Reputation Ledger

The Reputation Ledger is a core component of Session’s architecture, designed to establish a trust-based framework that holds each client accountable for their activity on the network. This ledger is a transparent, decentralized system, maintaining a real-time record of client and node interactions, performance metrics, and reputation scores.

The Reputation Ledger serves two primary functions:

1. Traffic Quality Monitoring: It evaluates and logs the nature and quality of traffic sent by each client. Clients who trigger firewall blocks due to suspicious or abusive behavior receive penalties, reducing their reputation score (similar to slashing in blockchain networks).

2. Node Performance Tracking: It maintains an up-to-date record of each lite-node’s reliability, speed, and resource availability. These metrics inform the selection process when assigning nodes to fulfill requests, ensuring optimal allocation based on performance and reputation.

Components of the Reputation Ledger

The Reputation Ledger consists of the following components:

• Client Reputation: Each client is assigned a reputation score that reflects their historical behavior and trustworthiness. Higher reputation scores indicate consistent, legitimate activity, while lower scores result from firewall blocks, suspicious traffic, or non-compliance with network policies.

• Node Metrics: The ledger tracks critical performance metrics for each lite-node, such as:

  • Uptime: How often the node is active and responsive.

  • Reliability: Frequency of successful request processing.

  • Latency: Response time for processing requests.

  • Bandwidth Utilization: Amount of bandwidth the node has contributed over time.

These metrics enable a fair and dynamic selection process, giving preference to nodes that demonstrate consistent, high-quality performance.

Pseudocode: Client Reputation Management

Class ReputationLedger:
    Initialize:
        client_reputations = empty dictionary

    Function register_client(client_id):
        If client_id not in client_reputations:
            client_reputations[client_id] = {
                reputation: 100,
                requests: 0,
                blocks: 0
            }

    Function track_request(client_id):
        If client_id in client_reputations:
            client_reputations[client_id].requests += 1

    Function penalize_client(client_id, penalty = 10):
        If client_id in client_reputations:
            client_reputations[client_id].reputation -= penalty
            client_reputations[client_id].blocks += 1

    Function get_client_reputation(client_id):
        If client_id in client_reputations:
            Return client_reputations[client_id].reputation
        Else:
            Return 0

// When client connects to network
ON CLIENT_CONNECT:
    IF client not in reputation_system:
        Initialize client score to 50
        Create empty event history

// During client activity on network
ON CLIENT_REQUEST:
    Get client's current reputation
    
    IF suspicious traffic detected:
        Decrease reputation by 5
        Log suspicious activity
    
    IF firewall block triggered:
        Decrease reputation by 10
        Log blocking event
    
    IF request successful:
        Increase reputation by 1
        Log successful request

// Periodic updates
ON REPUTATION_UPDATE_INTERVAL:
    FOR each client:
        Apply time decay to reputation
        Update trust status based on current score:
            90+ -> Highly Trusted
            40-89 -> Neutral
            <40 -> Untrusted

// When checking client status
ON CLIENT_STATUS_CHECK:
    Return:
        Current reputation score
        Trust status
        Recent events

This pseudocode initializes a reputation ledger for clients, tracks their requests, applies penalties for suspicious behavior, and retrieves their reputation scores.

Pseudocode: Node Metrics Tracking

Class LiteNode:
    Initialize(node_id):
        self.node_id = node_id
        self.uptime = 0
        self.reliability = 0.0
        self.latency = 0.0
        self.bandwidth_usage = 0

Class ReputationLedger:
    Initialize:
        client_reputations = empty dictionary
        node_metrics = empty dictionary

    Function register_node(node_id):
        If node_id not in node_metrics:
            node_metrics[node_id] = new LiteNode(node_id)

    Function update_node_performance(node_id, uptime, reliability, latency, bandwidth):
        If node_id in node_metrics:
            node = node_metrics[node_id]
            node.uptime = uptime
            node.reliability = reliability
            node.latency = latency
            node.bandwidth_usage += bandwidth

    Function get_node_metrics(node_id):
        If node_id in node_metrics:
            Return node_metrics[node_id] as dictionary
        Else:
            Return empty dictionary

