Improving the quality of service indices of task allocation in mobile crowd sensing with fuzzy-based inverse stackelberg game theory
Author:
Publisher
Elsevier BV
Subject
Artificial Intelligence,Computer Science Applications,Computer Vision and Pattern Recognition,Signal Processing,Computer Science (miscellaneous)
Reference19 articles.
1. Towards crowdsourcing Internet of Things (Crowd-IoT): Architectures, security and applications;Ang;Future Internet,2022
2. Intelligen tCrowd: Mobile crowdsensing via multi-agent reinforcement learning;Chen;IEEE Transactions on Emerging Topics in Computational Intelligence,2020
3. Delay-sensitive energy-efficient uav crowdsensing by deep reinforcement learning;Dai;IEEE Transactions on Mobile Computing,2021
4. A two-tier bipartite graph task allocation approach based on fuzzy clustering in cloud–fog environment;Gad-Elrab;Future Generation Computer Systems,2020
5. A heuristic model for tasks scheduling in heterogeneous distributed real time system under fuzzy environment;Kumar;International Journal of Computers and Applications,2015
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