Analysis of strategies for scalable transaction creation in blockchains
Authors: 
Ole Delzer, Richard Hobeck, 
Ingo Weber, Dominik Kaaser, Michael Sober, Stefan SchulteAuthors Info & Claims
Abstract
The growing popularity of blockchains highlights the need to improve their scalability. While previous research has focused on scaling transaction processing, the scalability of transaction creation remains unexplored. This issue is particularly important for organizations needing to send large volumes of transactions quickly or continuously. Scaling transaction creation is challenging, especially for blockchain platforms like Ethereum, which require transactions to include a sequence number. This paper proposes four different methods to scale transaction creation. Our experimental evaluation assesses the scalability and latency of these methods, identifying two as feasible for scaling transaction creation. Additionally, we provide an in-depth theoretical analysis of these two methods.
References
[1]
Bach LM, Mihaljević B, Z̆agar M (2018) Comparative analysis of blockchain consensus protocols. In: International convention on information and communication technology, electronics and microelectronics (MIPRO). IEEE, pp 1545–1550
[2]
Berenbrink P, Friedetzky T, Hahn C, et al (2021) Infinite balanced allocation via finite capacities. In: 41st IEEE international conference on distributed computing systems (ICDCS). IEEE, pp 965–975
[3]
Bratanova A, Devaraj D, Horton J, et al (2019) Blockchain 2030: a look at the future of blockchain in Australia. Tech rep, Data61, CSIRO, Brisbane, Australia
[4]
Crain T, Natoli C, Gramoli V (2021) Red belly: a secure, fair and scalable open blockchain. In: IEEE symposium on security and privacy (SP). IEEE, pp 466–483
[5]
Croman K, Decker C, Eyal I, et al (2016) On scaling decentralized blockchains. In: Financial cryptography and data security. Springer, pp 106–125
[6]
Dickerson T, Gazzillo P, Herlihy M, et al (2017) Adding concurrency to smart contracts. In: ACM symposium on principles of distributed computing. ACM, pp 303–312
[7]
Dinh TTA, Wang J, Chen G, et al (2017) BLOCKBENCH: A framework for analyzing private blockchains. In: 2017 ACM International conference on management of data. ACM, pp 1085–1100
[8]
Dubhashi DP and Ranjan D Balls and bins: a study in negative dependence Random Struct Algorithms 1998 13 2 99-124
[9]
Gervais A, Karame GO, Wüst K, et al (2016) On the security and performance of proof of work blockchains. In: 2016 ACM SIGSAC conference on computer and communications security. ACM, pp 3–16
[10]
Guo H, Yu X (2022) A survey on blockchain technology and its security. Blockchain Res Appl 3(2):100067
[11]
Joshi S (2021) Feasibility of proof of authority as a consensus protocol model. CoRR abs/2109.02480
[12]
Khan D, Jung LT, and Hashmani MA Systematic literature review of challenges in blockchain scalability Appl Sci 2021 11 20 9372
[13]
Lobmaier D, Konlechner R, Schulte S, et al (2024) Assessing routing algorithms for payment channel networks. Distributed Ledger Technologies: Research and Practice 3:6:1–6:27
[14]
Mitzenmacher M, Upfal E (2005) Probability and computing: randomized algorithms and probabilistic analysis. Cambridge University Press
[15]
Motwani R and Raghavan P Random Algorithms 1995 Cambridge Cambridge University Press
[16]
Nakamoto S (2008) Bitcoin: a peer-to-peer electronic cash system. http://www.bitcoin.org/bitcoin.pdf
[17]
Saleh F Blockchain without waste: proof-of-stake Rev Financ Stud 2021 34 3 1156-1190
[18]
Szabo N (1997) Formalizing and securing relationships on public networks. First Monday 2(9)
[19]
Vukolić M (2016) The quest for scalable blockchain fabric: proof-of-work vs. BFT replication. In: Open problems in network security. Springer, pp 112–125
[20]
Wang R, Ye K, Xu C (2019) Performance benchmarking and optimization for blockchain systems: a Survey. In: Second international conference on blockchain. Springer, pp 171–185
[21]
Weber I, Gramoli V, Staples M, et al (2017) On availability for blockchain-based systems. In: IEEE international symposium on reliable distributed systems. IEEE, pp 64–73
[22]
Wieder U Hashing, load balancing and multiple choice Found Trends Theor Comput Sci 2017 12 3–4 275-379
[23]
Wood G et al. Ethereum: a secure decentralised generalised transaction ledger Ethere Project Yellow Paper 2014 151 2014 1-32
[24]
Xu X, Pautasso C, Zhu L, et al (2018) A pattern collection for blockchain-based applications. In: European conference on pattern languages of programs. ACM, pp 1–20
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Published In
© The Author(s) 2024.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 29 July 2024
Accepted: 10 July 2024
Received: 19 February 2024
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- Christian Doppler Forschungsgesellschaft
- Technische Universität Hamburg (3140)
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