(Real) Science IS political, sorry to disillusion you

There is the big "climate gate" hoo-haw in the media right now. Reporters are acting surprised that some leading scientists were caught manipulating scientific literature to silence skeptics and dissenters. They convinced peers to knock skeptics' articles, journals to reject skeptics' papers, remove peers from paper review committees if they passed skeptics' papers, and even shut down journals that published dissenting views. Maybe even fudged their data.

Hey! Science is supposed to be awesome. It always eventually gets it right. Real science is about reproducible experiments and validated results. Actually, no, it is political. Like most other human endeavors.

• Galileo and other historical scientists were shut down by their community. Granted, their scientific peers were not basing their views on empirical data. But many modern scientists still base their views on what they've been taught, not what they've measured. This is understandable, you have to stand on the shoulders of giants to have time to make advances.
• Views are often validated by currently understood standards. If you plot the published speed of light against the year of publication, you will see sequences of flat spots where a value is almost identical to what was previously "measured". And then there is a jump; followed by another flat period of many years. Is this because they were using the same equipment and experimental procedure? Or because anyone that tried to publish a different "answer" was considered a skeptic and shut down? Again, this is understandable. Humans tend to try to be consistent, and not be antisocial and go against the crowd. It requires extra diligence to disprove a well respected master in their field. Like the great Einstein when quantum physics popped up. (Wait! Maybe God changes the real speed of light periodically as a joke!)
• Scientists are funded. Based on whether they get published or referenced. Or if they agree with the "sponsoring" corporation. So the system manipulates them into agreeing with the crowd. But the underbelly of the scientific community is less pretty than what we might have thought of as this kind of indirect pressure.
• Journals are funded. If the larger community of scientists don't subscribe to that journal offers, or schools or corporations pull their funding (or advertising!), a venue of dissent/questioning dies.
• I've seen public "attacks" during a presentation of research. In the form of a "question". Being honest, these questions are self-aggrandizing. E.g. "what makes you think that you are right when I have already published the opposite". It can embarrass a young scientist and discourage them from disagreeing in the future. Only the thick-skinned "crazies" keep at it. Like Tesla.
• I've been on paper review committees where papers are summarily discarded. There are so many that only one or two of the reviewers are assigned to read a given paper before the meeting. If they didn't understand it, or disagreed with the findings (based on their own experience/bias), it can get tossed very quickly. There are a lot to get through. Even when it is "marginal", the shepherding process can be taxing, discouraging a reviewer from volunteering. After all, they are contributing their expertise, but don't get their name on the paper. (Suggestion: maybe they should. If they pass something that proves incorrect, they lose points. As an incentive to get it right. Or would that discourage participation?). For "workshops" (not full Journals) an author's name is sometimes on the paper being reviewed, so their reputation is considered.
• As science get more "fine", some experiments cannot be reproduced except on the original equipment or by the original experts. Think CERN and supercolliders. (Or cold fusion?) Who has another billion dollars just to *reproduce* a result? Unless the larger community thinks a result is hogwash and feels motivated to pool their resources and dump on the results. So who is going to disagree? It almost sounds like a religion at that point.

I bet you've done the same things. Maybe at work. Tried to shut down "the competition". Competing for attention, or a raise, or recognition... You know what would be better? Listen to those that disagree and make sure they know you have heard them. They are trying to make the best decisions they can given their background. No one tries to make dumb decisions. If they are wrong, I'm sure they would appreciate learning something they don't know. Or, maybe they have something to teach you.

Imagine! Learning something from someone that disagrees with you and you find irritating. A dissenter. A skeptic. Seems like those that shut down dissent are not just closed minded, but unwilling to learn. Such a scientist should be embarrassed for themselves. Isn't IDEAL science supposed to be about discovery? Too bad that in reality there is so little ideal science, and so much science influenced by the politics of "real-life science".

Data Driven Entities and Rapid Iteration

It is clearly more difficult to develop content for an online game than a single player game. (For one, sometime entities you want to interact with aren't in your process). So starting with the right techniques and philosophies is critical. Then you need to add tools, a little magic and shake.

There are several hard problems you hit when developing and debugging an online game:

• Getting the game to fail at all. A lot of times bugs are timing related. Of course, once you ship it, to players it will seem like it happens all the time.
  
