```json
{
  "sym_variables": [
    ("x1", "ring layouts"),
    ("x2", "tree layouts"),
    ("x3", "mesh layouts")
  ],
  "objective_function": "2000*x1 + 4000*x2 + 8000*x3",
  "constraints": [
    "50*x1 + 30*x2 + 100*x3 <= 2000",
    "20*x1 + 15*x2 + 50*x3 <= 500",
    "10*x1 + 7*x2 + 30*x3 <= 300",
    "x1 >= 0",
    "x2 >= 0",
    "x3 >= 0"
  ]
}
```

```python
import gurobipy as gp

# Create a new model
model = gp.Model("NovaNetwork")

# Create variables
ring = model.addVar(vtype=gp.GRB.INTEGER, name="ring")
tree = model.addVar(vtype=gp.GRB.INTEGER, name="tree")
mesh = model.addVar(vtype=gp.GRB.INTEGER, name="mesh")


# Set objective function
model.setObjective(2000 * ring + 4000 * tree + 8000 * mesh, gp.GRB.MAXIMIZE)

# Add constraints
model.addConstr(50 * ring + 30 * tree + 100 * mesh <= 2000, "workstations")
model.addConstr(20 * ring + 15 * tree + 50 * mesh <= 500, "servers")
model.addConstr(10 * ring + 7 * tree + 30 * mesh <= 300, "switches")


# Optimize model
model.optimize()

# Print results
if model.status == gp.GRB.OPTIMAL:
    print(f"Optimal profit: ${model.objVal:.2f}")
    print(f"Ring layouts: {ring.x:.0f}")
    print(f"Tree layouts: {tree.x:.0f}")
    print(f"Mesh layouts: {mesh.x:.0f}")
elif model.status == gp.GRB.INFEASIBLE:
    print("The model is infeasible.")
else:
    print(f"Optimization ended with status {model.status}")

```
