4.4 Article

Fine-Grained Benchmarking and Targeted Optimization: Enabling Green IoT-Oriented Blockchain in the 6G Era

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TGCN.2022.3185610

关键词

Internet of Things (IoT); 6G; blockchain; benchmarking; performance optimization

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For 6G-empowered IoT, blockchain is considered fundamental for addressing security and privacy issues, but current blockchains have flaws in performance and scalability. To optimize these blockchains, a standard benchmarking tool is needed, and targeted optimization strategies should be designed. This paper presents a novel pipeline for green IoT-oriented blockchains in 6G era, including a benchmarking framework and targeted optimization mechanisms. The pipeline is applied to IOTA and successfully addresses its issues.
For 6G-empowered IoT, blockchain is widely regarded as a fundamental technique for addressing the security and privacy issues. Nonetheless, the current blockchains suffer from several flaws, especially the low performance and scalability. They seriously hinder the blockchain deployments in 6G-empowered IoT with high concurrency and complexity. To address this problem, we need to better understand blockchains and try to optimize them. However, we still lack a standard tool for comprehensively benchmarking the IoT-oriented blockchains in 6G era. As to blockchain optimization, the current general-purpose strategies can hardly hold efficiency all the time due to the heterogeneity of 6G-empowered IoT. In this paper, we present a novel pipeline for facilitating the green IoT-oriented blockchains in 6G era, called fine-grained benchmarking + targeted optimization. Specifically, we first design a benchmarking framework which realizes the whole workflow of data acquisition, log parsing, and metric visualization, offering quantitative blockchain performance reports. Moreover, our framework provides ten metrics divided into four dimensions, leading blockchain benchmarking to the fine-grained level. Based on the acquired insights, we further present the concept of targeted optimization, i.e., directly designing optimization strategies based on the metrics that perform poorly in benchmarking. To better illustrate this pipeline, we take IOTA, the most potential IoT-oriented blockchain in 6G era, as a case study. We observe two defects of IOTA, i.e., low power efficiency and slow ledger synchronization. Following our pipeline, we design two targeted optimization mechanisms, namely Proof-of-Resource Efficiency and Dynamic Local Snapshot Protocol. Extensive experiments demonstrate that our pipeline can maximize the optimization efficiency, successfully addressing the issues hindering IOTA. Last but not least, we emphasize that the proposed pipeline can also be applied by other IoT-oriented blockchains in the 6G era.

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