Scalability of blockchain: Review of cross-sharding with high communication overhead

Open Access

Issue		BIO Web Conf. Volume 97, 2024 Fifth International Scientific Conference of Alkafeel University (ISCKU 2024)


Article Number		00075
Number of page(s)		23
DOI		https://doi.org/10.1051/bioconf/20249700075
Published online		05 April 2024

Al-mutar, F. H. N., Ucan, O. N., & Ibrahim, A. A. (2022). Providing scalability and privacy for smart contract in the healthcare system. Optik, 271, 170077. https://doi.org/https://doi.org/10.1016/j.ijleo.2022.170077 [CrossRef] [Google Scholar]
Kniep, Q., Kokoris-Kogias, L., Sonnino, A., Zablotchi, I., & Zhang, N. (2024). Pilotfish: Distributed Transaction Execution for Lazy Blockchains. http://arxiv.org/abs/2401.16292 [Google Scholar]
Ahmad, J., Zia, M. U., Naqvi, I. H., Chattha, J. N., Butt, F. A., Huang, T., & Xiang, W. (2024). Machine learning and blockchain technologies for cybersecurity in connected vehicles. WIREs Data Mining and Knowledge Discovery, 14 (1), e1515. https://doi.org/https://doi.org/10.1002/widm.1515 [CrossRef] [Google Scholar]
Chaganti, R., Bhushan, B., & Ravi, V. (2023). A survey on Blockchain solutions in DDoS attacks mitigation: Techniques, open challenges and future directions. Computer Communications, 197, 96–112. https://doi.org/https://doi.org/10.1016/j.comcom.2022.10.026 [CrossRef] [Google Scholar]
Govindan, K., Jain, P., Singh, R. Kr., & Mishra, R. (2024). Blockchain technology as a strategic weapon to bring procurement 4.0 truly alive: Literature review and future research agenda. Transportation Research Part E: Logistics and Transportation Review, 181, 103352. https://doi.org/https://doi.org/10.1016/j.tre.2023.103352 [CrossRef] [Google Scholar]
H R., M. D., Mohan, K. G., Augustine, J., & Patra, G. K. (n.d.). International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING An Approach to Improvise Blockchain Scalability Using Sharding and PBFT. In Original Research Paper International Journal of Intelligent Systems and Applications in Engineering IJISAE (Vol. 2024, Issue 2s). www.ijisae.org [Google Scholar]
Hajian, A., Prybutok, V. R., & Chang, H.-C. (2023). An empirical study for blockchain-based information sharing systems in electronic health records: A mediation perspective. Computers in Human Behavior, 138, 107471. https://doi.org/https://doi.org/10.1016/j.chb.2022.107471 [CrossRef] [Google Scholar]
Hashim, F., Shuaib, K., & Zaki, N. (2022). Sharding for Scalable Blockchain Networks. SN Computer Science, 4 (1), 2. https://doi.org/10.1007/s42979-022-01435-z [CrossRef] [Google Scholar]
Huynh-The, T., Gadekallu, T. R., Wang, W., Yenduri, G., Ranaweera, P., Pham, Q.-V., da Costa, D. B., & Liyanage, M. (2023). Blockchain for the metaverse: A Review. Future Generation Computer Systems, 143, 401–419. https://doi.org/https://doi.org/10.1016/j.future.2023.02.008 [CrossRef] [Google Scholar]
Jia, L., Liu, Y., Wang, K., & Sun, Y. (2024). Estuary: A Low Cross-Shard Blockchain Sharding Protocol Based on State Splitting. IEEE Transactions on Parallel and Distributed Systems, 35(3), 405–420. https://doi.org/10.1109/TPDS.2024.3351632 [CrossRef] [Google Scholar]
Kniep, Q., Kokoris-Kogias, L., Sonnino, A., Zablotchi, I., & Zhang, N. (2024). Pilotfish: Distributed Transaction Execution for Lazy Blockchains. http://arxiv.org/abs/2401.16292 [Google Scholar]
