BS-GeoEduNet 1.0: Blockchain-Assisted Serverless Framework for Geospatial Educational Information Networks

Abstract

The integration of a blockchain-supported serverless computing framework enhances the performance of computational and analytical operations and the provision of services within internet-based data centers, rather than depending on independent desktop computers. Therefore, in the present research paper, a blockchain-assisted serverless framework for geospatial data visualizations is implemented. The proposed BS-GeoEduNet 1.0 framework leverages the capabilities of AWS Lambda for serverless computing, providing a reliable and efficient solution for data storage, analysis, and distribution. The proposed framework incorporates AES encryption, decryption layers, and queue implementation to achieve a scalable approach for handling larger files. It implements a queueing mechanism during the heavier input/output processes of file processing by using Apache KAFKA, enabling the system to handle large volumes of data efficiently. It concludes with the visualization of all geospatial-enabled NIT/IIT details on the proposed framework, which utilizes the data fetched from MongoDB. The experimental findings validate the reliability and efficiency of the proposed system, demonstrating its efficacy in geospatial data storage and processing.