A survey on mobile crowdsensing systems: Challenges, solutions, and opportunities

A Capponi, C Fiandrino, B Kantarci… - … surveys & tutorials, 2019‏ - ieeexplore.ieee.org
Mobile crowdsensing (MCS) has gained significant attention in recent years and has
become an appealing paradigm for urban sensing. For data collection, MCS systems rely on …

Internet of Things (IoT), mobile cloud, cloudlet, mobile IoT, IoT cloud, fog, mobile edge, and edge emerging computing paradigms: Disambiguation and research …

H Elazhary - Journal of network and computer applications, 2019‏ - Elsevier
Currently, we are experiencing a technological shift, which is expected to change the way
we program and interact with the world. Cloud computing and mobile computing are two …

Blockchain-enabled data collection and sharing for industrial IoT with deep reinforcement learning

CH Liu, Q Lin, S Wen - IEEE Transactions on Industrial …, 2018‏ - ieeexplore.ieee.org
With the rapid development of smart mobile terminals (MTs), various industrial Internet of
things (IIoT) applications can fully leverage them to collect and share data for providing …

Incentive mechanism for horizontal federated learning based on reputation and reverse auction

J Zhang, Y Wu, R Pan - Proceedings of the Web Conference 2021, 2021‏ - dl.acm.org
Current research on federated learning mainly focuses on joint optimization, improving
efficiency and effectiveness, and protecting privacy. However, there are relatively few …

Dynamic digital twin and distributed incentives for resource allocation in aerial-assisted internet of vehicles

W Sun, P Wang, N Xu, G Wang… - IEEE Internet of Things …, 2021‏ - ieeexplore.ieee.org
Internet of Vehicles (IoV), when empowered by aerial communications, provides vehicles
with seamless connections and proximate computing services. The unpredictable network …

When mobile crowd sensing meets UAV: Energy-efficient task assignment and route planning

Z Zhou, J Feng, B Gu, B Ai, S Mumtaz… - IEEE Transactions …, 2018‏ - ieeexplore.ieee.org
With the increasing popularity of unmanned aerial vehicles (UAVs), it is foreseen that they
will play an important role in broadening the horizon of mobile crowd sensing (MCS) …

Fmore: An incentive scheme of multi-dimensional auction for federated learning in mec

R Zeng, S Zhang, J Wang, X Chu - 2020 IEEE 40th …, 2020‏ - ieeexplore.ieee.org
Promising federated learning coupled with Mobile Edge Computing (MEC) is considered as
one of the most promising solutions to the AI-driven service provision. Plenty of studies focus …

Hybrid blockchain-based resource trading system for federated learning in edge computing

S Fan, H Zhang, Y Zeng, W Cai - IEEE Internet of Things …, 2020‏ - ieeexplore.ieee.org
By training a machine learning algorithm across multiple decentralized edge nodes,
federated learning (FL) ensures the privacy of the data generated by the massive Internet-of …

Auction mechanisms in cloud/fog computing resource allocation for public blockchain networks

Y Jiao, P Wang, D Niyato… - IEEE Transactions on …, 2019‏ - ieeexplore.ieee.org
As an emerging decentralized secure data management platform, blockchain has gained
much popularity recently. To maintain a canonical state of blockchain data record, proof-of …

Incentivizing differentially private federated learning: A multidimensional contract approach

M Wu, D Ye, J Ding, Y Guo, R Yu… - IEEE Internet of Things …, 2021‏ - ieeexplore.ieee.org
Federated learning is a promising tool in the Internet-of-Things (IoT) domain for training a
machine learning model in a decentralized manner. Specifically, the data owners (eg, IoT …