Eliciting truthful measurements from a community of sensors
Year: 2012
Type: conference-paper
Abstract: As the Internet of Things grows to large scale, its components will increasingly be controlled by self-interested agents. For example, sensor networks will evolve to community sensing where a community of agents combine their data into a single coherent structure. As there is no central quality control, agents need to be incentivized to provide accurate measurements. We propose game-theoretic mechanisms that provide such incentives and show their application on the example of community sensing for monitoring air pollution. These mechanisms can be applied to most sensing scenarios and allow the Internet of Things to grow to much larger scale than currently exists.
Authors: Boi Faltings, Jason Jingshi Li, Radu Jurca
Language: English
Topic: Game Theory and Applications
Field: Decision Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2076435282