Data Collection and Wireless Communication in Internet of Things (IoT) Using Economic Analysis and Pricing Models: A Survey
Not on the map. Why?
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.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Aug 2016.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 2; 2022: 3; 2023: 3; 2024: 2; 2025: 2.
12 papers.
- 2022Fundamentals of Task-Agnostic Data Valuationcited by 19
- 2021Data Pricing in Machine Learning Pipelinescited by 17
- 2022An Overview of Privacy-enhancing Technologies in Biometric Recognitioncited by 17
- 2023From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlookscited by 16
- 2022Label driven Knowledge Distillation for Federated Learning with non-IID Datacited by 3
- 2024Disentangled Structural and Featural Representation for Task-Agnostic Graph Valuationcited by 2
- 2023Privacy-Aware Data Acquisition under Data Similarity in Regression Marketscited by 1
- 2025Bandwidth Reservation for Time-Critical Vehicular Applications: A Multi-Operator Environmentcited by 1
- 2021Cloud computing as a platform for monetizing data services: A two-sided game business modelcited by 0
- 2023Intelligent Communication Planning for Constrained Environmental IoT Sensing with Reinforcement Learningcited by 0
- 2024Fair Distributed Cooperative Bandit Learning on Networks for Intelligent Internet of Things Systems (Technical Report)cited by 0
- 2025Large Language Model-Empowered Decision Transformer for UAV-Enabled Data Collectioncited by 0
- 2025Large Language Model-Empowered Decision Transformer for UAV-Enabled Data Collection17 Sep 2025
- 2025Bandwidth Reservation for Time-Critical Vehicular Applications: A Multi-Operator Environment22 Mar 2025
- 2024Disentangled Structural and Featural Representation for Task-Agnostic Graph Valuation22 Aug 2024
- 2024Fair Distributed Cooperative Bandit Learning on Networks for Intelligent Internet of Things Systems (Technical Report)18 Mar 2024
- 2023Privacy-Aware Data Acquisition under Data Similarity in Regression Markets5 Dec 2023
- 2023From Generative AI to Generative Internet of Things: Fundamentals, Framework, and Outlooks27 Oct 2023
- 2023Intelligent Communication Planning for Constrained Environmental IoT Sensing with Reinforcement Learning19 Aug 2023
- 2022Label driven Knowledge Distillation for Federated Learning with non-IID Data29 Sep 2022
- 2022Fundamentals of Task-Agnostic Data Valuation25 Aug 2022
- 2022An Overview of Privacy-enhancing Technologies in Biometric Recognition21 Jun 2022
- 2021Data Pricing in Machine Learning Pipelines18 Aug 2021
- 2021Cloud computing as a platform for monetizing data services: A two-sided game business model26 Apr 2021