TY - GEN
T1 - CLEAN
T2 - 6th ACM International Symposium on Blockchain and Secure Critical Infrastructure, BSCI 2024
AU - Chan, Weilin
AU - Wei, Yihang
AU - Jiang, Peng
AU - Xu, Lei
AU - Zhu, Liehuang
AU - Yu, Jing
N1 - Publisher Copyright:
© 2024 Copyright is held by the owner/author(s). Publication rights licensed to ACM.
PY - 2025/2/10
Y1 - 2025/2/10
N2 - Blockchain technology has garnered significant attention in academic and industrial domains due to its ability to establish a secure and trustworthy environment. As blockchain techniques continue to advance, there is a growing demand for computing resources in dimensions like storage, data processing, and network bandwidth. To meet this demand, leveraging cloud computing as an off-chain resource for scalable on-chain services has emerged as a viable solution. However, allocating cloud resources in heterogeneous cloud computing environments presents challenges due to their inherent complexity. Native cloud environments encompass diverse cloud service providers with varying capabilities, pricing models, and performance characteristics. Given the cloud's capacity to scale resources based on demand, this paper introduces a novel approach called the Cloud-enabled Scalable Blockchain (CLEAN) outsourcing model. The CLEAN model aims to develop a scalable blockchain system that minimizes costs and enhances performance. We propose a dynamic programming algorithm considering influential factors such as cloud service costs, availability, and execution time. The algorithm aims to minimize expenses while ensuring efficient resource allocation. Experimental evaluations involving rigorous analysis have been conducted to assess the effectiveness of the proposed approach. The results indicate that CLEAN outperforms the Greedy Algorithm and Genetic Algorithm (GA) by maintaining relatively low latency across all the CLEAN settings. Additionally, CLEAN demonstrates lower energy consumption compared to the Greedy Algorithm and GA, with up to a 50% and 30% reduction, respectively, as the number of transactions increases. Furthermore, the experiments determine the optimal number of orderers for the three settings to balance the trade-off between time cost and performance. Moreover, the findings also reveal that simply increasing the number of orderers in the cloud does not guarantee improved performance.
AB - Blockchain technology has garnered significant attention in academic and industrial domains due to its ability to establish a secure and trustworthy environment. As blockchain techniques continue to advance, there is a growing demand for computing resources in dimensions like storage, data processing, and network bandwidth. To meet this demand, leveraging cloud computing as an off-chain resource for scalable on-chain services has emerged as a viable solution. However, allocating cloud resources in heterogeneous cloud computing environments presents challenges due to their inherent complexity. Native cloud environments encompass diverse cloud service providers with varying capabilities, pricing models, and performance characteristics. Given the cloud's capacity to scale resources based on demand, this paper introduces a novel approach called the Cloud-enabled Scalable Blockchain (CLEAN) outsourcing model. The CLEAN model aims to develop a scalable blockchain system that minimizes costs and enhances performance. We propose a dynamic programming algorithm considering influential factors such as cloud service costs, availability, and execution time. The algorithm aims to minimize expenses while ensuring efficient resource allocation. Experimental evaluations involving rigorous analysis have been conducted to assess the effectiveness of the proposed approach. The results indicate that CLEAN outperforms the Greedy Algorithm and Genetic Algorithm (GA) by maintaining relatively low latency across all the CLEAN settings. Additionally, CLEAN demonstrates lower energy consumption compared to the Greedy Algorithm and GA, with up to a 50% and 30% reduction, respectively, as the number of transactions increases. Furthermore, the experiments determine the optimal number of orderers for the three settings to balance the trade-off between time cost and performance. Moreover, the findings also reveal that simply increasing the number of orderers in the cloud does not guarantee improved performance.
KW - cloud computing
KW - dynamic programming
KW - off-chain
KW - outsourcing
KW - scalable blockchain
UR - http://www.scopus.com/inward/record.url?scp=85219199497&partnerID=8YFLogxK
U2 - 10.1145/3659463.3660025
DO - 10.1145/3659463.3660025
M3 - Conference contribution
AN - SCOPUS:85219199497
T3 - Proceedings of the 6th ACM International Symposium on Blockchain and Secure Critical Infrastructure, BSCI 2024
BT - Proceedings of the 6th ACM International Symposium on Blockchain and Secure Critical Infrastructure, BSCI 2024
PB - Association for Computing Machinery, Inc
Y2 - 1 July 2024 through 5 July 2024
ER -