Decentralized IoT Data Marketplaces: Enabling Peer-to-Peer Exchange with Edge Computing
Filippos Serepas, Ioannis Papias, Konstantinos Christakis, Nikos Dimitropoulos, Vangelis Marinakis · 2025
The rapid proliferation of Internet of Things (IoT) devices has led to an exponential increase in data generation, creating new opportunities for data-driven insights and economic models. Traditional data marketplaces rely on centralized intermediaries, imposing high infrastructure costs, limiting user control, and introducing inefficiencies in data exchange. This study proposes a decentralized data-sharing architecture that enables direct peer-to-peer interactions between data producers and consumers. By leveraging the computational capabilities of edge devices, the proposed approach shifts data formatting and preprocessing from the cloud to the device level, reducing latency and infrastructure costs. The architecture enhances interoperability by allowing IoT devices to dynamically adapt their data structures to consumer needs, eliminating the need for centralized standardization mechanisms. Furthermore, it introduces an economic framework that allows everyday users to monetize the data generated by their smart devices. Key challenges, including security, trust mechanisms, and scalability, are discussed, and potential solutions such as lightweight blockchain verification, adaptive network optimization, and federated learning for edge devices are proposed. The findings suggest that the proposed architecture can serve as an efficient, scalable, and cost-effective alternative to traditional cloud-based data marketplaces, paving the way for a more decentralized and user-centric data economy.