• Getting the same failure to happen twice is really hard. E.g. if the problem is caused by multiplayer interaction, how are you going to get all players or testers to redo exactly the same thing? And in the spirit of Hiesenbugs, if you attach a debugger or add logging, good luck getting it to fail under those new conditions
  
• Testing a fix is really hard, because you want to get the big distributed system back into the original state and test your fix. Did you happen to snapshot that state?
  
• Starting up a game can take a long time (content loading). Starting an online game takes even longer because it also includes deployment to multiple machines, remote restarting, loading some entities from a DB, logging in, ...
  
• If you are a novice content developer plagued by such a bug or a guy in QA trying to create repro steps to go along with the bug report, it will probably end badly.
  

Consequently, what do you need to do to make things palatable?

• Don't recompile your application after a "change". Doing that leads (on multiple machines) to shutdown, deploy, restart, "rewind" to the failure point. You'd like to have edit and continue of some sort. To do that, almost certainly you'd need a scripted language (or at least one that does just in time compilation, and understands edit and continue).
  
• Don't even restart your application. Even if you can avoid recompilation, it can take a loooong time to load up all the game assets. Especially early in production, your pipeline may not support optimized assets (e.g. packed files). For a persistent world, there can be an awful lot of entities stored in the database to load and recreate. Especially if you are working against a live or a snapshot of a live shard. At the very least, only load the assets you need.
• Yes, I'm talking about rapid iteration and hot loading. When you can limit most changes to data, there is no reason you can't leave everything running, and just load the assets that changed. In some cases when things change enough you might have to "reset" by clearing all assets from memory and reloading, but at least you didn't have to restart the server
  
• Rapid iteration is particularly fun on consoles, which often have painfully long deployment steps. Bear in mind that you don't have an editor in-game on a console, it is too clumsy. So the content you see in your editor on your workstation is just a "preview". You would swivel-chair to the console to see what it really looks like on-target.
  
• Try to make "everything" data driven. For example, you can specify the properties and behaviors of your entities in a tool and use a "bag of properties" kind of Entity in most cases. After things have settled down, you can optimize the most used ones, but during content development, there is a huge win to making things data-driven. Of course, there is nothing stopping you from doing both at once.
• Another benefit of a data-driven definition of an Entity is that it is so much easier to extract information needed to automatically create a database schema. Wouldn't you rather build a tool to do this than to teach your content developers how to write SQL?

Don't forget that most of the time and money in game development pours through the content editor GUIs. The more efficient you can make that, the more great content will appear. If you want to hire the best content developers, make your content development environment better than anyone else's.

That's not an MMO, its a...

Some people call almost anything "big" an MMO. Is facebook an MMO? Is a chess ladder an MMO? Is Pogo? Not to me.

What about iMob and all the art-swapped stuff by The Godfather on the iPhone? You have an account with one character. Your level/score persists, money, and which buttons you've press on the "quest" screen. As much as they want to call that an MMO, it is something else. Is it an RPG? Well, there is a character. But you don't even get to see him. Or are you a her?

These super-light-weight online games are not technically challenging. You can build one out of web-tech or some other transaction server. If you are all into optimizing a problem that scalable web services solved years ago, cool. Your company probably even makes money. But it doesn't push the envelope. Someone is going to eat your lunch.

Maybe I should have called this blog "Interesting Online Game Technologies".

Me? I want to build systems that let studios build the "hard" MMO's, like large seamless worlds. I don't want a landscape that only has WoW. If that tech were already available, we'd be seeing much lower budgets, more experimentation, games that are more fun, lower subscription fees, more diversity, and better content. All at the same time. I certainly don't want to build the underlying infrastructure over and over.

Of course, I'd love it if the tech solved all the hard problems so my team could build something truly advanced while still landing the funding. Unfortunately, today, people have to compromise. But maybe not for long.

What is software architecture (in 15 pages or less)?

Kruchten's "4+1 views of software archicture" is one of my favorite papers of all time. It shows four views of software architecture (logical/functional, process, implementation/development, and physical). The plus one is use-cases/scenarios.

Being 15 pages long, it is an incredibly efficient use of your time if you want to disentangle the different aspects of designing complex systems. And it gives you terminology for explaining what view of the system you mean, and which you have temporarily abstracted away.

