Decentralized IoT Data Storage Using Edge & Mobile Devices

Abstract

The rapid proliferation of Internet of Things (IoT) devices has led to an exponential increase in data generation, enabling new data-driven insights while simultaneously introducing significant storage challenges for service providers. Conventional solutions address this growth by expanding cloud-based storage infrastructures, increasing dependence on cloud providers and associated operational costs. This paper proposes a decentralized IoT data storage architecture that shifts the storage of device-generated measurements from cloud infrastructure (CI) to users' mobile phones (MPs). By leveraging the computational and storage capabilities of modern edge devices and MPs, the proposed approach reduces reliance on centralized cloud storage while preserving low-latency data access. Contemporary MPs provide sufficient capacity to support long-term retention of user-generated IoT data at the user level. Key challenges related to security, trust, scalability, and edge-side storage optimization are discussed, along with potential solutions including lightweight blockchain-based verification, adaptive network optimization, and federated learning. The findings indicate that the proposed architecture offers an efficient, scalable, and cost-effective alternative to cloud-centric data storage, enabling more decentralized and user-centric IoT data management.