LP-8504: Sequencer Registry Protocol

Abstract

This LP defines a decentralized sequencer registry protocol for L2 rollups on Lux Network, implementing stake-based selection, rotation mechanisms, and performance monitoring. The system enables permissionless sequencer participation with economic incentives, supports multiple sequencer selection strategies including round-robin, weighted random, and auction-based models, and provides specialized mechanisms for AI workload scheduling and distributed training coordination. The protocol ensures liveness, censorship resistance, and fair transaction ordering through cryptographic commitments and threshold decryption.

Activation

Parameter	Value
Flag string	`lp504-sequencer-registry`
Default in code	false until block X
Deployment branch	`v0.0.0-lp504`
Roll‑out criteria	10+ active sequencers
Back‑off plan	Fallback to L1 sequencing

Motivation

Centralized sequencers present critical risks:

Single Point of Failure: Downtime affects entire L2
Censorship Risk: Can exclude transactions arbitrarily
MEV Extraction: Unfair value extraction from users
Trust Requirements: Users must trust sequencer operator
Limited Scalability: Single sequencer bottlenecks throughput

Decentralized sequencing enables:

Liveness Guarantees: Multiple sequencers ensure availability
Censorship Resistance: Transactions eventually included
Fair Ordering: Cryptographic mechanisms prevent manipulation
Horizontal Scaling: Multiple sequencers increase throughput
Specialized Scheduling: AI workloads get appropriate resources

Specification

Core Registry Interface

interface ISequencerRegistry {
    enum SequencerStatus {
        Inactive,
        Active,
        Suspended,
        Ejected,
        Exiting
    }

    enum SelectionMode {
        RoundRobin,
        WeightedRandom,
        Auction,
        Performance,
        Hybrid
    }

    struct SequencerInfo {
        address operator;
        string endpoint;              // P2P endpoint
        bytes publicKey;             // For encrypted mempool
        uint256 stake;
        uint256 delegatedStake;
        SequencerStatus status;
        uint256 activationBlock;
        uint256 lastActiveBlock;
        uint256 performanceScore;
        bytes metadata;              // Additional config
    }

    struct RegistryConfig {
        uint256 minStake;
        uint256 maxSequencers;
        uint256 rotationPeriod;      // Blocks per rotation
        uint256 exitDelay;           // Delay before stake withdrawal
        SelectionMode selectionMode;
        uint256 slashingPercentage;
    }

    // Registration and staking
    function registerSequencer(
        string calldata endpoint,
        bytes calldata publicKey,
        bytes calldata metadata
    ) external payable returns (uint256 sequencerId);

    function increaseStake(uint256 sequencerId) external payable;
    function delegateStake(uint256 sequencerId) external payable;
    function initiateExit(uint256 sequencerId) external;
    function completeExit(uint256 sequencerId) external;

    // Selection and rotation
    function selectNextSequencer() external returns (address);
    function rotateSequencer() external;
    function getActiveSequencer() external view returns (address);
    function getSequencerSet() external view returns (address[] memory);

    // Performance and slashing
    function updatePerformance(uint256 sequencerId, uint256 score) external;
    function reportMisbehavior(uint256 sequencerId, bytes calldata evidence) external;
    function slash(uint256 sequencerId, uint256 amount) external;

    // Events
    event SequencerRegistered(uint256 indexed sequencerId, address operator);
    event SequencerRotated(address indexed oldSequencer, address indexed newSequencer);
    event SequencerSlashed(uint256 indexed sequencerId, uint256 amount);
    event StakeDelegated(uint256 indexed sequencerId, address delegator, uint256 amount);
}

Selection Mechanisms

interface ISequencerSelection {
    struct RoundRobinState {
        uint256 currentIndex;
        address[] sequencers;
        uint256 lastRotation;
    }

    struct WeightedRandomState {
        uint256 totalStake;
        uint256 seed;
        mapping(address => uint256) weights;
    }

    struct AuctionState {
        uint256 currentRound;
        address highestBidder;
        uint256 highestBid;
        uint256 auctionEnd;
        mapping(address => uint256) bids;
    }

    struct PerformanceBasedState {
        mapping(address => uint256) scores;
        uint256 scoreDecayRate;
        uint256 minScore;
    }

    // Round-robin selection
    function selectRoundRobin(
        RoundRobinState storage state
    ) external returns (address);

    // Weighted random selection
    function selectWeightedRandom(
        WeightedRandomState storage state,
        uint256 blockHash
    ) external returns (address);