Don't get hung up on the UML terminology:

• Logical is what is commonly refered to as a bubble diagram. What components are in your system and what are they responsible for?
• Process is which OS processes/threads will be running and how they communicate.
• Implementation is the files and libraries you used to build the system.
• Physical is your hardware and where you decided to map your processes.

http://en.wikipedia.org/wiki/4%2B1_Architectural_View_Model
I prefer the original paper: http://www.cs.ubc.ca/~gregor/teaching/papers/4+1view-architecture.pdf

Fail over is actually kind of hard (and expensive)

You are building a peer to peer or peered server small scale online game. There are players that purposely disconnect as soon as someone start beating them. They think their meta score will be better, or whatever. Or maybe they have a crappy internet connection. In any case, the master simulator/session host goes down abruptly; now what?

At least you would want to keep playing with the guys you've matched with; the rest of your clan or whatever. At best, you'd like to keep playing from exactly the point of the "failure" without noticing any hiccup (good luck). The steps to get session host migration/fail over to a new simulator:

• Restablish network interconnection
  
• Pick a new master simulator
• Coordinate with the Live Service about who is the master (or do this first)
  
• Have the entity data already there, or somehow gather it
• Convert replicated entities in to real owned/master entities
• Reestablish interest subscriptions, or whatever distributed configuration settings are needed
• "Unpause"

Some challenges:

• To reconnect, someone needs the complete list of IP/ports used by the players. But that is consider a security issue. E.g. someone could use that info to DOS attack an opponent. Let's assume the Live Service renegotiates and handshakes your way back into business.
• If you aren't connected, how do you elect a new master? If you don't have a master yet, how would all the clients (in a strict client/server network topology) know who to connect to? So the answer has to be precomputed. E.g. designate a backup simulator before there is a fault (maybe the earliest joiner, lowest ip address...)
• If your game session service supports this, it can solve both of the previous issues by exposing IP addresses only to the master simulator, and since it has a fixed network address, each client can always make a connection to it and be told who is the new master.
• If the authoritative data is lost on the fault, you may as well restart the level, go back to the lobby or whatever. So instead, you have to send the entity state data to the backup simulator(s) as you go. This is actually more data than is necessary to exchange for an online game that is not fault tolerant, since you'd have to send hidden and possibly temporary data for master Entities. Otherwise you couldn't completely reconstruct the dead Entities. There may be data that only existed on the master, so gathering it from the remaining clients isn't going to be a great solution. Spreading the responsibility is that much more complicated.
  
• So the backup master starts converting replicated Entities into authoritative Entities. Any Entities it didn't know about couldn't get recreated, so the backup master has to have a full set of Entities. Think about the bandwidth of that. You should really want this feature before just building it. Now we hit a hard problem. If the Entities being recreated had in-flight Behaviors (e.g. you were using coroutines to model behavior), they can't be reconstructed. It is prohibitively expensive to continuously replicate the Behavior execution context. So you wind up "resetting" the Entities, and hoping their OnRecreate behavior can get it running again. You may have a self-driven Behavior that reschedules itself periodically. Something has to restart that sequence. Another thing to worry about: did the backup simulator have a truly-consistent image of the entity states, or was anything missing or out of order? At best this is an approximation of the state on the original session host.
  
• Unless you are broadcasting all state everywhere, you are going to have to redo interest management subscriptions to realize bandwidth limitation. This is like a whole bunch of late-joining clients coming in. They would get a new copy of each entity state. Big flurry of messages, especially if you do this naively.
• Now you are ready to go. Notify the players, give them a count-down...FIRE!

What did we forget? What defines "dropped out"; a maximum unresponsiveness time? What if the "dead" simulator comes back right then? What if the network "partitioned"? Would you restart two replacement sessions? Do you deal with simultaneous dropouts (have you ever logged out when the server went down? I have.)?

Note that the problem gets a lot easier if all you support is clean handoff from a running master to the new master. Would that be good enough for your game.

So is it worth the complexity, the continuous extra bandwidth and load on the backup simulator? Just to get an approximate recreation? With enough work, and game design tweaking, you could probably get something acceptable. Maybe give everyone a flash-bang to mask any error.

Or maybe you just reset the level, or go back to the lobby to vote on the next map. And put the bad player on your ban list.

Me? I'd probably instead invest the time of my network and simulator guys in something else, like smoothness, fun gameplay, voice, performance. Or ship earlier.

Incremental release vs. sequel

(Warning: plenty of irony below, as usual)

There was a time when the MMO developer community thought that the ideal was to stand up your world, and then start feeding the dragon. As quickly as possible, get new content into the players hands. The more new content, the more fascinated they would be, the stickier their subscriptions would be and the more money you would make.

