skip to main content
10.1145/3490322.3490335acmotherconferencesArticle/Chapter ViewAbstractPublication PagesicbdtConference Proceedingsconference-collections
research-article

Research on Blockchain Storage Extension Based on DHT

Authors Info & Claims
Published:27 December 2021Publication History

ABSTRACT

With the rapid growth of blockchain data, the storage cost of maintaining the full node of a blockchain is getting higher and higher. This has led to the gradual weakening of the decentralization of the blockchain, increasing the risk of 51% attacks on the blockchain system. Based on DHT, we propose a blockchain storage expansion mechanism, using the Kademlia protocol to assign unique ID for every node in the blockchain network, and divide the entire node into several node clusters according to certain rules, each node cluster stores a complete blockchain data, and the nodes in the cluster only need to store a small part of the blockchain data. At the same time, in order to reduce the storage pressure of the nodes in the cluster, a dynamic reorganization mechanism is proposed, and the cluster scale will be dynamically adjusted according to the storage capacity of the nodes in the cluster. Finally, we established an experimental simulation model based on Colored Petri Nets, and verified the superiority of our proposed scheme by comparing it with the other two storage schemes.

References

  1. Satoshi Nakamoto. 2008. Bitcoin: A peer-to-peer electronic cash system. (2008). Available online: https://bitcoin.org/bitcoin.pdf (accessed on 11 June 2021).Google ScholarGoogle Scholar
  2. Wood G. Ethereum: A secure decentralised generalised transaction ledger. 2015. Available online: http://gavwood.com/Paper.pdf (accessed on 11 June 2021).Google ScholarGoogle Scholar
  3. G , Rauchs M . 2017 Global Cryptocurrency Benchmarking Study. Social Science Electronic Publishing, 2017.Google ScholarGoogle Scholar
  4. Androulaki E , Manevich Y , Muralidharan S , Hyperledger fabric: a distributed operating system for permissioned blockchains.In the Thirteenth EuroSys Conference. 2018.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Bitcoin.org. 2018. Simplifed Payment Verifcation (SPV). Available online: https://bitcoin.org/en/developer-guide#simplifed-payment-verifcation-spv. (accessed on 26 May 2021).Google ScholarGoogle Scholar
  6. Rhea S C . Handling Churn in a DHT (Awarded Best Paper!). Usenix Technical Conference. USENIX, 2004.Google ScholarGoogle Scholar
  7. Petar Maymounkov and David Mazières. 2002. Kademlia: A Peer-to-Peer Information System Based on the XOR Metric. (2002), 53–65.Google ScholarGoogle Scholar
  8. F. Dabek, E. Brunskill, M.F. Kaashoek, D. Karger, R. Morris, I. Stoica, and H. Balakrishnan. 2001. Building peer-to-peer systems with chord, a distributed lookup service. In Proceedings Eighth Workshop on Hot Topics in Operating Systems. IEEE Comput. Soc, Elmau, Germany, 81–86.Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Perard D, Lacan J, Bachy Y, Detchart J. Erasure code-based low storage blockchain node. In: Proc. of the 2018 IEEE Int'l Conf. on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData). 2018. 1622-1627.Google ScholarGoogle ScholarCross RefCross Ref
  10. Chen H, WangYJ. SSChain: A full sharding protocol for public blockchain without data migration overhead. Pervasive and Mobile Computing, 2019,59:1-15.Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Abe R, Suzuki S, Murai J. Mitigating bitcoin node storage size by DHT. In: Proc. of the Asian Internet Engineering Conf. 2018. 17-23.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Jensen, K. , and L. M. Kristensen . Coloured Petri Nets: Modelling and Validation of Concurrent Systems. Springer, 2009.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. Research on Blockchain Storage Extension Based on DHT
        Index terms have been assigned to the content through auto-classification.

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Other conferences
          ICBDT '21: Proceedings of the 4th International Conference on Big Data Technologies
          September 2021
          189 pages
          ISBN:9781450385091
          DOI:10.1145/3490322

          Copyright © 2021 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 27 December 2021

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article
          • Research
          • Refereed limited

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader

        HTML Format

        View this article in HTML Format .

        View HTML Format