    // Auction-based selection
    function initAuction(
        uint256 duration
    ) external returns (uint256 auctionId);

    function placeBid(
        uint256 auctionId
    ) external payable;

    function finalizeAuction(
        uint256 auctionId
    ) external returns (address winner);

    // Performance-based selection
    function selectByPerformance(
        PerformanceBasedState storage state
    ) external returns (address);

    // Hybrid selection (combines multiple methods)
    function selectHybrid(
        uint256[] calldata weights,  // Weight for each method
        bytes calldata params
    ) external returns (address);

    // VRF for randomness
    function requestRandomness() external returns (uint256 requestId);
    function fulfillRandomness(uint256 requestId, uint256 randomness) external;
}

MEV Mitigation

interface IMEVMitigation {
    struct EncryptedTransaction {
        bytes encryptedData;
        bytes32 commitment;          // Hash of plaintext
        uint256 revealDeadline;
        address sender;
    }

    struct ThresholdDecryption {
        uint256 threshold;           // Min validators for decryption
        address[] validators;
        mapping(address => bytes) keyShares;
    }

    struct TimelockedTransaction {
        bytes32 txHash;
        uint256 unlockTime;
        bytes encryptedTx;
        bytes timeProof;             // VDF proof
    }

    // Threshold encryption for mempool
    function submitEncrypted(
        bytes calldata encryptedTx,
        bytes32 commitment
    ) external returns (bytes32 txId);

    function revealTransaction(
        bytes32 txId,
        bytes calldata plaintext,
        uint256 nonce
    ) external;

    // Threshold decryption
    function initThresholdDecryption(
        uint256 threshold,
        address[] calldata validators
    ) external;

    function submitKeyShare(
        bytes32 txId,
        bytes calldata keyShare
    ) external;

    function decryptTransaction(
        bytes32 txId
    ) external returns (bytes memory);

    // Time-locked transactions
    function submitTimelocked(
        bytes calldata encryptedTx,
        uint256 lockDuration
    ) external returns (bytes32);

    function proveTimeElapsed(
        bytes32 txId,
        bytes calldata vdfProof
    ) external;

    // Fair ordering
    function determineFairOrder(
        bytes32[] calldata txHashes,
        uint256 blockNumber
    ) external pure returns (bytes32[] memory);

    // Events
    event EncryptedTxSubmitted(bytes32 indexed txId, address sender);
    event TransactionRevealed(bytes32 indexed txId);
    event ThresholdDecrypted(bytes32 indexed txId);
}

AI Workload Scheduling

interface IAIWorkloadScheduler {
    struct ComputeJob {
        bytes32 jobId;
        uint256 requiredFlops;
        uint256 memoryRequirement;
        uint256 deadline;
        uint256 priority;
        address requester;
        bytes jobSpec;
    }

    struct SequencerCapabilities {
        uint256 sequencerId;
        uint256 availableFlops;
        uint256 availableMemory;
        uint256 networkBandwidth;
        string[] supportedModels;
        bool hasTEE;
        bool hasGPU;
    }

    struct SchedulingPolicy {
        enum PolicyType { FIFO, Priority, SJF, RoundRobin, Fair }
        PolicyType policyType;
        bytes policyParams;
    }

    // Job submission
    function submitComputeJob(
        ComputeJob calldata job
    ) external returns (bytes32);

    function cancelJob(bytes32 jobId) external;

    // Sequencer capabilities
    function registerCapabilities(
        uint256 sequencerId,
        SequencerCapabilities calldata capabilities
    ) external;

    function updateCapabilities(
        uint256 sequencerId,
        SequencerCapabilities calldata capabilities
    ) external;

    // Scheduling
    function scheduleJob(
        bytes32 jobId,
        uint256 sequencerId
    ) external returns (bool);

    function getOptimalSequencer(
        ComputeJob calldata job
    ) external view returns (uint256);

    function rebalanceWorkload() external;

    // Load balancing
    function getSequencerLoad(uint256 sequencerId) external view returns (uint256);
    function migrateJob(bytes32 jobId, uint256 newSequencerId) external;

    // Priority management
    function boostPriority(bytes32 jobId, uint256 amount) external payable;
    function preemptJob(bytes32 lowPriorityJob, bytes32 highPriorityJob) external;

    // Events
    event JobScheduled(bytes32 indexed jobId, uint256 sequencerId);
    event JobCompleted(bytes32 indexed jobId, uint256 gasUsed);
    event WorkloadRebalanced(uint256 numMigrations);
}

