138. Network Prediction


This sample shows how to use prediction and smoothing algorithms to compensate for network lag, making remotely controlled objects appear to move smoothly even when there is a significant delay in packets being delivered over the network.

Sample Overview

The Network Architecture: Client/Server and Network Architecture: Peer-to-Peer samples demonstrate two different network topologies, using an example of a tank that the player can drive around the screen. In both samples, tank data are sent over the network every frame, 60 times per second. That's a lot of data! When playing over a local network, these packets are delivered quickly enough to achieve smooth and continuous movement, but things don't work so well over the Internet. Most Internet connections don't have sufficient bandwidth to send data so often, and are slow enough that players will see delays and jerkiness in the movement of the tank.

This sample shows how to make the tank example from the Network Architecture: Peer-to-Peer sample work over the Internet. It uses the NetworkSession.SimulatedLatency and NetworkSession.SimulatedPacketLoss properties to artifically emulate a typical Internet connection, so you can see the effects of lag even when testing over a fast local network. It then applies prediction and smoothing algorithms to compensate for this lag, making the tanks move smoothly even though the underlying network data is far from smooth.


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