Tackling data inefficiency: Compressing the bitcoin blockchain

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

In blockchain-based solutions, the amount of data stored in the blockchain increases steadily. Considerable amounts of data accordingly need to be download and stored at decentralized nodes to carry out meaningful validations. For the Bitcoin blockchain, approximately 197 GB must currently be downloaded and processed by any node aiming to fully verify the correctness of stored transactions. This represents an emerging problem with respect to resource-constrained thin clients that lack the required download or storage capacities, but with which meaningful validations still need to be carried out. This problem will gain even more relevance in the future, as blockchain technology is applied to new domains such as the Internet of Things (IoT) that necessitate the use of thin clients. We address this emerging problem by proposing a novel compressible blockchain architecture. In our proposal, we use a snapshot-based approach, to create snapshots of the blockchain at regular intervals and store them in blocks. These blocks are chained, forming a second blockchain that is linked to the primary chain. In this way, the amount of data that needs to be downloaded and stored by decentralized nodes is reduced considerably, while the full validation of the entire blockchain still remains feasible. In this paper, we describe the proposed compressible blockchain architecture in detail. We conducted evaluations that demonstrate the feasibility of the proposed solution and show its advantages over related approaches introduced in the literature. Overall, our design can be used to reduce the size of the blockchain by up to 93%, facilitating secure blockchain-based applications even on resource-constrained thin clients such as IoT devices.

Original languageEnglish
Title of host publication2019 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering
Subtitle of host publicationTrustCom/BigDataSE 2019
PublisherInstitute of Electrical and Electronics Engineers
Pages626-633
Number of pages8
ISBN (Electronic)9781728127767
DOIs
Publication statusPublished - 1 Aug 2019
Event18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering - Rotorua, New Zealand
Duration: 5 Aug 20198 Aug 2019

Publication series

NameProceedings - 2019 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019

Conference

Conference18th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/13th IEEE International Conference On Big Data Science And Engineering
Abbreviated titleTrustCom/BigDataSE 2019
CountryNew Zealand
CityRotorua
Period5/08/198/08/19

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Keywords

  • Blockchain size
  • Compressible blockchain
  • Resource constrained devices
  • Snapshot
  • Thin client
  • UTXO

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality
  • Artificial Intelligence

Cite this

Marsalek, A., Zefferer, T., Fasllija, E., & Ziegler, D. (2019). Tackling data inefficiency: Compressing the bitcoin blockchain. In 2019 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering: TrustCom/BigDataSE 2019 (pp. 626-633). [8887331] (Proceedings - 2019 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications/13th IEEE International Conference on Big Data Science and Engineering, TrustCom/BigDataSE 2019). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/TrustCom/BigDataSE.2019.00089