Distributed Training Coordination

interface ITrainingCoordination {
    struct TrainingCluster {
        bytes32 clusterId;
        uint256[] sequencerIds;
        address coordinator;
        bytes32 modelHash;
        uint256 totalEpochs;
        uint256 currentEpoch;
    }

    struct DataShard {
        bytes32 shardId;
        uint256 sequencerId;
        bytes32 dataHash;
        uint256 numSamples;
        uint256 startIndex;
        uint256 endIndex;
    }

    struct GradientUpdate {
        bytes32 clusterId;
        uint256 sequencerId;
        uint256 epoch;
        bytes32 gradientHash;
        uint256 loss;
        uint256 timestamp;
    }

    // Cluster management
    function createTrainingCluster(
        uint256[] calldata sequencerIds,
        bytes32 modelHash
    ) external returns (bytes32 clusterId);

    function joinCluster(bytes32 clusterId, uint256 sequencerId) external;
    function leaveCluster(bytes32 clusterId, uint256 sequencerId) external;

    // Data distribution
    function assignDataShard(
        bytes32 clusterId,
        uint256 sequencerId,
        DataShard calldata shard
    ) external;

    function replicateShard(
        bytes32 shardId,
        uint256 targetSequencer
    ) external;

    // Synchronization
    function submitGradient(
        GradientUpdate calldata update
    ) external;

    function aggregateGradients(
        bytes32 clusterId,
        uint256 epoch
    ) external returns (bytes32 aggregatedHash);

    function broadcastWeights(
        bytes32 clusterId,
        bytes32 weightsHash
    ) external;

    // Fault tolerance
    function reportFailure(
        bytes32 clusterId,
        uint256 failedSequencer
    ) external;

    function reassignWork(
        bytes32 clusterId,
        uint256 failedSequencer,
        uint256 newSequencer
    ) external;

    // Checkpointing
    function saveCheckpoint(
        bytes32 clusterId,
        uint256 epoch,
        bytes32 stateHash
    ) external;

    function restoreFromCheckpoint(
        bytes32 clusterId,
        uint256 checkpointEpoch
    ) external;

    // Events
    event ClusterCreated(bytes32 indexed clusterId, uint256 numSequencers);
    event GradientSubmitted(bytes32 indexed clusterId, uint256 epoch, uint256 sequencerId);
    event WeightsBroadcast(bytes32 indexed clusterId, bytes32 weightsHash);
}

Performance Monitoring

interface IPerformanceMonitor {
    struct PerformanceMetrics {
        uint256 blocksProduced;
        uint256 transactionsProcessed;
        uint256 avgBlockTime;
        uint256 avgGasUsed;
        uint256 uptime;              // Percentage (basis points)
        uint256 missedSlots;
        uint256 reorgCount;
        uint256 latency;             // Average in ms
    }

    struct QualityScore {
        uint256 throughput;          // TPS
        uint256 availability;        // Uptime percentage
        uint256 correctness;         // Valid blocks percentage
        uint256 timeliness;          // On-time block production
        uint256 overall;             // Weighted average
    }

    struct SLAConfig {
        uint256 minThroughput;       // Minimum TPS
        uint256 minUptime;           // Minimum uptime (basis points)
        uint256 maxLatency;          // Maximum latency (ms)
        uint256 maxMissedSlots;      // Per epoch
    }

    // Metrics collection
    function recordBlockProduction(
        uint256 sequencerId,
        uint256 blockNumber,
        uint256 gasUsed,
        uint256 txCount
    ) external;

    function recordMissedSlot(uint256 sequencerId, uint256 slot) external;
    function recordReorg(uint256 sequencerId, uint256 depth) external;

    // Score calculation
    function calculateQualityScore(
        uint256 sequencerId
    ) external view returns (QualityScore memory);

    function getPerformanceMetrics(
        uint256 sequencerId,
        uint256 period
    ) external view returns (PerformanceMetrics memory);

    // SLA enforcement
    function checkSLACompliance(
        uint256 sequencerId,
        SLAConfig calldata sla
    ) external view returns (bool compliant, bytes memory violations);

    function penalizeSLAViolation(
        uint256 sequencerId,
        bytes calldata violations
    ) external;

    // Reputation system
    function updateReputation(uint256 sequencerId, int256 change) external;
    function getReputation(uint256 sequencerId) external view returns (uint256);

