How the Aggregator Works

Step 1: Collect liquidity pool data

It gathers data from connected AMMs:

• Direct pools (TokenA–TokenB)

• Intermediate pools (via WETH, USDC, etc.)

Supported:

• V2 Pools — constant product (x * y = k)

• V3 Pools — concentrated liquidity

• Order Book — e.g., Kuru

Step 2: Build the route graph

• Nodes = tokens

• Edges = liquidity pools

Step 3: Find optimal paths

Uses a modified Bellman-Ford algorithm to find up to 4-hop paths and selects the one with the best output.

Step 4: Simulate and calculate

Each route is simulated considering pool fee, liquidity, and slippage.

---

Route Graph Visualization

Here's how the aggregator maps available liquidity:

text    [USDT] ----Pool1---- [WMON]
          |                     |
        Pool2                 Pool3
          |                     |
        [USDC]  ----Pool4---- [MON]

Graph Structure:

• Nodes: USDT, WMON, USDC, MON (tokens)

• Edges: Pool1, Pool2, Pool3, Pool4 (liquidity pools)

Possible Routes (USDT → DAI):

1. Direct: USDT → Pool2 → USDC → Pool4 → MON

2. Multi-hop: USDT → Pool1 → WMON → Pool3 → MON

3. Complex: USDT → Pool1 → WMON → Pool3 → MON + USDT → Pool2 → USDC → Pool4 → MON (split route)

---

Route Types

1. Direct Route

Single pool: [USDT] → [WMON]

2. Multi-hop Route

Through intermediates: [TokenA] → [WMON] → [TokenB]

3. Split Route

Split across pools: 60% Kuru, 40% Bean

---

Route Building Process

1. Pool discovery (5–10 ms)

2. Graph construction (10–20 ms)

3. Path search (50–200 ms)

4. Alternative search (30–100 ms)

Optimization

Weights assigned based on efficiency

Bonuses/penalties:

• +15% for direct routes

• +5% for V3

• −2% per extra hop

Limits:

• Max 60% per route

• Min 5% per route

Convert to smart contract weights

Example:

• Route 1: 60% → 6000

• Route 2: 25% → 2500

• Route 3: 15% → 1500

• Total: 10000 ✅

---

Optimization and Distribution

Three strategies compared:

1. Single best route

2. Multiple direct routes

3. Multi-hop combinations

The system picks the strategy with the highest token output.

Slippage example

• Expected: 1000 tokens

• Fee 0.2% = -2

• Slippage 0.5% = -5

• → Minimum = 993 tokens