Exploring the Mechanisms of Efficiency and Scalability in Blockchain: A Qualitative Study of Distributed Ledger Algorithms in Decentralized Networks in Bintan, Riau Islands
DOI:
https://doi.org/10.58812/wsist.v4i02.3046Keywords:
Blockchain, Consensus Mechanism, Distributed Ledger, Efficiency, Scalability, DAG, HashgraphAbstract
Blockchain consensus mechanisms are critical for ensuring security, efficiency, and scalability in decentralized networks. This study qualitatively examines ten widely used consensus algorithms—Proof of Work (PoW), Proof of Stake (PoS), Delegated PoS (DPoS), PBFT, Raft, Proof of Authority (PoA), Hybrid PoW/PoS, DAG/IOTA, Hashgraph, and Tendermint—within the research context of Bintan, Riau Islands, Indonesia. Performance was evaluated through literature review and simulated network observations, focusing on transaction throughput (TPS), latency, energy consumption, and network stability. Results indicate that DAG/IOTA and Hashgraph achieve the highest throughput with minimal latency, making them suitable for IoT and enterprise-scale applications. PoS and PoA offer energy-efficient alternatives, while PoW provides high security at the cost of high energy usage. Hybrid PoW/PoS demonstrates balanced performance across multiple metrics. Qualitative analysis highlights trade-offs among energy efficiency, throughput, latency, and decentralization. These findings provide practical guidance for selecting consensus mechanisms according to network requirements, operational constraints, and sustainability considerations, contributing a consolidated perspective on blockchain efficiency and scalability.
References
[1] L. Chen, T., Wang, H., & Zhou, “Scalability challenges in blockchain networks: Solutions and trade-offs. Computer Networks,” vol. 214, pp. 109–124, 2023.
[2] Y. Chen, L., & Xu, “DAG/IOTA scalability assessment for IoT ecosystems,” IEEE Internet Things J., vol. 12, no. 4, pp. 500–514, 2025.
[3] K. Brown, T., & White, “Performance benchmarking of Hashgraph for enterprise deployments,” J. Enterp. Inf. Syst., vol. 19, no. 3, pp. 220–236, 2025.
[4] Y. Huang, K., & Lin, “Performance evaluation of Tendermint consensus in smart contract deployment.,” J. Syst. Archit., vol. 125, pp. 102–118, 2023.
[5] A. Gupta, S., & Verma, “Energy consumption analysis of blockchain consensus mechanisms.,” Sustain. Comput. Informatics Syst., vol. 38, pp. 101–115, 2024.
[6] M. Davis, L., & Anderson, “Hybrid consensus in blockchain networks: Balancing security and efficiency,” IEEE Access, vol. 12, pp. 3350–3365, 2024.
[7] S. Kim, Y., & Park, “Private blockchain protocols: PBFT and Raft performance review.,” Int. J. Inf. Secur., vol. 24, no. 1, pp. 55–70, 2025.
[8] P. Kumar, A., & Sharma, “Evaluating energy efficiency and scalability in modern blockchain networks.,” Int. J. Distrib. Ledger Res., vol. 11, no. 1, pp. 33–50, 2026.
[9] A. Kumar, R., & Singh, “Proof-of-stake versus proof-of-work: A comparative analysis.,” J. Blockchain Res., vol. 5, no. 1, pp. 33–47, 2022.
[10] S. Nakamoto, “Blockchain: A peer-to-peer electronic cash system,” 2018-11-01).[2021-02-25]. https://www. bitcoin. org. 2008.
[11] B. L. T. Setiawan and J. Jonathan, “THE ROLE OF BLOCKCHAIN TECHNOLOGY IN ENHANCING TRACEABILITY AND VISIBILITY ACROSS DISPERSED GLOBAL SUPPLY CHAIN NETWORKS,” LOGIS (Logistics, Oper. Glob. Integr. Stud., vol. 1, no. 2, pp. 68–79, 2025.
[12] V. Patel, S., & Kumar, “Delegated proof-of-stake: Mechanism, risks, and performance.,” Int. J. Distrib. Syst., vol. 9, no. 4, pp. 210–225, 2023.
[13] D. Patel, R., & Singh, “Energy-aware blockchain design for sustainable networks.,” Sustain. Comput. Informatics Syst., vol. 41, pp. 112–128, 2026.
[14] J. Liu, X., & Yang, “Consensus selection framework for efficient blockchain networks.,” ACM Comput. Surv., vol. 59, no. 2, pp. 1–29, 2026.
[15] M. Li, Q., & Zhao, “Hashgraph consensus: High-throughput applications and limitations.,” 2023, vol. 18, no. 2, pp. 77–92.
[16] J. Lee, S., & Kim, “Latency optimization in high-frequency blockchain applications.,” J. Syst. Softw., vol. 203, pp. 110–125, 2026.
[17] P. Zhao, L., & Sun, “Proof-of-authority networks: Efficiency and security analysis,” J. Netw. Comput. Appl., vol. 205, pp. 103–118, 2025.
[18] J. Zhang, Y., & Li, “Energy-efficient consensus algorithms for public blockchains.,” IEEE Trans. Sustain. Comput., vol. 7, no. 2, pp. 150–162, 2022.
[19] W. Zhang, J., & Chen, “Qualitative insights into blockchain performance trade-offs.,” J. Blockchain Stud., vol. 6, no. 2, pp. 89–104, 2026.
[20] F. Zhang, H., & Li, “Comparative study of PoW, PoS, and DPoS under high transaction loads.,” J. Parallel Distrib. Comput., vol. 167, pp. 48–62, 2024.
[21] X. Wang, J., & Chen, “Scalability and throughput optimization in distributed ledger technologies.,” Futur. Gener. Comput. Syst., vol. 140, pp. 456–471, 2024.
[22] Q. Wang, H., & Li, “Comparative analysis of distributed ledger algorithms in decentralized finance.,” Financ. Technol. Rev., vol. 8, no. 1, pp. 45–62, 2026.
[23] P. Smith, J., & Brown, “DAG-based blockchain frameworks for IoT microtransactions.,” Sensors, vol. 23, no. 5, p. 1892, 2023.
[24] V. Singh, R., & Sharma, “Throughput and latency trade-offs in blockchain consensus algorithms.,” Blockchain Res. Appl., vol. 7, no. 2, pp. 77–92, 2025.
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Copyright (c) 2026 Dodi Setiawan, Sri Sutjiningtyas, A. Eka Hermia Fitrianingsy, Ronald Naibaho, Yusup Ridwan

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