    // Events
    event MetricsRecorded(uint256 indexed sequencerId, uint256 blockNumber);
    event SLAViolation(uint256 indexed sequencerId, bytes violations);
    event ReputationUpdated(uint256 indexed sequencerId, uint256 newScore);
}

Rationale

Selection Mechanism Design

Multiple selection modes for different requirements:

Round-Robin: Simple, predictable, fair distribution
Weighted Random: Stake-proportional, Sybil-resistant
Auction: Market-driven, revenue-generating
Performance: Merit-based, incentivizes quality
Hybrid: Combines benefits of multiple approaches

MEV Mitigation Strategies

Following Flashbots and Chainlink FSS research:

Threshold Encryption: Transactions hidden until ordering determined
Time-lock Puzzles: VDF-based commit-reveal schemes
Fair Ordering: Deterministic ordering via consensus

AI Workload Optimization

Specialized scheduling for AI workloads:

Resource Matching: Match jobs to capable sequencers
Priority Scheduling: Deadline-aware scheduling
Load Balancing: Distribute work across cluster
Fault Tolerance: Automatic failover and recovery

Backwards Compatibility

Compatible with existing L2 designs:

Optional decentralization (can start centralized)
Gradual migration path
Fallback to L1 sequencing if needed
Standard interfaces for integration

Test Cases

Registry Operations

describe("Sequencer Registry", () => {
    it("should register sequencer with stake", async () => {
        const stake = ethers.parseEther("100000"); // 100k LUX

        await registry.registerSequencer(
            "enode://[email protected]:30303",
            publicKey,
            metadata,
            { value: stake }
        );

        const info = await registry.getSequencer(1);
        expect(info.stake).to.equal(stake);
        expect(info.status).to.equal(SequencerStatus.Active);
    });

    it("should rotate sequencers based on period", async () => {
        // Register multiple sequencers
        for(let i = 0; i < 5; i++) {
            await registerSequencer(accounts[i]);
        }

        const initialSequencer = await registry.getActiveSequencer();

        // Advance time
        await time.increase(rotationPeriod);
        await registry.rotateSequencer();

        const newSequencer = await registry.getActiveSequencer();
        expect(newSequencer).to.not.equal(initialSequencer);
    });

    it("should slash misbehaving sequencer", async () => {
        const sequencerId = 1;
        const evidence = generateFraudProof();

        await registry.reportMisbehavior(sequencerId, evidence);
        await registry.slash(sequencerId, ethers.parseEther("10000"));

        const info = await registry.getSequencer(sequencerId);
        expect(info.status).to.equal(SequencerStatus.Suspended);
        expect(info.stake).to.be.lt(initialStake);
    });
});

Selection Mechanism Tests

describe("Sequencer Selection", () => {
    it("should select via weighted random", async () => {
        // Register sequencers with different stakes
        const stakes = [100, 200, 300, 400]; // Different weights
        for(let i = 0; i < stakes.length; i++) {
            await registry.registerSequencer(
                endpoint,
                publicKey,
                metadata,
                { value: ethers.parseEther(stakes[i].toString()) }
            );
        }

        // Run selection many times to verify distribution
        const selections = {};
        for(let i = 0; i < 1000; i++) {
            const selected = await selection.selectWeightedRandom(state, blockHash);
            selections[selected] = (selections[selected] || 0) + 1;
        }

        // Verify roughly proportional to stakes
        expect(selections[accounts[3]] / selections[accounts[0]])
            .to.be.closeTo(4, 0.5);
    });

    it("should run sequencer auction", async () => {
        const auctionId = await selection.initAuction(3600); // 1 hour

        // Place bids
        await selection.placeBid(auctionId, { value: ethers.parseEther("100") });
        await selection.connect(accounts[1]).placeBid(
            auctionId,
            { value: ethers.parseEther("150") }
        );

        await time.increase(3601);
        const winner = await selection.finalizeAuction(auctionId);

        expect(winner).to.equal(accounts[1].address);
    });
});

MEV Mitigation Tests

describe("MEV Mitigation", () => {
    it("should handle threshold encrypted transactions", async () => {
        const tx = createTransaction();
        const encrypted = encrypt(tx, thresholdKey);
        const commitment = keccak256(tx);

        const txId = await mev.submitEncrypted(encrypted, commitment);

        // Validators submit key shares
        for(let i = 0; i < threshold; i++) {
            await mev.connect(validators[i]).submitKeyShare(
                txId,
                keyShares[i]
            );
        }

