Codecs for DNA-based Data Storage Systems with Multiple Constraints for Internet of Things

Internet of Things (IoT) devices are severely constrained in computational capacity, battery life, and data storage, which fail to meet the requirement of mass data storage. With the explosive growth of data to be stored, Deoxyribonucleic acid (DNA)-based storage has become a promising direction for...

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Published in:IEEE Global Communications Conference (Online) pp. 2857 - 2862
Main Authors: Fan, Kaixin, Wu, Huaming, Li, Ruidong
Format: Conference Proceeding
Language:English
Published: IEEE 04.12.2023
Subjects:
Constrained systems
Decoding
DNA
DNA-based storage
Encode and decode
Encoding
Information rates
Internet of Things
Memory
Sequential analysis
ISSN:2576-6813
Online Access:Get full text
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Abstract Internet of Things (IoT) devices are severely constrained in computational capacity, battery life, and data storage, which fail to meet the requirement of mass data storage. With the explosive growth of data to be stored, Deoxyribonucleic acid (DNA)-based storage has become a promising direction for IoT data storage due to its various advantages, e.g. high capacity, long durability and scalability. However, DNA synthesis and sequencing are subject to errors due to certain biochemical properties of DNA. In this paper, an explicit encoding and decoding scheme for constrained systems satisfying both 3-RLL constraint and strong-( 4,1)-locally-GC-balanced constraint is designed. We propose the use of a state-splitting algorithm to encode binary strong-(4,1)-locally-balanced constrained systems with the rate 2: 3, and a state-dependent decoding algorithm to decode the encoded data. The calculation results show that the codebook of the encoding scheme in this paper is larger than that of the existing scheme, and the total number of codewords with a length of 24 is more than 6 times that of the existing scheme. The information rate is higher than that of existing coding schemes. The encoding table size required is two orders of magnitude smaller than the existing scheme.
AbstractList Internet of Things (IoT) devices are severely constrained in computational capacity, battery life, and data storage, which fail to meet the requirement of mass data storage. With the explosive growth of data to be stored, Deoxyribonucleic acid (DNA)-based storage has become a promising direction for IoT data storage due to its various advantages, e.g. high capacity, long durability and scalability. However, DNA synthesis and sequencing are subject to errors due to certain biochemical properties of DNA. In this paper, an explicit encoding and decoding scheme for constrained systems satisfying both 3-RLL constraint and strong-( 4,1)-locally-GC-balanced constraint is designed. We propose the use of a state-splitting algorithm to encode binary strong-(4,1)-locally-balanced constrained systems with the rate 2: 3, and a state-dependent decoding algorithm to decode the encoded data. The calculation results show that the codebook of the encoding scheme in this paper is larger than that of the existing scheme, and the total number of codewords with a length of 24 is more than 6 times that of the existing scheme. The information rate is higher than that of existing coding schemes. The encoding table size required is two orders of magnitude smaller than the existing scheme.
Author Li, Ruidong
Wu, Huaming
Fan, Kaixin
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  email: liruidong@ieee.org
  organization: Institute of Science and Engineering, Kanazawa University,Kanazawa,Japan,920–1192
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Snippet Internet of Things (IoT) devices are severely constrained in computational capacity, battery life, and data storage, which fail to meet the requirement of mass...
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StartPage 2857
SubjectTerms Constrained systems
Decoding
DNA
DNA-based storage
Encode and decode
Encoding
Information rates
Internet of Things
Memory
Sequential analysis
Title Codecs for DNA-based Data Storage Systems with Multiple Constraints for Internet of Things
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