AN END-TO-END DECENTRALIZED INTERNET OF THINGS (IOT) DATA MODEL

Abstract

In today’s data-driven society, the demand for secure, efficient, and decentralized data storage and communication solutions has become increasingly critical. This thesis explores the design and implementation of an end-to-end decentralized data model that leverages IOTA Streams and Swarm Storage technologies. The research begins by examining the limitations and challenges associated with centralized data models, such as single points of failure, data breaches, and high maintenance costs. To overcome these challenges, a decentralized approach is proposed, which combines the strengths of IOTA Streams and Swarm Storage. IOTA Streams is a messaging and data transmission protocol that provides a secure and tamper-proof communication layer. It allows for end-to-end encryption, data integrity verification, and fine-grained access control. By utilizing IOTA Streams, the proposed data model ensures the confidentiality and integrity of data throughout its lifecycle. Swarm Storage, on the other hand, offers a decentralized and fault-tolerant storage infrastructure. It employs a distributed hash table (DHT) network to store and retrieve data, enabling data redundancy, availability, and scalability. The integration of Swarm Storage within the data model enhances data persistence and accessibility in a decentralized manner. The thesis presents the design and implementation details of the end-to-end decentralized data model. It covers aspects such as data ingestion, transmission, storage, retrieval, and access control. The model incorporates cryptographic techniques, consensus mechanisms, and decentralized identifiers (DIDs) to establish a robust and secure data ecosystem. To evaluate the performance and effectiveness of the proposed data model, a series of experiments and simulations are conducted. The experiments assess factors such as data transfer speed, storage efficiency, fault tolerance, and resilience against attacks.The results validate the feasibility and advantages of the end-to-end decentralized data model based on IOTA Streams and Swarm Storage. In conclusion, this thesis demonstrates the potential of combining IOTA Streams and Swarm Storage to achieve an end-to-end decentralized data model. The proposed solution addresses the limitations of centralized data models and provides a secure, efficient, and scalable alternative for storing and transmitting data in decentralized environments. The findings of this research contribute to the field of decentralized systems and can guide the development of future decentralized data solutions.