Page 260 - 《软件学报》2026年第1期
P. 260
彭泽顺 等: 面向跨地理区域联盟链的事务处理技术综述 257
[104] Nathan S, Govindarajan C, Saraf A, Sethi M, Jayachandran P. Blockchain meets database: Design and implementation of a blockchain
relational database. arXiv:1903.01919, 2019.
[105] Ruan PC, Loghin D, Ta QT, Zhang MH, Chen G, Ooi BC. A transactional perspective on execute-order-validate blockchains. In: Proc.
of the 2020 ACM SIGMOD Int’l Conf. on Management of Data. Portland: ACM, 2020. 543–557. [doi: 10.1145/3318464.3389693]
[106] Xu C, Zhang C, Xu JL, Pei J. SlimChain: Scaling blockchain Trans. through off-chain storage and parallel processing. Proc. of the
VLDB Endowment, 2021, 14(11): 2314–2326. [doi: 10.14778/3476249.3476283]
[107] Faleiro JM, Abadi DJ. Rethinking serializable multiversion concurrency control. arXiv:1412.2324, 2015.
[108] Amiri MJ, Agrawal D, El Abbadi A. ParBlockchain: Leveraging transaction parallelism in permissioned blockchain systems. In: Proc. of
the 39th IEEE Int’l Conf. on Distributed Computing Systems. Dallas: IEEE, 2019. 1337–1347. [doi: 10.1109/ICDCS.2019.00134]
[109] Baheti S, Anjana PS, Peri S, Simmhan Y. DiPETrans: A framework for distributed parallel execution of Trans. of blocks in blockchains.
Concurrency and Computation: Practice and Experience, 2022, 34(10): e6804. [doi: 10.1002/cpe.6804]
[110] Thomson A, Diamond T, Weng SC, Ren K, Shao P, Abadi DJ. Calvin: Fast distributed Trans. for partitioned database systems. In: Proc.
of the 2012 ACM SIGMOD Int’l Conf. on Management of Data. Scottsdale: ACM, 2012. 1–12. [doi: 10.1145/2213836.2213838]
[111] Cahill MJ, Röhm U, Fekete AD. Serializable isolation for snapshot databases. ACM Trans. on Database Systems (TODS), 2009, 34(4):
20. [doi: 10.1145/1620585.1620587]
[112] Ports DRK, Grittner K. Serializable snapshot isolation in PostgreSQL. arXiv:1208.4179, 2012.
[113] Li ZM, Romano P, Van Roy P. Sparkle: Speculative deterministic concurrency control for partially replicated transactional stores. In:
Proc. of the 49th Annual IEEE/IFIP Int’l Conf. on Dependable Systems and Networks (DSN). Portland: IEEE, 2019. 164–175. [doi: 10.
1109/DSN.2019.00029]
[114] Faleiro JM, Abadi DJ, Hellerstein JM. High performance transactions via early write visibility. Proc. of the VLDB Endowment, 2017,
10(5): 613–624. [doi: 10.14778/3055540.3055553]
[115] Lai ZL, Liu C, Lo E. When private blockchain meets deterministic database. Proc. of the ACM on Management of Data, 2023, 1(1): 98.
[doi: 10.1145/3588952]
[116] Qi XD, Chen ZH, Zhuo HZ, Xu QQ, Zhu CY, Zhang Z, Jin CQ, Zhou AY, Yan Y, Zhang H. SChain: Scalable concurrency over flexible
permissioned blockchain. In: Proc. of the 39th IEEE Int’l Conf. on Data Engineering. Anaheim: IEEE, 2023. 1901–1913. [doi: 10.1109/
ICDE55515.2023.00148]
[117] Chen ZH, Zhuo HZ, Xu QQ, Qi XD, Zhu CY, Zhang Z, Jin CQ, Zhou AY, Yan Y, Zhang H. SChain: A scalable consortium blockchain
exploiting intra- and inter-block concurrency. Proc. of the VLDB Endowment, 2021, 14(12): 2799–2802. [doi: 10.14778/3476311.
3476348]
[118] Karypis G, Kumar V. METIS: A software package for partitioning unstructured graphs, partitioning meshes, and computing fill-
reducing orderings of sparse matrices. 1997. https://conservancy.umn.edu/items/2f610239-590c-45c0-bcd6-321036aaad56
[119] Bailis P, Davidson A, Fekete A, Ghodsi A, Hellerstein JM, Stoica I. Highly available transactions: Virtues and limitations (extended
version). arXiv:1302.0309, 2013.
[120] Shapiro M, Preguiça N, Baquero C, Zawirski M. Conflict-free replicated data types. In: Proc. of the 13th Int’l Symp. on Stabilization,
Safety, and Security of Distributed Systems. Grenoble: Springer, 2011. 386–400. [doi: 10.1007/978-3-642-24550-3_29]
[121] Nasirifard P, Mayer R, Jacobsen HA. FabricCRDT: A conflict-free replicated datatypes approach to permissioned blockchains. In: Proc.
of the 20th Int’l Middleware Conf. Davis: ACM, 2019. 110–122. [doi: 10.1145/3361525.3361540]
[122] Sharma A, Schuhknecht FM, Agrawal D, Dittrich J. Blurring the lines between blockchains and database systems: The case of
Hyperledger Fabric. In: Proc. of the 2019 Int’l Conf. on Management of Data. Amsterdam: ACM, 2019. 105–122. [doi: 10.1145/
3299869.3319883]
[123] Hong ZC, Guo S, Zhou EY, Zhang JY, Chen WH, Liang JW, Zhang J, Zomaya A. Prophet: Conflict-free sharding blockchain via
Byzantine-tolerant deterministic ordering. arXiv:2304.08595, 2023.
[124] Li MZ, Lin Y, Zhang J, Wang W. CoChain: High concurrency blockchain sharding via consensus on consensus. In: Proc. of the 2023
IEEE Conf. on Computer Communications. New York: IEEE, 2023. 1–10. [doi: 10.1109/INFOCOM53939.2023.10228892]
[125] Zhang YZ, Pan SR, Yu JS. TxAllo: Dynamic transaction allocation in sharded blockchain systems. In: Proc. of the 39th IEEE Int’l Conf.
on Data Engineering. Anaheim: IEEE, 2023. 721–733. [doi: 10.1109/ICDE55515.2023.00390]
[126] Luu L, Narayanan V, Zheng CD, Baweja K, Gilbert S, Saxena P. A secure sharding protocol for open blockchains. In: Proc. of the 2016
ACM SIGSAC Conf. on Computer and Communications Security. Vienna: ACM, 2016. 17–30. [doi: 10.1145/2976749.2978389]
[127] Wang JP, Wang H. Monoxide: Scale out blockchains with asynchronous consensus zones. In: Proc. of the 16th USENIX Symp. on
Networked Systems Design and Implementation. Boston: USENIX Association, 2019. 95–112.
[128] Popov S. The tangle. IOTA Whitepaper, Version 1.4.3., 2024. https://www.allcryptowhitepapers.com/iota-whitepaper/

