Phase 42.1 — ConsensusEngine: Raft/Paxos Consensus & Byzantine Fault Tolerance

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Phase 42.1 — ConsensusEngine

Overview

The ConsensusEngine implements distributed consensus protocols for ASI-Build's multi-node AI infrastructure. It provides Raft-based log replication, Paxos-based agreement, and PBFT extensions for Byzantine fault tolerance, ensuring all nodes agree on model state, training progress, and configuration changes.

Academic Foundation

• Lamport (1998) — Paxos: the foundational consensus algorithm for crash-tolerant distributed systems
• Ongaro & Ousterhout (2014) — Raft: an understandable consensus algorithm with strong leader, log replication, and membership changes
• Castro & Liskov (1999) — PBFT: practical Byzantine fault tolerance tolerating f < n/3 Byzantine nodes
• Fischer, Lynch & Paterson (1985) — FLP impossibility: no deterministic consensus in async systems with even one crash failure

Architecture

ConsensusEngine
├── RaftConsensus
│   ├── LeaderElection          # Randomized timeouts, term management
│   ├── LogReplicator           # AppendEntries RPC, commit index tracking
│   ├── MembershipManager       # Joint consensus for config changes
│   └── SnapshotCompactor       # Log compaction via snapshots
├── PaxosConsensus
│   ├── Proposer                # Prepare/Accept phase management
│   ├── Acceptor                # Promise/Accept state machine
│   ├── Learner                 # Value learning and dissemination
│   └── MultiPaxos              # Leader-based optimization for repeated consensus
├── ByzantineConsensus
│   ├── PBFTEngine              # Pre-prepare/Prepare/Commit protocol
│   ├── ViewChanger             # View change on leader failure
│   ├── MessageAuthenticator    # MAC-based message authentication
│   └── CheckpointProtocol      # Periodic state checkpoints for garbage collection
├── ModelAgreement
│   ├── GradientConsensus       # Agree on gradient updates across nodes
│   ├── ParameterSync           # Synchronized parameter server protocol
│   └── VersionVector           # Causal ordering of model versions
└── ConsensusMetrics
    ├── LatencyTracker          # Consensus round latency monitoring
    ├── ThroughputMeter         # Operations per second measurement
    └── SafetyVerifier          # Invariant checking (single leader, log matching)

Interface Specification

from dataclasses import dataclass, field
from enum import Enum
from typing import Any, Optional, Callable
import asyncio


class ConsensusProtocol(Enum):
    RAFT = "raft"
    PAXOS = "paxos"
    PBFT = "pbft"
    MULTI_PAXOS = "multi_paxos"


class NodeState(Enum):
    FOLLOWER = "follower"
    CANDIDATE = "candidate"
    LEADER = "leader"


@dataclass
class LogEntry:
    term: int
    index: int
    command: Any
    timestamp: float
    client_id: str


@dataclass
class ConsensusConfig:
    protocol: ConsensusProtocol = ConsensusProtocol.RAFT
    cluster_size: int = 5
    election_timeout_ms: tuple = (150, 300)  # min, max randomized
    heartbeat_interval_ms: int = 50
    max_log_entries_per_append: int = 100
    snapshot_threshold: int = 10000
    byzantine_tolerance: bool = False
    max_byzantine_nodes: int = 1  # f < n/3


class ConsensusEngine:
    """
    Distributed consensus engine supporting Raft, Paxos, and PBFT protocols.
    
    Provides strong consistency guarantees for distributed AI model state,
    training coordination, and configuration management.
    """
    
    def __init__(self, config: ConsensusConfig):
        self.config = config
        self.state = NodeState.FOLLOWER
        self.current_term = 0
        self.voted_for = None
        self.log: list[LogEntry] = []
        self.commit_index = 0
        self.last_applied = 0
        
    async def start_node(self, node_id: str, peers: list[str]) -> None:
        """Initialize and start the consensus node."""
        ...
    
    async def propose(self, command: Any, client_id: str) -> LogEntry:
        """Propose a new command to the consensus group. Only leader can accept proposals."""
        ...
    
    async def request_vote(self, candidate_id: str, term: int, 
                           last_log_index: int, last_log_term: int) -> tuple[int, bool]:
        """Handle RequestVote RPC (Raft) or Prepare (Paxos)."""
        ...
    
    async def append_entries(self, leader_id: str, term: int, 
                             prev_log_index: int, prev_log_term: int,
                             entries: list[LogEntry], leader_commit: int) -> tuple[int, bool]:
        """Handle AppendEntries RPC for log replication."""
        ...
    
    async def get_leader(self) -> Optional[str]:
        """Return current leader node ID, None if no leader elected."""
        ...
    
    async def add_node(self, node_id: str) -> bool:
        """Add a new node via joint consensus (Raft) or reconfiguration."""
        ...
    
    async def remove_node(self, node_id: str) -> bool:
        """Remove a node from the consensus group."""
        ...
    
    async def create_snapshot(self) -> bytes:
        """Create a state snapshot for log compaction."""
        ...
    
    def get_metrics(self) -> dict:
        """Return consensus performance metrics."""
        ...

Testing Requirements

class TestConsensusEngine:
    async def test_leader_election_single_candidate(self): ...
    async def test_leader_election_split_vote(self): ...
    async def test_log_replication_basic(self): ...
    async def test_log_replication_with_follower_lag(self): ...
    async def test_leader_failure_and_reelection(self): ...
    async def test_network_partition_minority_cannot_commit(self): ...
    async def test_network_partition_majority_continues(self): ...
    async def test_byzantine_node_detection(self): ...
    async def test_pbft_3f_plus_1_tolerance(self): ...
    async def test_snapshot_compaction(self): ...
    async def test_membership_change_joint_consensus(self): ...
    async def test_gradient_consensus_convergence(self): ...
    async def test_causal_ordering_version_vectors(self): ...
    async def test_concurrent_proposals_linearizability(self): ...

Acceptance Criteria

• Raft leader election with randomized timeouts completes within 2× election timeout
• Log replication achieves linearizable consistency across 5-node cluster
• PBFT tolerates f < n/3 Byzantine nodes with safety and liveness
• Snapshot compaction reduces log size by >90% after threshold
• Gradient consensus converges within 10 rounds for typical model updates
• Network partition handling: majority partition continues, minority becomes read-only
• Joint consensus membership changes maintain safety during transitions

Dependencies

• Phase 38 (Federated Learning) — FederatedAggregator for aggregation patterns
• Phase 41 (Adversarial Robustness) — Byzantine detection techniques

References

• Raft Paper
• PBFT Paper
• FLP Impossibility
• Planning: Phase 42 Planning — Distributed Systems & Fault-Tolerant AI Infrastructure #840