🧪Simulation and Gas optimization

This guide demonstrates advanced techniques for utilizing gas simulation to achieve better fee estimations and guarantees, as well as implementing efficient transaction batching patterns using the cheqd SDK. These techniques are based on the SDK's internal implementation and provide production-ready optimization strategies.

Table of Contents

Gas Simulation Overview

Gas simulation allows you to accurately estimate transaction costs before execution, providing several key benefits:

Core Benefits

Benefit
Description
Use Case

Cost Prediction

Accurate fee estimation before transaction execution

User experience, cost planning

Failure Prevention

Early detection of insufficient gas scenarios

Transaction reliability

Optimal Gas Setting

Avoid over/under-provisioning gas

Cost optimization

Batch Optimization

Efficient grouping of multiple transactions

Throughput maximization

Simulation vs Real Execution

Aspect
Simulation
Real Execution

Network State

Current state snapshot

State at execution time

Gas Consumption

Estimated usage

Actual usage

Side Effects

None (read-only)

Permanent state changes

Cost

Free

Consumes actual fees

Advanced Gas Estimation

Basic Gas Simulation

The SDK provides a simulate() method for accurate gas estimation:

Enhanced Gas Estimation with Safety Margins

Bulk Gas Estimation for Multiple Transactions

Transaction Batching Strategies

The SDK provides an intelligent batchMessages() method that optimally groups transactions based on gas limits:

Core Batching Implementation

Advanced Batching Strategies

1. Priority-Based Batching

2. Smart Batching with Gas Optimization

3. Transaction Type-Aware Batching

Fee Optimization Patterns

Dynamic Fee Calculation with Simulation

Batch Fee Optimization

Production Implementation

Complete Implementation Example

Error Handling and Resilience

Robust Error Handling

Circuit Breaker Pattern

Built-in Transaction Retry Policy

The cheqd SDK includes a sophisticated retry mechanism in the broadcastTx method that automatically handles transient network failures and ensures reliable transaction delivery. Understanding this built-in functionality helps you design more robust applications.

Retry Policy Overview

The CheqdSigningStargateClient.broadcastTx() method implements an enhanced retry policy with the following features:

Feature
Description
Default Value

Max Retries

Maximum number of broadcast attempts

3

Timeout

Maximum wait time for transaction inclusion

60,000 ms (60s)

Poll Interval

Frequency of checking for transaction inclusion

3,000 ms (3s)

Backoff Delay

Brief delay between retry attempts

1,000 ms (1s)

How the Retry Policy Works

Retry Flow:

  1. Initial Broadcast: Attempts to broadcast transaction using broadcastTxSync

  2. Transaction Tracking: Records transaction hash for monitoring

  3. Polling Phase: Continuously checks for transaction inclusion in blocks

  4. Failure Handling: On broadcast failure, implements exponential backoff

  5. Retry Logic: Retries up to maxRetries times with same signed transaction

  6. Double-Spend Prevention: Reuses identical signed transaction bytes across retries

Retry Scenarios

The retry policy handles several common failure scenarios:

Error Handling and Transaction Tracking

The retry policy provides enhanced error information:

Integration with Gas Simulation

The retry policy works seamlessly with gas simulation and fee calculation:

Production Configuration

For production deployments, you can tune the retry parameters based on your requirements:

Monitoring Retry Behavior

You can implement monitoring to track retry patterns:

Key Benefits

The built-in retry policy provides several advantages:

  1. Reliability: Automatic handling of transient network issues

  2. Transaction Safety: Prevents double-spending through transaction reuse

  3. Visibility: Maintains transaction hash tracking even on failures

  4. Configurability: Tunable parameters for different use cases

  5. Integration: Works seamlessly with gas simulation and fee calculation

This retry mechanism significantly improves the reliability of transaction broadcasting without requiring additional application-level retry logic.

Best Practices Summary

Gas Simulation Best Practices

  1. Always Use Safety Margins: Apply 20-50% buffer to simulated gas estimates

  2. Handle Simulation Failures: Implement fallback gas values for production systems

  3. Batch Simulations: Simulate multiple transactions in parallel for efficiency

  4. Monitor Gas Usage: Track actual vs estimated gas consumption

  5. Network-Specific Limits: Respect network gas limits and consensus parameters

Batching Best Practices

  1. Optimal Batch Size: Target 80-90% of max gas limit for efficiency

  2. Transaction Prioritization: Group high-priority transactions together

  3. Type-Aware Batching: Consider transaction complexity when batching

  4. Error Isolation: Design batches to minimize failure propagation

  5. Progress Monitoring: Implement progress tracking for large batch operations

Production Deployment

  1. Comprehensive Testing: Test all scenarios in development environments

  2. Monitoring and Alerting: Track gas usage, failure rates, and cost optimization

  3. Graceful Degradation: Implement fallback strategies for all failure modes

  4. Performance Metrics: Monitor transaction throughput and cost effectiveness

  5. Regular Optimization: Continuously tune parameters based on network conditions

This comprehensive approach to gas simulation and transaction batching will provide optimal performance, cost efficiency, and reliability for production cheqd SDK implementations.

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