Scalable IoT Data Access with Block Chain and Bloom Filters
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Abstract
The Internet of Things (IoT) connects numerous devices that perform unique tasks and gather various types of data, requiring scalable, efficient, and secure management. Traditional centralized solutions have limitations concerning security and scalability. Blockchain, a decentralized system, can enhances data integrity and security but poses challenges because of the IoT devices' resource limitations. A multi-layer blockchain framework is proposed in this study to improve scalability and access control for IoT data management by using multiple permissioned blockchains and enabling parallel processing. As an extension to this, this architecture is also integrated with decentralized storage, InterPlanetary File System or IPFS to facilitate scalability of the framework. Bloom filters have been used in IPFS to optimize data retrieval by filtering out non-existent content before initiating full data retrieval processes. The investigation is separated into four sections: the examination of latency, throughput, and IPFS query and response time and time taken for data retrieval using Bloom’s filter. The experimental results show that proposed framework has a low response time for detection of presence of data and measures 1.21345 s when data is present and 0.02476 s when data is not present. The suggested method works better than most of today’s cutting-edge consensus methods. Additionally, it is shown that the suggested method works well in IoT applications that demand low latency or resource efficiency.
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