// When node joins network
ON NODE_CONNECT:
    Initialize node metrics:
        uptime = 0
        response_time_avg = 0
        successful_requests = 0
        network_failures = 0    // failures due to node's network
        client_failures = 0     // failures due to client issues
        total_requests = 0
        bandwidth_used = 0
        last_heartbeat = current_time

// Regular health checks
ON HEARTBEAT_INTERVAL:
    FOR each node:
        Send health probe
        IF node responds:
            Update last_heartbeat
            Record response time
            Update uptime percentage
        ELSE:
            // Cross-check with other nodes to verify network status
            IF other_nodes_also_unreachable:
                Mark as network partition
            ELSE:
                Mark node as potentially offline
                IF offline_duration > threshold:
                    network_failures++
                    Decrease reliability score

// During request processing
ON REQUEST_ASSIGNED:
    Record request start time
    Track bandwidth allocation
    Monitor connection status
    
    IF request completes:
        successful_requests++
        Calculate response latency
        Update response_time_avg
        Add bandwidth to total
    ELSE:
        Analyze failure:
            // Check multiple indicators
            IF node_connection_dropped:
                network_failures++
            ELSE IF client_disconnected OR client_timeout OR invalid_request:
                client_failures++
            ELSE IF multiple_nodes_report_same_client_issue:
                client_failures++
            ELSE IF neighboring_nodes_operational:
                network_failures++
            
            Update reliability score based on failure type

// Node selection for requests
ON NODE_SELECTION:
    Filter available nodes where:
        - uptime above minimum threshold
        - response time within acceptable range
        - enough bandwidth available
        - network_failures below threshold
    
    Sort nodes by:
        - reliability score (excluding client-caused failures)
        - current load
        - response time

// Performance reporting
ON METRICS_UPDATE:
    FOR each node:
        Calculate:
            true_reliability = successful_requests / (total_requests - client_failures)
            health_score = weighted_average(
                uptime,
                true_reliability,
                response_time_avg,
                bandwidth_contribution
            )

This pseudocode represents how to register lite-nodes and keep track of their performance metrics within the Reputation Ledger.

Pseudocode: Node Selection Committee

Class SelectionCommittee:
    Initialize(reputation_ledger):
        self.reputation_ledger = reputation_ledger

    Function select_best_node(required_bandwidth):
        candidates = empty list

        For each node_id, metrics in reputation_ledger.node_metrics:
            If metrics.reliability > 0.9 AND metrics.bandwidth_usage >= required_bandwidth:
                Add node_id to candidates

        If candidates not empty:
            Sort candidates by:
                - Highest uptime (descending)
                - Lowest latency (ascending)
            selected_node = first node in sorted candidates
            Return selected_node
        Else:
            Return None

// When client needs a node for request
ON CLIENT_REQUEST_NODE(bandwidth_needed):
    // Get list of all available nodes
    available_nodes = GET_ACTIVE_NODES()
    candidates = []
    
    // Filter nodes based on minimum requirements
    FOR each node in available_nodes:
        IF node.reliability >= 75% AND    // Only highly reliable nodes
           node.bandwidth >= bandwidth_needed AND  // Has enough bandwidth
           node.is_online:  // Currently active
            Add node to candidates
    
    // If we found suitable nodes
    IF candidates not empty:
        // Sort them by performance metrics
        SORT candidates by:
            1. Uptime (highest first)
            2. Latency (lowest first)
        
        // Select best node
        best_node = first node in candidates
        RETURN best_node
        
    // No suitable nodes found
    ELSE:
        RETURN none

// Example usage flow:
ON NEW_MESSAGE_RELAY:
    bandwidth = CALCULATE_REQUIRED_BANDWIDTH(message)
    selected_node = CLIENT_REQUEST_NODE(bandwidth)
    
    IF selected_node exists:
        RELAY_MESSAGE(selected_node, message)
    ELSE:
        NOTIFY_NO_SUITABLE_NODES()

This pseudocode outlines the logic for selecting the best node based on reliability, bandwidth, uptime, and latency.