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In-memory Blockchain: Toward Efficient and Trustworthy Data Provenance for HPC Systems

Scholary Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Related Event

Title

2018 IEEE International Conference on Big Data, Big Data 2018

Event type

Conference

Date

12/10/2018 - 12/13/2018

Location

SeattleUnited States

Abstract

The state-of-the-art approaches for tracking data provenance on high-performance computing (HPC) systems are either supported by file systems or relational databases. These techniques shared the same critique on the provenance data's fidelity and the associated I/O overhead. This paper envisions to track the HPC data provenance using a distributed in-memory ledger - the core technique leveraged by blockchains and proven to be highly trustworthy by many large-scale applications. We pinpoint two system challenges - storage architecture and consensus protocol - for adopting blockchains to HPC and make the following contributions: (i) We design a new in-memory blockchain architecture for HPC systems, exploiting the high-performance network infrastructure InfiniBand and greatly reducing the I/O overhead; and (ii) We develop a new consensus protocol, namely proof-of-reproducibility (PoR), crafted for the new architecture, which takes into account both proof-of-work (PoW) and proof-of-stake (PoS) mechanisms. The correctness of PoR is both theoretically proven and experimentally verified. A prototype system is implemented and evaluated with more than one million transactions, showing 32× speedup compared to the filesystem-based provenance service and four orders of magnitude speedup compared to the database-based provenance service.

Publication Information

Output type

Scholary Output:
Chapter in Book/Report/Conference proceeding
Conference contribution

Original language

English (US)

Article number

8621897

Pages from-to (Number of pages)

Pages 3808-3813 (6 pages)

Publication milestones

  • Published - 01/22/2019

Publication status

Published - 01/22/2019

Publisher

Institute of Electrical and Electronics Engineers Inc.

Publication series

  • Publication series name: Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

ISBN (Electronic)

9781538650356

Publication IDs

  • Scopus: 85062553669

Host publication title

Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018

Host publication editors

  • Yang Song
  • Bing Liu
  • Kisung Lee
  • Naoki Abe
  • Calton Pu
  • Mu Qiao
  • Nesreen Ahmed
  • Donald Kossmann
  • Jeffrey Saltz
  • Jiliang Tang
  • Jingrui He
  • Huan Liu
  • Xiaohua Hu

Publication metrics

Metrics

Fractional count
1
Fractional count
0.25
Fractional count
3
Fractional count
0.75
Fractional count
1
Fractional count
1
Scopus
citations

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Citation count
24
Captures
34

Funding Details

This paper presents a new in-memory blockchain system architecture where ledgers are maintained mostly in memory and a new consensus protocol crafted for the new architecture. The new architecture and new consensus collectively enable an efficient blockchain-like ledger service for trustworthy data provenance on HPC systems. The correctness of the proposed consensus is both theoretically proven and experimentally verified. A lightweight system prototype is implemented and evaluated with more than one million transactions, showing 32× speedup compared to the filesystem-based provenance service and four orders of magnitude speedup compared to the database-based provenance service. Acknowledgement. This work is in part supported by a Microsoft Azure Research Award.