Advanced Data Storage Model with Blockchain Technology and Huffman Algorithm

The secure storage and preservation of data is a very important issue. Different methods and studies have been presented for the secure storage of data. One of these methods is Blockchain based approaches. Blockchain technology continues to revolutionize various sectors by offering innovative solutions for reliable and distributed data management. Therefore in this study, an approach that aims to increase transaction efficiency and reduce storage costs in the Blockchain infrastructure is presented. Huffman coding, transaction clustering and PoW (Proof of Work) mechanism are integrated into the presented approach. The smart clustering algorithm we developed by taking into account transaction similarities compresses data with Huffman coding and includes compressed transactions in blocks. In addition the security of each block is ensured by using the PoW mechanism. The main contributions of our work include a dynamic clustering approach for transaction similarity analysis, the effectiveness of the on-chain data compression method and the performance evaluation of a Blockchain system integrated with PoW. In the experiments, it has been observed that the proposed system saves approximately 35% in storage costs compared to the traditional Blockchain structure and optimizes the transaction addition speed. This study provides an important step towards improving the efficiency and reliability of Blockchain technology from both theoretical and practical perspectives. The proposed approach provides an ideal solution for large-scale Blockchain applications and resource-constrained environments.