Proposes a framework for analyzing performance bottlenecks in blockchain systems, highlighting critical metrics and their interrelations.
Abstract With the widespread application of blockchain technology across variousindustries, detecting and analyzing performance bottlenecks is crucialfor evaluating and optimizing blockchain system performance. How-ever, current research lacks general performance metrics for detectingand analyzing performance bottlenecks, and few studies focus on thisaspect within blockchain systems. To address this, this paper first pro-poses 18 fine-grained performance metrics to comprehensively evaluateperformance across various layers of blockchain systems. Subsequently,We introduce a generalized loosely-coupled performance measurementframework to capture these metrics and construct the causal relation-ship between them, i.e., the mesoscopic performance structure. Thisapproach allows for the detection and analysis of performance bot-tlenecks. Finally, numerous experimental results demonstrate that thecausality between the relevant performance metrics disappears whenthe system reaches a performance bottleneck. Additionally, the frame-work has a performance impact of less than 15% on ChainMaker.
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song et al. (2024) studied this question.
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