  Several smart city services rely on users contribution, e.g., data, which can
be costly for the users in terms of privacy. High costs lead to reduced user
participation, which undermine the success of smart city technologies. This
work develops a scenario-independent design principle, based on public good
theory, for resource management in smart city applications, where provision of
a service depends on contributors and free-riders, which benefit from the
service without contributing own resources. Following this design principle,
different classes of algorithms for resource management are evaluated with
respect to human-centered measures, i.e., privacy, fairness and social welfare.
Trade-offs that characterize algorithms are discussed across two smart city
application scenarios. These results might help Smart City application
designers to choose a suitable algorithm given a scenario-specific set of
requirements, and users to choose a service based on an algorithm that matches
their preferences.
