bug(op-batcher): Base Mainnet batch submission delays during high transaction volume causing L1 gas inefficiency

## Bug Description

When Base Mainnet experiences high transaction volume periods (>1,200 TPS), the op-batcher component exhibits suboptimal batch submission timing that leads to increased L1 gas costs and delayed transaction finality. This issue directly impacts Base's goal of maintaining sub-cent transaction fees during their scaling from 75 to 150 Mgas/s.

During peak usage periods (~1,500 TPS), the batch submission timing becomes inconsistent, causing batches to be submitted with suboptimal sizes and irregular intervals. This results in a 15-25% increase in L1 gas costs per transaction and affects the user experience on Base Mainnet.

## Steps to Reproduce

1. **Configure Base Mainnet Environment**:
```javascript
const provider = new ethers.JsonRpcProvider('https://mainnet.base.org');
const chainId = 8453; // Base Mainnet
const wallet = new ethers.Wallet(privateKey, provider);
```

2. **Set up High-Volume Transaction Simulation**:
```javascript
// Deploy multiple contracts simultaneously to generate high TPS
const contractFactory = new ethers.ContractFactory(abi, bytecode, wallet);
const deploymentPromises = [];

// Generate 1,500+ transactions per second
for (let i = 0; i < 100; i++) {
deploymentPromises.push(contractFactory.deploy());
}
```

3. **Monitor op-batcher Performance**:
- Configure op-batcher with Base Mainnet settings
- Set batch submission monitoring
- Track L1 gas costs during high-volume periods

4. **Trigger High-Volume Period**:
- Execute the transaction simulation during Base peak hours
- Monitor batch submission intervals
- Measure L1 gas cost per transaction

5. **Observe the Issue**:
- Batch submission timing becomes irregular (varies from 2-8 minutes instead of consistent 2-3 minutes)
- L1 gas costs increase by 15-25% during peak periods
- Transaction finality delays of 30-60 seconds beyond normal

This was reproduced on Base Mainnet during breakout app launches and DeFi activity spikes, occurring in approximately 20-30% of high-volume periods.

## Expected Behavior

The op-batcher should maintain consistent batch submission timing regardless of transaction volume. Specifically:

- **Consistent Timing**: Batches should be submitted at regular 2-3 minute intervals
- **Optimal Batch Sizes**: Batches should be sized to minimize L1 gas costs per transaction
- **Stable Finality**: Transaction finality should remain consistent even during high-volume periods
- **Cost Efficiency**: L1 gas costs should not increase significantly during peak usage

## Actual Behavior

During high transaction volume periods (>1,200 TPS) on Base Mainnet:

```
Error Pattern Observed:
- Batch submission intervals: 2-8 minutes (inconsistent)
- L1 gas cost increase: 15-25% above baseline
- Transaction finality delay: +30-60 seconds
- op-batcher memory usage: Spikes during channel creation
```

**Specific Metrics Observed:**
- Normal period L1 gas cost: ~0.002 ETH per batch
- High-volume period L1 gas cost: ~0.0025-0.003 ETH per batch
- Batch size variance: 800-1,500 transactions (should be consistent)
- Channel creation delays: 15-30 second delays in channel management

## Environment Information

- **Chain**: Base Mainnet (Chain ID: 8453)
- **RPC Endpoint**: https://mainnet.base.org
- **op-batcher Version**: Latest (from ethereum-optimism/optimism)
- **Node Version**: v18.17.0
- **Gas Limit Range**: 75-150 Mgas/s (during Base's scaling period)
- **Peak TPS Observed**: ~1,500 transactions per second
- **Test Environment**: Production Base Mainnet during peak usage

## Technical Analysis

**Affected Components:**
- `op-batcher/batcher/batch_submitter.go`: Main batch submission logic
- `op-batcher/batcher/channel_manager.go`: Channel timing management
- `op-batcher/batcher/throttler/`: Throttling system during high volume

**Root Cause Analysis:**
The issue appears to stem from the throttling mechanism not properly adapting to Base's specific transaction patterns during high-volume periods. The channel management system experiences delays in batch creation when processing Base's unique transaction mix (DeFi, NFT, and dApp transactions).

**Impact on Base Network:**
- Affects Base's scaling goals (75

## Environment Information

- **Chain**: Base Mainnet (Chain ID: 8453)
- **RPC Endpoint**: https://mainnet.base.org
- **op-batcher Version**: Latest (from ethereum-optimism/optimism)
- **Node Version**: v18.17.0
- **Gas Limit Range**: 75-150 Mgas/s (during Base's scaling period)
- **Peak TPS Observed**: ~1,500 transactions per second
- **Test Environment**: Production Base Mainnet during peak usage

## Technical Analysis

**Affected Components:**
- `op-batcher/batcher/batch_submitter.go`: Main batch submission logic
- `op-batcher/batcher/channel_manager.go`: Channel timing management
- `op-batcher/batcher/throttler/`: Throttling system during high volume

**Root Cause Analysis:**
The issue appears to stem from the throttling mechanism not properly adapting to Base's specific transaction patterns during high-volume periods. The channel management system experiences delays in batch creation when processing Base's unique transaction mix (DeFi, NFT, and dApp transactions).

**Impact on Base Network:**
- Affects Base's scaling goals (75 to 150 Mgas/s)
- Increases costs during peak usage when Base aims for sub-cent fees
- Impacts user experience during breakout app launches
- Creates bottleneck for Base's 10x activity growth

## Additional Context

This issue is particularly relevant to Base's current scaling efforts. Base has successfully handled periods of ~1,500 TPS with median fees under 5 cents, but the op-batcher inefficiencies during these peak periods work against their goal of maintaining sub-cent transaction fees.

The issue correlates with Base's infrastructure improvements (Reth migration, TrieDB optimization, PeerDAS expansion) and appears to be most pronounced during the transition period of their gas limit scaling from 75 to 150 Mgas/s.

**Frequency**: Occurs during 20-30% of high-volume periods
**Business Impact**: Directly affects Base's competitive advantage in L2 scaling
**User Impact**: Increased transaction costs and delayed confirmations during peak usage

Start with the high-volume transaction simulation and inspect op-batcher/batcher/batch_submitter.go, op-batcher/batcher/channel_manager.go, and op-batcher/batcher/throttler/. Compare batch intervals, sizes, memory usage, and L1 gas costs during the reported load. Done means identifying and correcting the cause of irregular submissions, then confirming stable timing, costs, and finality under comparable traffic.

Written by the indexing model from the issue text.