Distributed Auction System

This tutorial demonstrates building a robust, secure distributed auction system using the Ceylon multi-agent framework. The system implements a scalable architecture with an auctioneer agent orchestrating the auction process and multiple authenticated bidder agents participating in real-time auctions.

System Overview

The auction system implements: - Multiple concurrent auction support with isolation - Secure bid validation and authentication - Configurable auction rules (reserve price, minimum increment) - Fault-tolerant communication with automatic recovery - Scalable bid processing with rate limiting

Core Components

Data Models

@dataclass
class Item:
    name: str
    starting_price: float
    reserve_price: Optional[float] = None
    min_increment: float = 1.0
    auction_duration: timedelta = timedelta(minutes=5)

@dataclass
class Bid:
    bidder: str
    amount: float
    timestamp: float
    signature: bytes  # For bid verification
    auction_id: str

@dataclass
class AuctionStart:
    item: Item
    auction_id: str
    start_time: float

@dataclass
class AuctionResult:
    winner: str
    winning_bid: float
    auction_id: str
    end_time: float

@dataclass
class AuctionEnd:
    auction_id: str
    reason: str  # "completed", "reserve_not_met", "cancelled"

Auctioneer Agent

The auctioneer manages multiple concurrent auctions:

class Auctioneer(BaseAgent):
    def __init__(self, name="auctioneer", port=8888):
        super().__init__(
            name=name,
            mode=PeerMode.ADMIN,
            role="auctioneer",
            port=port
        )
        self.active_auctions: Dict[str, AuctionState] = {}
        self.bid_queue = asyncio.Queue(maxsize=1000)
        self.bidder_registry: Dict[str, BidderInfo] = {}

Key features: - Asynchronous bid processing with rate limiting - Automatic auction timeouts and cleanup - Bid verification and signature validation - Bidder reputation tracking - Comprehensive error handling and recovery

Bidder Agent

Each bidder implements secure auction participation:

class Bidder(BaseAgent):
    def __init__(self, name: str, budget: float, strategy: BiddingStrategy):
        super().__init__(
            name=name,
            mode=PeerMode.CLIENT,
            role="bidder"
        )
        self.budget = budget
        self.strategy = strategy
        self.active_bids: Dict[str, float] = {}
        self.key_pair = generate_keypair()  # For bid signing

Key features: - Configurable bidding strategies - Bid signing and verification - Budget enforcement and tracking - Automatic bid updates on price changes - Graceful handling of connection issues

Advanced Bidding Strategies

class SmartBidder(Bidder):
    async def calculate_bid(self, item: Item, auction_state: AuctionState) -> float:
        market_value = await self.estimate_market_value(item)
        competition = len(auction_state.active_bidders)
        time_remaining = auction_state.end_time - time.time()

        if time_remaining < 60:  # Last minute strategy
            return min(self.budget, market_value * 1.1)

        return min(
            self.budget,
            market_value * (0.8 + (0.4 * (1 - time_remaining/auction_state.duration)))
        )

Error Handling and Recovery

class AuctionManager:
    async def handle_disconnection(self, bidder_id: str):
        affected_auctions = self.find_affected_auctions(bidder_id)
        for auction in affected_auctions:
            if auction.status == "pending_payment":
                await self.revert_auction(auction.id)
            else:
                await self.pause_auction(auction.id)
                await self.notify_participants(auction.id, "auction_paused")

    async def recover_auction_state(self, auction_id: str):
        state = await self.load_backup_state(auction_id)
        await self.verify_bid_sequence(state.bids)
        await self.resume_auction(state)

Running the System

1. Initialize auction system with configuration:

   config = AuctionConfig(
       min_bidders=3,
       bid_timeout=30,
       max_concurrent_auctions=10,
       bid_verification_required=True
   )
   auctioneer = Auctioneer(config)
   

2. Create authenticated bidders:

   bidders = [
       SmartBidder("Alice", 1500.0, MarketValueStrategy()),
       SmartBidder("Bob", 1200.0, AggressiveStrategy()),
       SmartBidder("Charlie", 2000.0, ConservativeStrategy())
   ]
   

3. Start the system with monitoring:

   async with AuctionMonitor() as monitor:
       await auctioneer.start_agent(b"", bidders)
       await monitor.track_metrics()
   

System Architecture

sequenceDiagram
    participant A as Auctioneer
    participant B1 as Bidder1
    participant B2 as Bidder2
    participant B3 as Bidder3
    participant M as Monitor

    Note over A,M: Initialization Phase
    A->>M: Register System
    B1->>A: Connect(auth_token)
    A->>B1: Connection Confirmed
    B2->>A: Connect(auth_token)
    A->>B2: Connection Confirmed
    B3->>A: Connect(auth_token)
    A->>B3: Connection Confirmed

    Note over A,M: Auction Start
    A->>M: Start Monitoring
    A->>B1: AuctionStart(item, rules)
    A->>B2: AuctionStart(item, rules)
    A->>B3: AuctionStart(item, rules)

    Note over A,M: Active Bidding
    B1-->>A: SignedBid(amount, timestamp)
    A-->>M: Log Bid
    A->>B1: BidAcknowledged
    B2-->>A: SignedBid(amount, timestamp)
    A-->>M: Log Bid
    A->>B2: BidAcknowledged
    B3-->>A: SignedBid(amount, timestamp)
    A-->>M: Log Bid
    A->>B3: BidAcknowledged

    Note over A,M: Auction Close
    A->>M: Finalize Metrics
    A->>B1: AuctionResult(winner, amount)
    A->>B2: AuctionResult(winner, amount)
    A->>B3: AuctionResult(winner, amount)
    A->>M: Store Results

Performance Monitoring

The system includes built-in monitoring for: - Bid processing latency - Message queue depths - Bidder connection health - Auction completion rates - System resource utilization

Security Considerations

1. Bid Authentication - All bids are cryptographically signed - Timestamps prevent replay attacks - Rate limiting prevents DoS attacks

2. Data Integrity - Auction state is regularly checkpointed - Bid history is immutable and verifiable - Transaction logs for audit trails

3. Access Control - Bidder authentication required - Role-based permissions - Resource usage quotas

Scalability Features

1. Horizontal Scaling - Multiple auctioneer instances - Load-balanced bidder connections - Distributed state management

2. Performance Optimization - Asynchronous bid processing - Efficient state management - Connection pooling - Message batching