# Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey

arXiv: https://arxiv.org/abs/1608.03475 · HTML: https://mlsanity.com/paper/1608.03475/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Aug 2016.

## Built on by (most cited first, 12 of 12)

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- [Disentangled Structural and Featural Representation for Task-Agnostic Graph Valuation](https://mlsanity.com/paper/2408.12659/) (2024)
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- [Bandwidth Reservation for Time-Critical Vehicular Applications: A Multi-Operator Environment](https://mlsanity.com/paper/2503.17756/) (2025)
- [Cloud computing as a platform for monetizing data services: A two-sided game business model](https://mlsanity.com/paper/2104.12762/) (2021)
- [Intelligent Communication Planning for Constrained Environmental IoT Sensing with Reinforcement Learning](https://mlsanity.com/paper/2308.10124/) (2023)
- [Fair Distributed Cooperative Bandit Learning on Networks for Intelligent Internet of Things Systems (Technical Report)](https://mlsanity.com/paper/2403.11603/) (2024)
- [Large Language Model-Empowered Decision Transformer for UAV-Enabled Data Collection](https://mlsanity.com/paper/2509.13934/) (2025)

## Abstract (arXiv)

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.