Kumar, S., Lim, W. M., Sivarajah, U., & Kaur, J. (2023a). Artificial Intelligence and Blockchain Integration in Business: Trends from a Bibliometric-Content Analysis. Information Systems Frontiers, 25(2), 871–896. https://doi.org/10.1007/s10796-022-10279-0 [PubMed] [Google Scholar]
Kumar, S., Lim, W. M., Sivarajah, U., & Kaur, J. (2023b). Artificial Intelligence and Blockchain Integration in Business: Trends from a Bibliometric-Content Analysis. Information Systems Frontiers, 25(2), 871–896. https://doi.org/10.1007/s10796-022-10279-0 [PubMed] [Google Scholar]
Li, J., Qin, R., Guan, S., Hou, J., & Wang, F.-Y. (2024). Blockchain Intelligence: Intelligent Blockchains for Web 3.0 and Beyond. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 1–10. https://doi.org/10.1109/TSMC.2023.3348449 [Google Scholar]
Li, W., Tian, W., Yan, Z., Li, Z., Gao, J., Wu, F., Liu, J., Chen, W., & Ren, J. (2024). CoralDB: A Collaborative Database for Data Sharing based on Permissioned Blockchain. IEEE Transactions on Mobile Computing, 1–15. https://doi.org/10.1109/TMC.2024.3357499 [Google Scholar]
Luna, M., Fernandez-Vazquez, S., Tereñes Castelao, E., & Arias Fernández, Á. (2024). A blockchainbased approach to the challenges of EU’s environmental policy compliance in aquaculture: From traceability to fraud prevention. Marine Policy, 159, 105892. https://doi.org/https://doi.org/10.1016/j.marpol.2023.105892 [CrossRef] [Google Scholar]
Malik, N., Wei, Y. “Max,” Appel, G., & Luo, L. (2023a). Blockchain technology for creative industries: Current state and research opportunities. International Journal of Research in Marketing, 40(1), 38–48. https://doi.org/https://doi.org/10.1016/j.ijresmar.2022.07.004 [CrossRef] [Google Scholar]
Malik, N., Wei, Y. “Max,” Appel, G., & Luo, L. (2023b). Blockchain technology for creative industries: Current state and research opportunities. International Journal of Research in Marketing, 40(1), 38–48. https://doi.org/https://doi.org/10.1016/j.ijresmar.2022.07.004 [CrossRef] [Google Scholar]
Matani, A., Sahafi, A., & Broumandnia, A. (2024). Journal of Electrical and Computer Engineering Innovations A Comprehensive Review on Blockchain Scalability. J. Electr. Comput. Eng. Innovations, 12(1), 187–216. https://doi.org/10.22061/jecei.2023.9975.670 [Google Scholar]
Miao, J., Wang, Z., Wu, Z., Ning, X., & Tiwari, P. (2024). A blockchain-enabled privacy-preserving authentication management protocol for Internet of Medical Things. Expert Systems with Applications, 237, 121329. https://doi.org/https://doi.org/10.1016/j.eswa.2023.121329 [CrossRef] [Google Scholar]
Peres, R., Schreier, M., Schweidel, D. A., & Sorescu, A. (2023). Blockchain meets marketing: Opportunities, threats, and avenues for future research. International Journal of Research in Marketing, 40(1), 1–11. https://doi.Org/https://doi.org/10.1016/j.ijresmar.2022.08.001 [CrossRef] [Google Scholar]
Piduguralla, M., Sarkar, S., & Peri, S. (2024). Improving Throughput and Fault Tolerance of Blockchain Nodes. Proceedings of the 25th International Conference on Distributed Computing and Networking, 256–257. https://doi.org/10.1145/3631461.3632509 [Google Scholar]
Singh, A., Gutub, A., Nayyar, A., & Khan, M. K. (2023). Redefining food safety traceability system through blockchain: findings, challenges and open issues. Multimedia Tools and Applications, 82(14), 21243–21277. https://doi.org/10.1007/s11042-022-14006-4 [CrossRef] [PubMed] [Google Scholar]