So we put a lot of effort into techniques to manage continuous development of content, test it, and roll it out with the minimum possible maintenance window. Some got good enough they could release content or patches every week. Didn't we have automated client patchers? Why not use those to continuously deliver content. Not just streaming content as you move around in virtual space, but as you move forward in real time.

Then someone noticed that Walmart took their game box off the shelf because it had been there for a year, and new titles were showing up. Surely consumers want the new stuff more? Besides, you don't need the latest release, you get all the new stuff when you patch. Then new subscriptions drop because of that lack of visibility at retail. Why would Gamestop sell prepaid cards if it is so easy to pay online?

So the light goes bing, and it is suddenly obvious that sequels would be a much better approach, since you'll get shelf space if it is a new SKU. Clearly this is the best approach, since it works so well for Blizzard. (So clearly, I cannot choose the glass in front of you. Where was I?) All you have to do is patch a few bugs, and set up a parallel team to work on the sequel.

But then everyone piles onto Steam. Definitely the end of brick and mortar. Maybe we go back to the low-latency content pipeline so our game is fresher than the sequel-only guys. But wait, Steam sales and free trials increase traffic at Gamestop.

Clearly, I cannot choose the glass in front of me... Wait til I get started.

Not really. As you can see, the point is that technologists are very unlikely to see the future of sales and distribution mechanisms. And if we did, it would take a year to adapt our development practices and product design to take optimal advantage of it.

The answer? Be flexible. Don't assume you've got the one and only magic bullet. Requirements change. And for an MMO the development timespan is large enough that a lot of things will change before you are finished. Don't implement your company into a corner with a big complex optimal single point solution, and keep your mind open.

Web tech for "game services"

I hold the opinion that every disagreement is a matter of different axioms, values or definitions.

I believe definitions is what is going on with this post by "Kressilac" (Derek Licciardi?):
http://blogs.elysianonline.com/blogs/derek/archive/2009/05/29/6400.aspx I'd guess we do hold the same values.

Derek argues that portions of an MMO server are suited to using and best implemented using web technology. I absolutely agree. I call these parts of the system "Game Services". Most would be accessed directly from the client. Examples:

• profanity filtering,
• shard status, open, full, down, locked, capped
• in game search/player online,
• clan/guild management,
• item trade,
• auction,
• voting/elections,
• chat,
• match making/lobby,
• leaderboards,
• persistent messages/email,
• reputation management/community services,
• in-game advertising
• Search,
• authentication,
  
• CSR account locking
• patching, streaming patching
• microtransactions
• petitions
• custom content
• character annotation, friend lists,
  
• knowledge base
• voice chat
• Maybe: inventory, quests, crafting (touches in-game entities)
  

Anyone got more for this list?

Most of these systems are "decorative" and are for the community aspects of the game.

The complication arises where the data managed by these services is affected by or used by the simulator (I.e. in-game logic). E.g. the number of members of your clan changes Mana recharge rate. I'd suggest that most of those kind of communications are not critical to be transactional or latency critical or can have the game design bent to accommodate that restriction.

There are a couple of those game services (especially those interacting with items) that are entangled. The easiest way to deal with those is to transfer ownership of the Entities in question to one system or the other such that there is no synchronization needed other than at the transfer. I'm betting that is how WoW does auctions and mailing of items.

My "run screaming; it sucks" article is my thinking about the core gameplay/simulator manipulated Entities. What Derek calls Real Time Data. To me that is the "hard problem". All the rest of the stuff can be handled by web-tech, and that is a solved problem (waves hand dismissively), and not so interesting.

Well. There are a few interesting issues, like coordinating authentication. But the coolest payoff (as Derek states) is that these things automatically become available offline via browsers, mobile devices, etc.

BTW, I'm working on another contentious article that more fully details the issues that drive my opinion about DB-centric game state management.

Google's Protocol Buffers (for messages and files?)

This is an interesting package:

http://code.google.com/apis/protocolbuffers/docs/overview.html


It can be used for on-the-wire and for file formats. It is much more efficient than XML, and has multiple language API’s (e.g. easier to send a message between apps of different languages). It deals with versioning, and has automated class and serialization code generation.


I haven't used it yet. Any thoughts? How good is it for archive files/pack files? How good is its historical version handling wrt up-converting or semantic changes (like feet to meters)?

