TY - GEN
T1 - Toward accurate and efficient emulation of public blockchains in the cloud
AU - Wang, Xinying
AU - Al-Mamun, Abdullah
AU - Yan, Feng
AU - Zhao, Dongfang
N1 - Funding Information:
Acknowledgement. This work is in part supported by National Science Foundation CCF-1756013 and IIS-1838024 (using resources provided by Amazon Web Services as part of the NSF BIGDATA program).
Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - Blockchain is an enabler of many emerging decentralized applications in areas of cryptocurrency, Internet of Things, smart healthcare, among many others. Although various open-source blockchain frameworks are available in the form of virtual machine images or docker images on public clouds, the infrastructure of mainstream blockchains nonetheless exhibits a technical barrier for many users to modify or test out new research ideas in blockchains. To make it worse, many advantages of blockchain systems can be demonstrated only at large scales, e.g., thousands of nodes, which are not always available to researchers. This paper presents an accurate and efficient emulating system to replay the execution of large-scale blockchain systems on tens of thousands of nodes. In contrast to existing work that simulates blockchains with artificial timestamp injection, the proposed system is designed to be executing real proof-of-work workload along with peer-to-peer network communications and hash-based immutability. In addition, the proposed system employs a preprocessing approach to avoid the per-node computation overhead at runtime and thus achieves practical scales. We have evaluated the system for emulating up to 20,000 nodes on Amazon Web Services (AWS), showing both high accuracy and high efficiency with millions of transactions.
AB - Blockchain is an enabler of many emerging decentralized applications in areas of cryptocurrency, Internet of Things, smart healthcare, among many others. Although various open-source blockchain frameworks are available in the form of virtual machine images or docker images on public clouds, the infrastructure of mainstream blockchains nonetheless exhibits a technical barrier for many users to modify or test out new research ideas in blockchains. To make it worse, many advantages of blockchain systems can be demonstrated only at large scales, e.g., thousands of nodes, which are not always available to researchers. This paper presents an accurate and efficient emulating system to replay the execution of large-scale blockchain systems on tens of thousands of nodes. In contrast to existing work that simulates blockchains with artificial timestamp injection, the proposed system is designed to be executing real proof-of-work workload along with peer-to-peer network communications and hash-based immutability. In addition, the proposed system employs a preprocessing approach to avoid the per-node computation overhead at runtime and thus achieves practical scales. We have evaluated the system for emulating up to 20,000 nodes on Amazon Web Services (AWS), showing both high accuracy and high efficiency with millions of transactions.
KW - Blockchains
KW - Consensus protocols
KW - Distributed systems
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U2 - 10.1007/978-3-030-23502-4_6
DO - 10.1007/978-3-030-23502-4_6
M3 - Conference contribution
AN - SCOPUS:85068205653
SN - 9783030235017
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 67
EP - 82
BT - Cloud Computing – CLOUD 2019 - 12th International Conference, Held as Part of the Services Conference Federation, SCF 2019, Proceedings
A2 - Da Silva, Dilma
A2 - Wang, Qingyang
A2 - Zhang, Liang-Jie
PB - Springer Verlag
T2 - 12th International Conference on Cloud Computing, CLOUD 2019 held as part of the Services Conference Federation, SCF 2019
Y2 - 25 June 2019 through 30 June 2019
ER -