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How To Optimize My Blockchain? A Multi-Level Recommendation Approach

Titelangaben

Chacko, Jeeta Ann ; Mayer, Ruben ; Jacobsen, Hans-Arno:
How To Optimize My Blockchain? A Multi-Level Recommendation Approach.
arXiv , 2023
DOI: https://doi.org/10.48550/arXiv.2301.04719

Abstract

Aside from the conception of new blockchain architectures, existing blockchain optimizations in the literature primarily focus on system or data-oriented optimizations within prevailing blockchains. However, since blockchains handle multiple aspects ranging from organizational governance to smart contract design, a holistic approach that encompasses all the different layers of a given blockchain system is required to ensure that all optimization opportunities are taken into consideration. In this vein, we define a multi-level optimization recommendation approach that identifies optimization opportunities within a blockchain at the system, data, and user level. Multiple metrics and attributes are derived from a blockchain log and nine optimization recommendations are formalized. We implement an automated optimization recommendation tool, BlockOptR, based on these concepts. The system is extensively evaluated with a wide range of workloads covering multiple real-world scenarios. After implementing the recommended optimizations, we observe an average of 20% improvement in the success rate of transactions and an average of 40% improvement in latency.

Weitere Angaben

Publikationsform: Preprint, Postprint
Institutionen der Universität: Fakultäten
Fakultäten > Fakultät für Mathematik, Physik und Informatik
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Data Systems
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik > Lehrstuhl Data Systems > Lehrstuhl Data Systems - Univ.-Prof. Dr. Ruben Mayer
Fakultäten > Fakultät für Mathematik, Physik und Informatik > Institut für Informatik
Titel an der UBT entstanden: Nein
Themengebiete aus DDC: 000 Informatik,Informationswissenschaft, allgemeine Werke > 004 Informatik
Eingestellt am: 24 Apr 2023 12:39
Letzte Änderung: 05 Feb 2024 06:59
URI: https://eref.uni-bayreuth.de/id/eprint/76053