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The high density, large capacity, and long-term stability of DNA molecules make them an emerging storage medium that is especially suitable for the long-term storage of large datasets. The DNA sequences used in storage need to consider relevant constraints to avoid nonspecific hybridization reactions, such as the No-runlength constraint, GC-content, and the Hamming distance. In this work, a new nonlinear control parameter strategy and a random opposition-based learning strategy were used to improve the Harris hawks optimization algorithm (for the improved algorithm NOL-HHO) in order to prevent it from falling into local optima. Experimental testing was performed on 23 widely used benchmark functions, and the proposed algorithm was used to obtain better coding lower bounds for DNA storage. The results show that our algorithm can better maintain a smooth transition between exploration and exploitation and has stronger global exploration capabilities as compared with other algorithms. At the same time, the improvement of the lower bound directly affects the storage capacity and code rate, which promotes the further development of DNA storage technology.

No abstract

In an era of information explosion, dealing with massive data has become a problem. Since DeoxyriboNucleic Acid (DNA) is a high-density storage medium with long storage endurance, a DNA based storage system is a viable solution. The first consideration of a DNA storage system is the DNA codes, which can avoid non-specific hybridization of DNA strands in the hybridization reaction process by using related constraints, such as Hamming distance constraints, GC-content constraints, and no-runlength constraints. A K-means Multi-Verse Optimizer (KMVO) algorithm is proposed to construct a better code boundary than the previous Multi-Verse Optimizer (MVO) algorithm that satisfies the above constraints. Our results can store information more efficiently over a given length, increasing storage utilization. INDEX TERMS DNA code design, DNA storage, k-means, MVO algorithm.

The rapid development of information technology has generated substantial data, which urgently requires new storage media and storage methods. DNA, as a storage medium with high density, high durability, and ultra-long storage time characteristics, is promising as a potential solution. However, DNA storage is still in its infancy and suffers from low space utilization of DNA strands, high read coverage, and poor coding coupling. Therefore, in this work, an adaptive coding DNA storage system is proposed to use different coding schemes for different coding region locations, and the method of adaptively generating coding constraint thresholds is used to optimize at the system level to ensure the efficient operation of each link. Images, videos, and PDF files of size 698 KB were stored in DNA using adaptive coding algorithms. The data were sequenced and losslessly decoded into raw data. Compared with previous work, the DNA storage system implemented by adaptive coding proposed in this paper has high storage density and low read coverage, which promotes the development of carbon-based storage systems.