Federated learning in smart city sensing: Challenges and opportunities
Smart Cities sensing is an emerging paradigm to facilitate the transition into smart city
services. The advent of the Internet of Things (IoT) and the widespread use of mobile …
services. The advent of the Internet of Things (IoT) and the widespread use of mobile …
A survey on mobile crowdsensing systems: Challenges, solutions, and opportunities
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 …
become an appealing paradigm for urban sensing. For data collection, MCS systems rely on …
Hybrid blockchain-based resource trading system for federated learning in edge computing
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 …
federated learning (FL) ensures the privacy of the data generated by the massive Internet-of …
A stackelberg game approach toward socially-aware incentive mechanisms for mobile crowdsensing
Mobile crowdsensing has shown great potential in addressing large-scale data sensing
problems by allocating sensing tasks to pervasive mobile users. The mobile users will …
problems by allocating sensing tasks to pervasive mobile users. The mobile users will …
Enhanced-AODV: A robust three phase priority-based traffic load balancing scheme for internet of things
One of the operational challenges in the Internet of Things (IoT) is load balancing, which is
the focus of interest of this article. We propose a three-phase enhanced ad hoc on-demand …
the focus of interest of this article. We propose a three-phase enhanced ad hoc on-demand …
An AI-enabled three-party game framework for guaranteed data privacy in mobile edge crowdsensing of IoT
J Xiong, M Zhao, MZA Bhuiyan… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The mobile crowdsensing (MCS) technology with a large number of Internet of Things (IoT)
devices provides an economic and efficient solution to participation in coordinated large …
devices provides an economic and efficient solution to participation in coordinated large …
Mobile crowd-sensing applications: Data redundancies, challenges, and solutions
TN Nguyen, S Zeadally - ACM Transactions on Internet Technology …, 2021 - dl.acm.org
Conventional data collection methods that use Wireless Sensor Networks (WSNs) suffer
from disadvantages such as deployment location limitation, geographical distance, as well …
from disadvantages such as deployment location limitation, geographical distance, as well …
CMAB-based reverse auction for unknown worker recruitment in mobile crowdsensing
M Xiao, B An, J Wang, G Gao… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Mobile CrowdSensing (MCS), through which a requester can coordinate a crowd of workers
to accomplish some data collection tasks, has been recognized as a promising paradigm for …
to accomplish some data collection tasks, has been recognized as a promising paradigm for …
Use of mobile crowdsensing in disaster management: A systematic review, challenges, and open issues
D Cicek, B Kantarci - Sensors, 2023 - mdpi.com
With the increasing efforts to utilize information and communication technologies (ICT) in
disaster management, the massive amount of heterogeneous data that is generated through …
disaster management, the massive amount of heterogeneous data that is generated through …
ilocus: Incentivizing vehicle mobility to optimize sensing distribution in crowd sensing
Vehicular crowd sensing systems are designed to achieve large spatio-temporal sensing
coverage with low-cost in deployment and maintenance. For example, taxi platforms can be …
coverage with low-cost in deployment and maintenance. For example, taxi platforms can be …