Alright, let’s break it down. The goal is to keep the server load as even as possible across all nodes, so each node handles roughly the same amount of work. We usually start with the basic load‑balance equation: **Load_i = Σ (Task_j × Weight_j) / Node_i_capacity** where Load_i is the load on node i, Task_j is the computational cost of task j, Weight_j is how many times that task appears in a given time window, and Node_i_capacity is the processing power (in FLOPs or similar) of node i. Now, to make it “optimal” we minimise the maximum load across all nodes. That’s an optimisation problem: **minimize max_i Load_i** subject to - Σ_i Load_i = Σ_j (Task_j × Weight_j) (total work is constant) - Load_i ≤ Node_i_capacity (each node cannot exceed its capacity) In practice we often approximate it with a linear programming model or a greedy algorithm that iteratively assigns the most expensive tasks to the least loaded node. If you want a quick closed‑form check, you can use the “balance factor”: **BF = (max_i Load_i) / (average Load)** If BF is close to 1, you’re near optimal. If it’s above, say, 1.2, you’re still a bit off. And remember, for huge multiplayer games we often add a safety margin: keep each node’s load at no more than 85% of its capacity to account for spikes. Give me the numbers from your simulations, and we can crunch the exact BF and tweak the assignment algorithm until BF < 1.05. That’ll give us a rock‑solid load balance.

Sure thing, just drop the task cost list and the capacity specs of each server in the chat, and I’ll pull the numbers straight into the formula. Once I’ve got the raw data, we’ll crunch the balance factor and start moving the heavy hitters around if we need to. Ready when you are!