This article explains the Byzantine Generals Problem, showing why 3 generals cannot tolerate 1 traitor, proving the N ≥ 3m+1 bound, contrasting oral vs signed messages, providing a Java simulation, comparing crash vs Byzantine fault tolerance, and offering an interview answer template.
This article explains the challenges of distributed consistency in decentralized environments and provides an in‑depth overview of classic consensus algorithms such as PBFT, Proof‑of‑Work, and Proof‑of‑Stake, including their mechanisms, limitations, and suitable application scenarios.
This article explains the CAP theorem, illustrates the Byzantine Generals problem, and provides detailed overviews of PBFT, Paxos (including Multi‑Paxos), and Raft consensus algorithms, highlighting their phases, roles, and practical considerations for achieving consistency in distributed systems.
This article explains how to augment Hyperledger Fabric's orderer service by integrating Tendermint's ABCI to implement a PBFT consensus mechanism, detailing the limitations of solo and Kafka ordering, the motivation for decentralized ordering, and the step‑by‑step implementation approach.
The article compares Raft, a crash‑only consensus used in private blockchains with leader election and O(N) communication, to PBFT, a Byzantine‑tolerant protocol for consortium chains that requires 3f+1 nodes, uses three‑phase messaging, O(N²) complexity, and different fault‑tolerance limits.
This article explains the fundamentals of Raft and PBFT consensus algorithms, compares their processes, fault tolerance limits, and suitability for private and consortium blockchains, and highlights key differences in leader election, message handling, and fault models.
