Collaborator(s): Prof. Show-Shiow Tzeng, Prof. Li-Chun Wang
This research focuses on distributed consensus mechanisms and explores how proposal quality evaluation and reputation-based leader selection can improve the decision quality and operational efficiency of PBFT-based protocols. It also analyzes and mitigates safety and liveness issues arising from low-quality proposals, collisions, and livelocks.
| [C02] | W.A. Prabowo, S.W. Wang, S.S. Tzeng, and L.C. Wang, "Collision and Livelock: Primary Selection Failures in Reputation-Based PBFT with Inconsistent Scores," in 2026 IEEE Global Communication Conference (Globecom 2026), Macau S.A.R., China, December 7-11, 2026. |
| [C01] | S.W. Wang, W.L. Chen, and S.S. Tzeng, "VLQ Attack: Valid-but-Low-Quality Proposals in PBFT-Based MIS Agreement over Transaction Conflict Graphs in Permissioned Blockchains," in 2026 IEEE Global Communication Conference (Globecom 2026), Macau S.A.R., China, December 7-11, 2026. |
| [S02] | W.A. Prabowo, S.W. Wang, S.H. Cheng, and L.C. Wang, "SHIELD-MCPS: Intelligent, Fair, and Adaptive Leader Selection for Byzantine Fault-Tolerant Consensus in Permissioned Blockchains," under review by IEEE Transactions on Network Science and Engineering, (Last update: 2026-08-22 Revising after Revise and Resubmit ) |
| [S01] | S.W. Wang, S.S. Tzeng, and W.L. Chen, "QE-X-PBFT: Bridging the Validity-Quality Gap in Byzantine Consensus for Permissioned Blockchains," under review by IEEE Transactions on Parallel and Distributed Systems, (Last update: 2026-08-01 Under review in 1st round ) |
| [R01] | Anonymous, "Accelerating Federated Learning Convergence in Blockchains via Quality-Aware PBFT ConsensusAccelerating Federated Learning Convergence in Permissioned Blockchains with Byzantine Primaries," preparing for IEEE ICC 2027 CISS Symposium. |