Taherdoost, H. (2023). Smart Contracts in Blockchain Technology: A Critical Review. Information, 14(2). https://doi.org/10.3390/info14020117 [PubMed] [Google Scholar]
Tian, J., Xu, H., & Tian, J. (2024). SLChain: A secure and low-storage pressure sharding blockchain. Concurrency and Computation: Practice and Experience, 36 (3), e7918. https://doi.org/https://doi.org/10.1002/cpe.7918 [CrossRef] [Google Scholar]
Wang, X., Zhu, H., Ning, Z., Guo, L., & Zhang, Y. (2023). Blockchain Intelligence for Internet of Vehicles: Challenges and Solutions. IEEE Communications Surveys & Tutorials, 25(4), 2325–2355. https://doi.org/10.1109/COMST.2023.3305312 [CrossRef] [Google Scholar]
Winter, S., & Zimmermann, M. (n.d.). Weak Muller Conditions Make Delay Games Hard. In Aspects of Computation and Automata Theory with Applications (pp. 425–464). https://doi.org/10.1142/9789811278631_0016 [Google Scholar]
Xu, J., Wang, C., & Jia, X. (2023). A Survey of Blockchain Consensus Protocols. ACM Comput. Surv., 55(13s). https://doi.org/10.1145/3579845 [Google Scholar]
Yavaprabhas, K., Pournader, M., & Seuring, S. (2023). Blockchain as the “trust-building machine” for supply chain management. Annals of Operations Research, 327(1), 49–88. https://doi.org/10.1007/s10479-022-04868-0 [CrossRef] [Google Scholar]
Zhen, Z., Wang, X., Lin, H., Garg, S., Kumar, P., & Hossain, M. S. (2024). A dynamic state sharding blockchain architecture for scalable and secure crowdsourcing systems. Journal of Network and Computer Applications, 222, 103785. https://doi.org/https://doi.org/10.1016/j.jnca.2023.103785 [CrossRef] [Google Scholar]
Zhen, Z., Wang, X., Lin, H., Garg, S., Kumar, P., & Hossain, M. S. (2024). A dynamic state sharding blockchain architecture for scalable and secure crowdsourcing systems. Journal of Network and Computer Applications, 222. https://doi.org/10.1016/j.jnca.2023.103785. [Google Scholar]
Martinez, K. K. C. (2023). Blockchain Scalability Solved via Quintessential Parallel Multiprocessor. 2023 International Wireless Communications and Mobile Computing, IWCMC 2023, 1626–1631. https://doi.org/10.1109/IWCMC58020.2023.10183268. [CrossRef] [Google Scholar]
Zhang, Q., Wang, S., Zhang, D., Wang, J., & Sun, J. (2023). FortunChain: EC-VRF-Based Scalable Blockchain System for Realizing State Sharding. IEEE Transactions on Network and Service Management, 20(4), 4340–4353. https://doi.org/10.1109/TNSM.2023.3277833 [CrossRef] [Google Scholar]
Li, M., Wang, W., & Zhang, J. (2023). LB-Chain: Load-Balanced and Low-Latency Blockchain Sharding via Account Migration. IEEE Transactions on Parallel and Distributed Systems, 34(10), 2797–2810. https://doi.org/10.1109/TPDS.2023.3238343. [CrossRef] [Google Scholar]
Khacef, K., Benbernou, S., Ouziri, M., & Younas, M. (2023). A Dynamic Sharding Model Aware Security and Scalability in Blockchain. Information Systems Frontiers. https://doi.org/10.1007/s10796-023-10380-y. [Google Scholar]
Wang, Y., Wang, W., Zeng, Y., & Yang, T. (2023). GradingShard: A new sharding protocol to improve blockchain throughput. Peer-to-Peer Networking and Applications, 16(3), 1327–1339. https://doi.org/10.1007/s12083-023-01466-0. [CrossRef] [Google Scholar]
Zhang, P., Guo, W., Liu, Z., Zhou, M., Huang, B., & Sedraoui, K. (2023). Optimized Blockchain Sharding Model Based on Node Trust and Allocation. IEEE Transactions on Network and Service Management, 20(3), 2804–2816. https://doi.org/10.1109/TNSM.2022.3233570 [CrossRef] [Google Scholar]

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