Distributed Agreements Algorithms

In the Distributed Agreement Algorithms section, the focus will be on the mechanisms that allow distributed systems to reach consensus, even in the presence of faulty or malicious nodes. This section will cover:

• HoneyBadgerBFT: A Byzantine Fault Tolerant (BFT) protocol designed for asynchronous networks. It will discuss how HoneyBadgerBFT achieves agreement in a decentralized and permissionless environment, with a focus on its robustness against attacks and its use in blockchain and distributed ledger technologies.

• Byzantine General Problem (BGP): The classical problem that lays the foundation for BFT protocols. You’ll describe the theoretical challenge of reaching consensus in a system with potentially malicious actors and how this problem informs modern distributed consensus protocols.

• Practical Byzantine Fault Tolerance (PBFT): A widely-used consensus algorithm that solves the Byzantine General Problem under practical network assumptions. This section will explore how PBFT achieves high performance in partially synchronous networks and its applications in enterprise-level blockchains.

• Delegated Byzantine Fault Tolerance (DBFT): Used primarily in networks like NEO, this algorithm optimizes PBFT by introducing delegation, allowing a group of nodes to reach consensus on behalf of others. The section will cover how DBFT reduces communication overhead and improves efficiency.

• Federated Byzantine Fault Tolerance (FBFT): This consensus mechanism, used by Stellar, introduces a federated voting system to achieve agreement among nodes. You’ll cover how FBFT enhances scalability and decentralization by using quorum slices.

While Raft and Paxos are typically consensus algorithms, they will be covered in the Data Replication section, as they are used both for reaching agreements and ensuring data replication across nodes, showcasing their dual functionality in Golang implementations.