skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Can We Store the Whole World Data in DNA-Storage?
The total amount of data in the world has been increasing rapidly. However, the increase of data storage capacity is much slower than that of data generation. How to store and archive such a huge amount of data becomes critical and challenging. Synthetic Deoxyribonucleic Acid (DNA) storage is one of the promising candidates with high density and long-term preservation for archival storage systems. The existing works have focused on the achievable feasibility of a small amount of data when using DNA as storage. In this paper, we investigate the scalability and potentials of DNA storage when a huge amount of data, like all available data from the world, is to be stored. First, we investigate the feasible storage capability that can be achieved in a single DNA pool/tube based on current and future technologies. Then, the indexing of DNA storage is explored. Finally, the metadata overhead based on future technology trends is also investigated.  more » « less
Award ID(s):
1812537
PAR ID:
10276609
Author(s) / Creator(s):
Date Published:
Journal Name:
Usenix HotStorage 2020
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. As the volume of data is rapidly produced every day, there is a need for the storage media to keep up with the growth rate of digital data created. Despite emerging storage solutions that have been proposed such as Solid State Drive (SSD) with quad-level cells (QLC) or penta-level cells (PLC), Shingled Magnetic Recording (SMR), LTO-tape, etc., these technologies still fall short of meeting the demand for preserving huge amounts of available data. Moreover, current storage solutions have a limited lifespan, often lasting just a few years. To ensure long-term preservation, data must be continuously migrated to new storage drives. Therefore, there is a need for alternative storage technologies that not only offer high storage capacity but also long persistency. In contrast to existing storage devices, Synthetic Deoxyribonucleic Acid (DNA) storage emerges as a promising candidate for archival data storage, offering both high-density storage capacity and the potential for long-term data preservation. In this paper, we will introduce DNA storage, discuss the capabilities of DNA storage based on the current biotechnologies, discuss possible improvements in DNA storage, and explore further improvements with future technologies. Currently, the limitations of DNA storage are due to its weaknesses including high error rates, long access latency, etc. In this paper, we will focus on possible DNA storage research issues based on its relevant bio and computer technologies. Also, we will provide potential solutions and forward-looking predictions about the development and the future of DNA storage. We will discuss DNA storage from the following five perspectives: 1) We will describe the basic background of DNA storage including the basic technologies of read/write DNA storage, data access processes such as Polymerase Chain Reaction (PCR) based random access, encoding schemes from digital data to DNA, and required DNA storage format. 2) We will describe the issues of DNA storage based on the current technologies including bio-constraints during the encoding process such as avoiding long homopolymers and containing certain GC contents, different types of errors in synthesis and sequencing processes, low practical capacity with the current technologies, slow read and write performance, and low encoding density for random accesses. 3) Based on the previously mentioned issues, we will summarize the current solutions for each issue, and also give and discuss the potential solutions based on the future technologies. 4) From a system perspective, we will discuss how the DNA storage system will look if the DNA storage becomes commercialized and is widely equipped in archive systems. Some questions will be discussed including i) How to efficiently index data in DNA storage? ii) What is a good storage hierarchical storage system with DNA storage? iii) What will DNA storage be like with the development of technology? 5) Finally, we will provide a comparison with other competitive technologies. 
    more » « less
  2. Abstract DNA is a compelling alternative to non-volatile information storage technologies due to its information density, stability, and energy efficiency. Previous studies have used artificially synthesized DNA to store data and automated next-generation sequencing to read it back. Here, we report digital Nucleic Acid Memory (dNAM) for applications that require a limited amount of data to have high information density, redundancy, and copy number. In dNAM, data is encoded by selecting combinations of single-stranded DNA with (1) or without (0) docking-site domains. When self-assembled with scaffold DNA, staple strands form DNA origami breadboards. Information encoded into the breadboards is read by monitoring the binding of fluorescent imager probes using DNA-PAINT super-resolution microscopy. To enhance data retention, a multi-layer error correction scheme that combines fountain and bi-level parity codes is used. As a prototype, fifteen origami encoded with ‘Data is in our DNA!\n’ are analyzed. Each origami encodes unique data-droplet, index, orientation, and error-correction information. The error-correction algorithms fully recover the message when individual docking sites, or entire origami, are missing. Unlike other approaches to DNA-based data storage, reading dNAM does not require sequencing. As such, it offers an additional path to explore the advantages and disadvantages of DNA as an emerging memory material. 
    more » « less
  3. null (Ed.)
