A Novel Methodology for designing Policies in Mobile Crowdsensing Systems

Keyphrases

• Incentive Mechanism 100%
• Novel Methodology 100%
• Homophily 100%
• Mobile Crowdsensing System 100%
• User Behavior 66%
• Social Dilemma 66%
• Evolutionary Dynamics 66%
• Reputation Score 66%
• Social Networks 33%
• Proposed Methodology 33%
• Game Analysis 33%
• Systems-based 33%
• Multiplex Networks 33%
• Multiplex 33%
• Decision Support System 33%
• Sensing System 33%
• Network Structure 33%
• Dynamic Interaction 33%
• Rethink 33%
• Human Cooperation 33%
• User Contribution 33%
• Score-based 33%
• Quantifying Impact 33%
• Multiscale Characterization 33%
• Sensing Framework 33%
• User Reputation 33%
• Nash Equilibrium Point 33%
• Vehicular Traffic Monitoring 33%
• Sensing Behavior 33%
• Mobile Crowdsensing 33%
• Contribution Mechanism 33%
• Social Sensing 33%
• Spatiotemporal Distribution 33%
• Social Layer 33%
• Crowdsensing Applications 33%
• Waze 33%
• Network Heterogeneity 33%
• Social Sensors 33%
• Interaction Frequency 33%
• Novel Incentives 33%
• User Incentives 33%
• People-centric Sensing 33%
• Statistical Measures 33%
• Dilemma Structures 33%
• Human-related Factors 33%
• Disbursement 33%
• Mathematical Framework 33%

Computer Science

• Incentive Mechanism 100%
• User Behavior 66%
• Social Dilemma 66%
• Evolutionary Dynamics 66%
• Reputation Score 66%
• Experimental Result 33%
• Nash Equilibrium 33%
• Equilibrium Point 33%
• Research Direction 33%
• Dynamic Interaction 33%
• Related Factor 33%
• Network Structures 33%
• Traffic Monitoring 33%
• Vehicular Traffic 33%
• Human Cooperation 33%
• User Reputation 33%
• Social Network 33%