, Abdallah M'hamed   +5 more
openaire   +1 more source

QoS Assessment of Mobile Crowdsensing Services

Journal of Grid Computing, 2015
© 2015, Springer Science+Business Media Dordrecht. The wide spreading of smart devices drives to develop distributed applications of increasing complexity, attracting efforts from both research and business communities. Recently, a new volunteer contribution paradigm based on participatory and opportunistic sensing is affirming in the Internet of ...
DISTEFANO, SALVATORE, LONGO, FRANCESCO, SCARPA, Marco Lucio   +2 more
openaire   +3 more sources

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 0002, Yunhao Liu 0001, Jianqiang Li 0001, Zhong Ming 0001   +4 more
openaire   +1 more source

Data Quality Maximization for Mobile Crowdsensing

NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium, 2020
With the increase of smart devices, mobile crowdsensing, in which a crowdsensing Internet of Things (IoT) platform collects data from smart devices (such as smartphone) users, has become a popular paradigm. Various incentive mechanisms are widely employed for the IoT platform to incentivize smart device users to provide sensing data.
Cheng Zhang 0007, Noriaki Kamiyama
openaire   +1 more source

Investigating mobile crowdsensing application performance

Proceedings of the third ACM international symposium on Design and analysis of intelligent vehicular networks and applications, 2013
Mobile Crowdsensing (MCS) is an emerging distributed paradigm lying at the intersection between the Internet of Things and the volunteer/crowd-based approach. MCS applications are usually deployed on contributing nodes such as smart devices and mobiles, equipped by sensing resources that sample the physical environment and provide the sensed data, once
DISTEFANO, SALVATORE, LONGO, FRANCESCO, SCARPA, Marco Lucio   +2 more
openaire   +1 more source

Economics of Peer-to-Peer Mobile Crowdsensing

2015 IEEE Global Communications Conference (GLOBECOM), 2014
Mobile crowdsensing is a new sensing paradigm relying on computation and storage capabilities of mobile devices. However, traditional server-client mobile crowdsensing models suffer from a high operational cost on the server, and hence a poor scalability.
Changkun Jiang, Lin Gao 0001, Lingjie Duan, Jianwei Huang 0001   +3 more
openaire   +1 more source

Incentive Mechanisms for Discretized Mobile Crowdsensings

IEEE Transactions on Wireless Communications, 2016
In crowdsensing to mobile phones, each user needs incentives to participate. Mobile devices with sensing capabilities have enabled a new paradigm of mobile crowdsensing with a broad range of applications. A major challenge in achieving stable crowdsensing on a large scale is the incentive issue.
Shiyu Ji, Tingting Chen
openaire   +1 more source

Exploiting Data Reuse in Mobile Crowdsensing

2016 IEEE Global Communications Conference (GLOBECOM), 2016
Mobile crowdsensing emerges as a promising sensing paradigm through leveraging the diverse embedded sensors in massive mobile devices. A key objective in mobile crowdsensing is to efficiently schedule mobile device users to perform multiple sensing tasks.
Changkun Jiang, Lin Gao 0001, Lingjie Duan, Jianwei Huang 0001   +3 more
openaire   +1 more source

Using On-the-Move Mining for Mobile Crowdsensing

2012 IEEE 13th International Conference on Mobile Data Management, 2012
In this paper, we propose and develop a platform to support data collection for mobile crowdsensing from mobile device sensors that is under-pinned by real-time mobile data stream mining. We experimentally show that mobile data mining provides an efficient and scalable approach for data collection for mobile crowdsensing.
Wanita Sherchan, Prem Prakash Jayaraman, Shonali Krishnaswamy, Arkady B. Zaslavsky, Seng Wai Loke, Abhijat Sinha   +5 more
openaire   +1 more source