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Towards Full Stack Adaptivity in Permissioned Blockchains

  • University of Pennsylvania

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

This paper articulates our vision for a learning-based untrustworthy distributed database. We focus on permissioned blockchain systems as an emerging instance of untrustworthy distributed databases and argue that as novel smart contracts, modern hardware, and new cloud platforms arise, future-proof permissioned blockchain systems need to be designed with full-stack adaptivity in mind. At the application level, a future-proof system must adaptively learn the best-performing transaction processing paradigm and quickly adapt to new hardware and unanticipated workload changes on the fly. Likewise, the Byzantine consensus layer must dynamically adjust itself to the workloads, faulty conditions, and network configuration while maintaining compatibility with the transaction processing paradigm. At the infrastructure level, cloud providers must enable cross-layer adaptation, which identifies performance bottlenecks and possible attacks, and determines at runtime the degree of resource disaggregation that best meets application requirements. Within this vision of the future, our paper outlines several research challenges together with some preliminary approaches.

Original languageEnglish
Pages (from-to)1073-1080
Number of pages8
JournalProceedings of the VLDB Endowment
Volume17
Issue number5
DOIs
StatePublished - 2024
Event50th International Conference on Very Large Data Bases, VLDB 2024 - Guangzhou, China
Duration: Aug 24 2024Aug 29 2024

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