DNA Computing-Based Multi-Source Data Storage Model in Digital Twins

Abstract

The work aims to study the application of Deoxyribonucleic Acid (DNA) multi-source data storage in Digital Twins (DT) . Through the investigation of the research status of DT and DNA computing, the work puts forward the concept of DNA multi-source data storage for DT. Raptor code is improved from the design direction of degree distribution function, and six degree function distribution schemes are proposed in turn in the process of describing the research method. Additionally, a quaternary dynamic Huffman coding method is applied in DNA data storage, combined with the improved concatenated code as the error correction code. Considering the content of cytosine deoxynucleotide (C) and guanine deoxynucleotide Guanine (G) and the distribution of homopolymer in DNA storage, the work proposes and verifies an improved concatenated code algorithm Deoxyribonucleic Acid-Improved Concatenated code (DNA-ICC) . The results show that while the Signal-to-Noise Ratio (SNR) increases, the Bit Error Rate (BER) decreases gradually and the trend is similar. But the anti-interference ability of the degree distribution function optimized by the probability transfer method is better. The BER of DNA-ICC scheme decreases with the decrease of error probability, which is stronger than other error correction codes. Compared with the original concatenated code, it saves at least 1.65 s, and has a good control effect on homopolymer. When the size of homopolymer exceeds 4 nt, the probability of homopolymer is only 0.44%. The proposed Quaternary dynamic Huffman code and concatenated error correction code have excellent performance.