  This paper provides a state-of-the-art literature review on economic analysis
and pricing models for data collection and wireless communication in Internet
of Things (IoT). Wireless Sensor Networks (WSNs) are the main component of IoT
which collect data from the environment and transmit the data to the sink
nodes. For long service time and low maintenance cost, WSNs require adaptive
and robust designs to address many issues, e.g., data collection, topology
formation, packet forwarding, resource and power optimization, coverage
optimization, efficient task allocation, and security. For these issues,
sensors have to make optimal decisions from current capabilities and available
strategies to achieve desirable goals. This paper reviews numerous applications
of the economic and pricing models, known as intelligent rational
decision-making methods, to develop adaptive algorithms and protocols for WSNs.
Besides, we survey a variety of pricing strategies in providing incentives for
phone users in crowdsensing applications to contribute their sensing data.
Furthermore, we consider the use of some pricing models in Machine-to-Machine
(M2M) communication. Finally, we highlight some important open research issues
as well as future research directions of applying economic and pricing models
to IoT.