    Deoxyribonucleic Acid (DNA) as a storage medium with high density and long-term preservation properties can satisfy the requirement of archival storage for rapidly increased digital volume. The read and write processes of DNA storage are error-prone. Images widely used in social media have the properties of fault tolerance which are well fitted to the DNA storage. However, prior work simply investigated the feasibility of DNA storage storing different types of data and simply store images in DNA storage, which did not fully investigate the fault-tolerant potential of images in the DNA storage. In this paper, we proposed a new image-based DNA system called IMG-DNA, which can efficiently store images in DNA storage with improved DNA storage robustness. First, a new DNA architecture is proposed to fit JPEG-based images and improve the image’s robustness in DNA storage. Moreover, barriers inserted in DNA sequences efficiently prevent error propagation in images of DNA storage. The experimental results indicate that the proposed IMG-DNA achieves much higher fault-tolerant than prior work. 
    more » « less
  4. Accurate 3D object detection in real-world environments requires a huge amount of annotated data with high quality. Acquiring such data is tedious and expensive, and often needs repeated effort when a new sensor is adopted or when the detector is deployed in a new environment. We investigate a new scenario to construct 3D object detectors: learning from the predictions of a nearby unit that is equipped with an accurate detector. For example, when a self-driving car enters a new area, it may learn from other traffic participants whose detectors have been optimized for that area. This setting is label-efficient, sensor-agnostic, and communication-efficient: nearby units only need to share the predictions with the ego agent (e.g., car). Naively using the received predictions as ground-truths to train the detector for the ego car, however, leads to inferior performance. We systematically study the problem and identify viewpoint mismatches and mislocalization (due to synchronization and GPS errors) as the main causes, which unavoidably result in false positives, false negatives, and inaccurate pseudo labels. We propose a distance-based curriculum, first learning from closer units with similar viewpoints and subsequently improving the quality of other units' predictions via self-training. We further demonstrate that an effective pseudo label refinement module can be trained with a handful of annotated data, largely reducing the data quantity necessary to train an object detector. We validate our approach on the recently released real-world collaborative driving dataset, using reference cars' predictions as pseudo labels for the ego car. Extensive experiments including several scenarios (e.g., different sensors, detectors, and domains) demonstrate the effectiveness of our approach toward label-efficient learning of 3D perception from other units' predictions. 
    more » « less
  5. Deoxyribonucleic Acid (DNA), with its ultra-high storage density and long durability, is a promising long-term archival storage medium and is attracting much attention today. A DNA storage system encodes and stores digital data with synthetic DNA sequences and decodes DNA sequences back to digital data via sequencing. Many encoding schemes have been proposed to enlarge DNA storage capacity by increasing DNA encoding density. However, only increasing encoding density is insufficient because enhancing DNA storage capacity is a multifaceted problem. This paper assumes that random accesses are necessary for practical DNA archival storage. We identify all factors affecting DNA storage capacity under current technologies and systematically investigate the practical DNA storage capacity with several popular encoding schemes. The investigation result shows the collision between primers and DNA payload sequences is a major factor limiting DNA storage capacity. Based on this discovery, we designed a new encoding scheme called Collision Aware Code (CAC) to trade some encoding density for the reduction of primer-payload collisions. Compared with the best result among the five existing encoding schemes, CAC can extricate 120% more primers from collisions and increase the DNA tube capacity from 211.96 GB to 295.11 GB. Besides, we also evaluate CAC's recoverability from DNA storage errors. The result shows CAC is comparable to those of existing encoding schemes. 
    more » « less