        // Decrypt and verify
        const decrypted = await mev.decryptTransaction(txId);
        expect(keccak256(decrypted)).to.equal(commitment);
    });

    it("should enforce fair ordering", async () => {
        const txHashes = [
            "0xaaa...",
            "0xbbb...",
            "0xccc..."
        ];

        const fairOrder = await mev.determineFairOrder(txHashes, blockNumber);

        // Verify deterministic ordering
        const fairOrder2 = await mev.determineFairOrder(txHashes, blockNumber);
        expect(fairOrder).to.deep.equal(fairOrder2);
    });
});

AI Workload Tests

describe("AI Workload Scheduling", () => {
    it("should schedule job to optimal sequencer", async () => {
        // Register sequencers with different capabilities
        await scheduler.registerCapabilities(1, {
            availableFlops: ethers.parseUnits("100", 12), // 100 TFLOPS
            availableMemory: 128 * 1024 * 1024 * 1024, // 128 GB
            hasGPU: true,
            hasTEE: false
        });

        await scheduler.registerCapabilities(2, {
            availableFlops: ethers.parseUnits("50", 12),
            availableMemory: 64 * 1024 * 1024 * 1024,
            hasGPU: false,
            hasTEE: true
        });

        const job = {
            requiredFlops: ethers.parseUnits("80", 12),
            memoryRequirement: 100 * 1024 * 1024 * 1024,
            deadline: Date.now() + 3600,
            priority: 10
        };

        const jobId = await scheduler.submitComputeJob(job);
        const sequencer = await scheduler.getOptimalSequencer(job);

        expect(sequencer).to.equal(1); // First sequencer has enough resources
    });

    it("should rebalance workload", async () => {
        // Submit multiple jobs
        for(let i = 0; i < 10; i++) {
            await submitJob(i);
        }

        // Check initial distribution
        const load1 = await scheduler.getSequencerLoad(1);
        const load2 = await scheduler.getSequencerLoad(2);

        // Trigger rebalance
        await scheduler.rebalanceWorkload();

        // Verify more even distribution
        const newLoad1 = await scheduler.getSequencerLoad(1);
        const newLoad2 = await scheduler.getSequencerLoad(2);

        expect(Math.abs(newLoad1 - newLoad2)).to.be.lt(Math.abs(load1 - load2));
    });
});

Distributed Training Tests

describe("Distributed Training", () => {
    it("should coordinate training cluster", async () => {
        const sequencerIds = [1, 2, 3, 4, 5];
        const modelHash = keccak256("bert-large");

        const clusterId = await training.createTrainingCluster(
            sequencerIds,
            modelHash
        );

        // Assign data shards
        for(let i = 0; i < 5; i++) {
            await training.assignDataShard(clusterId, sequencerIds[i], {
                shardId: keccak256(`shard${i}`),
                sequencerId: sequencerIds[i],
                dataHash: keccak256(`data${i}`),
                numSamples: 10000,
                startIndex: i * 10000,
                endIndex: (i + 1) * 10000
            });
        }

        // Submit gradients
        for(let i = 0; i < 5; i++) {
            await training.submitGradient({
                clusterId,
                sequencerId: sequencerIds[i],
                epoch: 1,
                gradientHash: keccak256(`gradient${i}`),
                loss: 100 - i * 10,
                timestamp: Date.now()
            });
        }

        // Aggregate gradients
        const aggregated = await training.aggregateGradients(clusterId, 1);
        expect(aggregated).to.not.equal(ZERO_HASH);

        // Broadcast new weights
        await training.broadcastWeights(clusterId, aggregated);
    });

    it("should handle sequencer failure", async () => {
        const clusterId = await createCluster();
        const failedSequencer = 3;

        await training.reportFailure(clusterId, failedSequencer);
        await training.reassignWork(clusterId, failedSequencer, 6);

        const cluster = await training.getCluster(clusterId);
        expect(cluster.sequencerIds).to.not.include(failedSequencer);
        expect(cluster.sequencerIds).to.include(6);
    });
});

Reference Implementation

Available at:

Key components:

contracts/SequencerRegistry.sol: Main registry contract
contracts/SelectionMechanisms.sol: Various selection strategies
contracts/MEVMitigation.sol: Anti-MEV mechanisms
contracts/AIScheduler.sol: Workload scheduling
p2p/: Sequencer P2P network implementation

Security Considerations

Sybil Resistance

Minimum Stake: High barrier to entry (100k LUX)
Reputation System: Long-term performance tracking
Identity Verification: Optional KYC for operators
Network Diversity: Geographic and infrastructure requirements

