Striking A Balance Between Server And Client-Side Physics Calculations
The Server-Client Physics Calculation Dilemma
Determining the optimal split between server and client physics calculations is a key dilemma in game development. Performing all physics on the server provides consistency but doesn’t scale while handling everything on the client enables responsiveness but risks inaccuracy. The goal is to strike the right balance based on game type, platform capabilities, and performance requirements.
Physics Calculations on the Server
Performing computations like collision detection, projectile trajectories, and particle simulations on the server ensures all clients share the same physics state. This is essential for multiplayer games to prevent cheating and synchronize experiences. Server-side physics also allows securing game rules and mechanics against manipulation.
var collisions = [];
for(var i = 0; i < objects.length; i++) {
for(var j = i + 1; j < objects.length; j++) {
if(objects[i].intersects(objects[j])) {
collisions.push(new Collision(objects[i], objects[j]));
}
}
}
applyCollisions(collisions);
updateGameState();
sendUpdatesToClients();
This example collision detection code runs on the server, collects all intersections between game objects, applies collision resolution, updates the authoritative game state, and syncs the changes to connected clients. This ensures all players see the same physics behavior. However, increased server load can result in laggy experiences if not handled efficiently.
Physics Calculations on the Client
Pushing physics computations to each individual client machine allows maximizing responsiveness and graphical fidelity. Client-side movement and animation calculations can run at high framerates unaffected by network speeds. This enables smooth, lag-free control and visuals critical for believable experiences.
function handleMovement() {
applyAcceleration();
applyVelocity();
moveObject();
clampToWorld();
collisionDetection();
}
function renderFrame() {
animationSystem();
lightingSystem();
renderObjects();
}
These examples demonstrate client-side movement physics along with animation and visualization calculations for high responsiveness. Each client runs these in real-time for precise interactions and visual updates. However, in multiplayer games, inconsistencies between clients can develop over time.
Finding the Right Balance
There are many factors to consider when balancing physics workloads including game genres, number of players, device capabilities, and performance budgets. Multiplayer games require more server-side calculations to enable fair competition and prevent exploits. Single-player games can shift more workloads to clients as consistency is less critical. Mobile devices limit client computation capacity due to lower memory, GPUs, and battery life.
For fast paced multiplayer games, collisions, projectiles, vehicles, and other key physics can run server-side while clients handle inputs, movement, animations, and visual effects. Turn-based games can utilize clients for computations in between turns synced via the server. Single-player mobile games can offload all physics to clients with occasional server checkpoints to prevent state divergences.
Playtesting different workload distributions is essential to strike the right balance for game feel, fairness, and performance. Low server workload risks inconsistencies but going too far risks lag and low responsiveness. Profile network traffic, server load, client frames per second, and gameplay feel to optimize.
Optimizing the Physics Pipeline
Fine tuning game physics performance involves employing optimization techniques like reducing communication overhead, avoiding redundant computations, interpolation, serialization, and locking. Compressing physics updates sent from server to clients reduces network congestion. Interpolating between state updates creates smooth transitions. Serializingphysics objects allows efficient transfer and storage.
class PhysicsObject {
Vector position;
Vector velocity;
Vector acceleration;
string Serialize() {
return Json(position) + "&" + Json(velocity) + "&" + Json(acceleration);
}
void Deserialize(string data) {
string[] values = data.Split('&');
position = JsonToVector(values[0]);
velocity = JsonToVector(values[1]);
acceleration = JsonToVector(values[2]);
}
}
This example serializes a physics object's state into a compact string for network transfer and deserializes back into actual variables on the client. Applying locks around physics update code prevents concurrent modifications. Optimizations enhance throughput and reduce latency for buttery smooth physics interactions.
Testing and Benchmarking
Quantitatively testing different server and client physics workload distributions is vital for optimizing performance. Capture metrics like server CPU and memory usage, network utilization, round trip latency, and client frame rates under simulated player loads. Compare results to target benchmarks and thresholds to identify bottlenecks.
Profile actual gameplay sessions with tools like console logging, network sniffers, and visual profilers to pinpoint heavy operations. Analyze profiling data to best allocate physics calculations between server and clients based on their capabilities and typical workloads during play.
// Pseudocode
Start game session with physics work 50/50 split
Spawn bots to simulate player load
While game running:
Monitor CPU, memory, network, FPS
If bottlenecks detected:
Adjust workload distribution
Sleep 5 minutes
Continue monitoring
End session
Analyze results
Repeat testing with different splits
This example methodology loads the game with an even physics split then adjusts based on real-time profiling before retesting to empirically determine optimal balance.
Achieving High Performance and Precision
Game physics requires carefully balancing workload between servers and client devices to maximize performance and precision. Striking the optimal balance depends on game type, platforms, network, and other constraints but begins with understanding processing costs. Profile hardware capabilities and gameplay analytics to allocate key calculations then optimize with techniques like serialization, interpolation, and locking.
Quantitative testing of different physics splits under simulated and real player loads identifies sensitivities and bottlenecks. Smooth gameplay feel, visual fidelity, and fairness rely on physics systems operating efficiently within capability budgets. Platform capabilities grow over time enabling more advanced techniques but only through diligent testing and optimization.
