This paper explains the design architecture, implementation, and some of the lessons learned creating the multiplayer (networking) code for the Age of Empires 1 & 2 games; and discusses the current and future networking approaches used by Ensemble Studios in its game engines.

When the multiplayer code for Age of Empires was started in early 1996 there were some very specific goals that had to be met to deliver the kind of game experience we had in mind.

The Genie Engine was already running and the game simulation was shaping up into a compelling experience in single player. The Genie Engine is a 2D single-threaded (game loop) engine. Sprites are rendered in 256 colors in a tile-based world. Randomly-generated maps were filled with thousands of objects, from trees that could be chopped down to leaping gazelles. The rough breakdown (post optimization) of processing tasks for the engine was: 30% graphic rendering, 30% AI and Pathing, and 30% running the simulation & maintenance.

At a fairly early stage, the engine was reasonably stable -- and multiplayer communications needed to work with the existing code without substantial recoding of the existing (working) architecture.

To complicate matters further, the time to complete each simulation step varied greatly: the rendering time changed if the user was watching units, scrolling, or sitting over unexplored terrain, and large paths or strategic planning by the AI made the game turn fluctuate fairly wildly by as much as 200 msec.

A few quick calculations would show that passing even a small set of data about the units, and attempting to update it in real time would severely limit the number of units and objects we could have interacting with the player. Just passing X and Y coordinates, status, action, facing and damage would have limited us to 250 moving units in the game at the most.

We wanted to devastate a Greek city with catapults, archers, and warriors on one side while it was being besieged from the sea with triremes. Clearly, another approach was needed.

Simultaneous Simulations

Rather than passing the status of each unit in the game, the expectation was to run the exact same simulation on each machine, passing each an identical set of commands that were issued by the users at the same time. The PCs would basically synchronize their game watches in best war-movie tradition, allow players to issue commands, and then execute in exactly the same way at the same time and have identical games.

This tricky synchronization was difficult to get running initially, but did yield some surprising benefits in other areas.

Improving on the Basic Model

At the easiest conceptual level, achieving a simultaneous simulation seems fairly straightforward. For some games, using lock-step simulations and fixed game timings might even be feasible.

Since the problem of moving hundreds or thousands of objects simultaneously was taken care of by this approach -- the solution still had to be viable on the Internet with latency swings of 20 to 1,000 milliseconds, and handle changes in frame processing time.

Sending out the player commands, acknowledging all messages, and then processing them before going on to the next turn was going to be a gameplay nightmare of stop-start or slow command turnover. A scheme to continue processing the game while waiting for communications to happen in the background was needed.

Mark used a system of tagging commands to be executed two "communications turns" in the future (Comm. turns were separated in AoE from actual rendering frames).

So commands issued during turn 1000 would be scheduled for execution during turn 1002 (see Figure 1). On turn 1001 commands that were issued on turn 0999 would be executed. This allowed messages to be received, acknowledged, and ready to process while the game was still animating and running the simulation.

Figure 1. Tagging commands to be executed two "communications turns" in the future.

Turns were typically 200 msec in length, with commands being sent out during the turn. After 200 msec, the turn was cut off and the next turn was started. At any point during the game, commands were being processed for one turn, received and stored for the next turn, and sent out for execution two turns in the future.

"Speed Control"

Figure 2. Speed Control.

Since the simulations must always have the exact same input, the game can really only run as fast as the slowest machine can process the communications, render the turn, and send out new commands. Speed Control is what we called the system to change the length of the turn to keep the animation and gameplay smooth over changing conditions in communications lag and processing speed.

There are two factors that make the gameplay feel "laggy": If one machine's frame rate drops (or is lower than the rest) the other machines will process their commands, render all of the allocated time, and end up waiting for the next turn -- even tiny stops are immediately noticeable. Communications lag -- due to Internet latency and lost data packets would also stop the game as the players waited around for enough data to complete the turn.

Each client calculated a frame rate that it thought could be consistently maintained by averaging the processing time over a number of frames. Since this varied over the course of the game with the visible line-of-sight, number of units, map size and other factors -- it was sent with each "Turn Done" message.

Each client would also measure a round trip "ping time" periodically from it to the other clients. It would also send the longest average ping time it was seeing to any of the clients with the "Turn Done" message. (Total of 2 bytes was used for speed control)

Each turn the designated host would analyze the "done" messages, figure out a target frame rate and adjustment for Internet latency. The host would then send out a new frame rate and communications turn length to be used. Figures 3 through 5 show how the communications turn was broken up for the different conditions.

Figure 3. A single communication turn.

Figure 4. High Internet latency with normal machine performance.

Figure 5. Poor machine performance with normal latency.

The "communications turn" which was roughly the round-trip ping time for a message, was divided up into the number of simulation frames that on average could be done by the slowest machine in that period.

The communications turn length was weighted so it would quickly rise to handle Internet latency changes, and slowly settle back down to the best average speed that could be consistently maintained. The game would tend to pause or slow only at the very worst spikes- command latency would go up but would stay smooth (adjusting only a few milliseconds per turn) as the game adjusted back down to best possible speed. This gave the smoothest play experience possible while still adjusting to changing conditions.

Guaranteed Delivery

At the network layer UDP was used, with command ordering, drop detection and resending being handled by each client. Each message used a couple of bytes to identify the turn that execution was scheduled and the sequence number for the message. If a message was received for a past turn, it was discarded, and incoming messages were stored for execution. Because of the nature of UDP, Mark's assumption for message receipt was that "When in doubt, assume it dropped." If messages were received out of order, the receiver immediately sent out re-send requests for the dropped messages. If an acknowledgement was later than predicted, the sender would just resend without being asked anticipating the message had been dropped.

Hidden Benefits

Because the game's outcome depended on all of the users executing exactly the same simulation, it was extremely difficult to hack a client (or client communication stream) and cheat. Any simulation that ran differently was tagged as "out of sync" and the game stopped. Cheating to reveal information locally was still possible, but these few leaks were relatively easy to secure in subsequent patches and revisions. Security was a huge win.

Hidden Problems

At first take it might seem that getting two pieces of identical code to run the same should be fairly easy and straightforward -- not so. The Microsoft product manager, Tim Znamenacek, told Mark early on, "In every project, there is one stubborn bug that goes all the way to the wire -- I think out-of-sync is going to be it." He was right. The difficulty with finding out-of-sync errors is that very subtle differences would multiply over time. A deer slightly out of alignment when the random map was created would forage slightly differently -- and minutes later a villager would path a tiny bit off, or miss with his spear and take home no meat. So what showed up as a checksum difference as different food amounts had a cause that was sometimes puzzling to trace back to the original cause.

As much as we check-summed the world, the objects, the pathfinding, targeting and every other system -- it seemed that there was always one more thing that slipped just under the radar. Giant (50MB) message traces and world object dumps to sift through made the problem even more difficult. Part of the difficulty was conceptual -- programmers were not used to having to write code that used the same number of calls to random within the simulation (yes, the random numbers were seeded and synchronized as well).