Liveness

Multiple Sequencers: No single point of failure
Automatic Failover: Quick replacement of failed sequencers
L1 Fallback: Users can submit directly to L1
Timeout Mechanisms: Automatic rotation on inactivity

Censorship Resistance

Rotation: Regular sequencer changes
Forced Inclusion: L1 can force transaction inclusion
Encrypted Mempool: Sequencers can't discriminate
Slashing: Penalties for censorship

Economic Security

Stake at Risk: Misbehavior leads to slashing
Delegation Limits: Cap on delegated stake
Gradual Exits: Time delay for stake withdrawal
Insurance Fund: Coverage for user losses

Economic Impact

Revenue Streams

Sequencer Fees: 0.01-0.1% of transaction value
Priority Fees: Users pay for faster inclusion
MEV Auctions: Sequencer slot auctions
Compute Premiums: Higher fees for AI workloads

Cost Structure

Infrastructure: $10,000/month per sequencer
Stake Opportunity Cost: 5-10% APY
Insurance: 1% of revenue to insurance fund
Development: Ongoing protocol improvements

Market Dynamics

Competition: Multiple sequencers compete on quality
Specialization: Some focus on AI, others on DeFi
Economies of Scale: Larger operators more efficient
Decentralization Incentives: Bonuses for geographic diversity

Open Questions

Optimal Rotation Period: Balance between stability and decentralization
Stake Requirements: Minimum stake vs accessibility
Cross-L2 Sequencing: Shared sequencer sets
Regulatory Compliance: KYC/AML for sequencer operators

References

Kelkar, M., et al. (2021). "Order-Fairness for Byzantine Consensus"
Flashbots (2021). "MEV-SGX: A Sealed-Bid MEV Auction Design"
Chainlink (2020). "Fair Sequencing Services: Enabling a Provably Fair DeFi Ecosystem"
Boneh, D., et al. (2018). "Verifiable Delay Functions"
Buterin, V. (2021). "Proposer/Builder Separation"
Espresso Systems (2022). "HotShot: BFT Consensus Designed for Rollups"
Radius (2023). "Shared Sequencing Layer"
Astria (2023). "Decentralized Sequencer Network"

Implementation

Status: Specification stage - implementation planned for future release

Planned Locations:

Sequencer registry: ~/work/lux/sequencer-registry/ (to be created)
Selection mechanisms: ~/work/lux/sequencer-registry/selection/
MEV mitigation: ~/work/lux/sequencer-registry/mev/
AI scheduling: ~/work/lux/sequencer-registry/scheduler/
Contracts: ~/work/lux/standard/src/sequencer/

Build on Existing Infrastructure:

P-Chain validator set management (reference implementation)
Warp messenger for cross-sequencer communication
Existing staking mechanisms from Platform VM
Q-Chain for post-quantum signature validation

Core Components:

Registry Smart Contract (~800 LOC Solidity)
- Sequencer registration and staking
- Rotation scheduling
- Performance tracking
Selection Engine (~1200 LOC Go)
- Round-robin scheduling
- Weighted random selection (VRF-based)
- Auction mechanism
- Performance-based selection
MEV Mitigation (~1500 LOC Go)
- Threshold encryption for transactions
- Time-locked transaction handling
- Fair ordering determinism
AI Workload Scheduler (~1300 LOC Go)
- Compute requirement matching
- Load balancing
- Priority queue management
- Fault tolerance and migration
Distributed Training Coordinator (~1000 LOC Go)
- Cluster formation and management
- Data shard distribution
- Gradient aggregation
- Checkpoint management

Integration Points:

P-Chain: Validator set queries and epoch-based selection
Platform VM: Staking and delegation mechanisms
Warp: Cross-chain sequencer coordination
EVM: Precompile interface for dApps

Testing Strategy:

Selection mechanism distribution testing (statistical analysis)
MEV mitigation game-theoretic verification
Load balancing under various workload distributions
Byzantine sequencer behavior resistance

Performance Targets:

Block proposal latency: < 500ms
Selection decision time: < 50ms
MEV protection overhead: < 5%
Scheduler decision time: < 100ms

Deployment Phases:

Phase 1: Basic registry + round-robin selection
Phase 2: Weighted random + auction mechanisms
Phase 3: MEV mitigation (threshold encryption)
Phase 4: AI workload scheduling
Phase 5: Distributed training coordination
Phase 6: Cross-rollup sequencer coordination

Sequencer Registry Protocol