Entity Concurrency

Ever since Simula and Demos in the 60's, object-oriented (or process-oriented) simulation has been considered the most natural and intuitive approach to representing a system. Certainly it is the way we think when we write programs using imperative languages (like C++), even when taking advantage of multithreading.

Over simplifying things, process oriented entities have a "main loop" which continues to be in scope, on the stack but possibly suspended even as the entity is idle or blocked waiting for something. An example would be a vehicle that stops at a red light. After the light goes green, the program continues with the next line of code (perhaps navigating to the nearest gas station). Conversly in an event-oriented simulation, the car would be unscheduled and the light would have to signal the car change its state from waiting to driving the next leg of the route. In the one case, the programmer can write all the code from the perspective of the entities (the vehicle, the light...). In the other, they write a soup of events and state changes that is very hard to visualize and see whether the logic is correct.

The easiect way to realize process oriented entities is to take advantage of coroutines built in the scripting language of your choice. Using a thread per object can get horribly expensive, even if they were cooperative threads. Using a coroutine allows a program to choose to block between two statements and go idle, context switching to another entity. When the resource being blocked on is available, the system can switch back to the suspended entity.

So the challenge is coordinating the objects. You can look at a previous article on bin/res for some ideas.

You can even have multiple concurrent activities running on an entity. E.g. monitoring your fuel level, driving a route, and listening for new orders from a taxi-dispatcher. Each would consume another coroutine. A complication here is that when a coroutine blocks and goes idle, the others might run and change the value of states in the entity. Fortunately this does not result in race conditions because coroutines are cooporative and only switch at a point that the programmer chooses. They can then be very aware that other processing might change things before they wake up again.

Coroutines can also be used to spread computation across multiple ticks without having to refactor the algorithm you are using. If you have a long AI or path planning algorithm, you could suspend at any point and resume during the next tick. The exact context is restored by the scripting language coroutine system. It might also make it easier to cancel such a computation at those suspend points.

When thinking about online games, load balancing is critical. We do it by migrating entities. But if an entity has a suspended context in a coroutine at the point you want to do the migration, things get harder. How do you pick up the stack context and reconstruct it on the target machine?

One way is to refuse to migrate until the entire context tears down (e.g. it returns to the "main loop"). Better would be to make use of the scripting language facilities to serialize and restore a coroutine. Various folks have shown that Stackless Python is capable of pickling an entity that has an outstanding context, and reconstructing it (either after a save/load, or after migration).

Has anyone tried "pickling" a coroutine in Lua? It's been on my todo list for a while. The question is whether references to (global) variables outside the coroutine can be "reattached" when it is unserialized on the other side. And what format is the coroutine "printed" and trasmitted as?

Off Topic: Most common solid waste?

OK. Weird thought... If you went to a landfill, what would be the most common solid waste you saw? A number of years back, a greeny asked that question and challenged people to go see for ourselves. It's been bugging me ever since. Here are some quick Googled results.

The most common waste product is paper (about 40 percent of the total). Other common components are: yard waste (green waste), plastics, metals, wood, glass and food waste. The composition of the municipal wastes can vary from region to region and from season to season. (U of Cal)

Paper, Organics (in Canada, from an Amazon "search inside" book)

Malaysia: Plastic waste is the most common solid waste that we generate in the country accounting for 7-12 percent by weight and 18-30 percent by volume of the total residential waste generated.

Throwaways (diapers) comprise 2 percent of the nation's solid waste by weight, making them the third most common solid waste item after newspapers and beverage and food containers. (diaper "activist" site, NY)

So "paper" is #1 and is quite recyclable, and energy rich. Plastic and organics too (possibly #2 and #3, if you include diapers; heh!).

Still doesn't answer what the "source" of the paper and plastic is. Fast food bags and wrappers? Retail boxes/packaging, grocery packaging, industrial/wholesale packaging? Books, junk mail, printouts?

I'd love to have a reference to a more detailed discussion of the source data. Not the reinterpreted-for-an-agenda summaries. And then make my own conclusions about reducing. (Maybe I should just look in *my* trash can at the end of the week).

Online Hard Problems

I've tried to keep a list of "hard problems" for online games. Sometimes it is to impress folks with how much work is involved in trying to build the technology itself (and redirect them toward middleware), and sometimes it is to remind me of how much work we have left as a middleware company. Here is my current collection. It is not every system needed, but the ones that are particularly tricky or challenging and require the right architectural decisions early. I'd appreciate if folks would add to this.

Hopefully, over time I'll be able to publish my conclusions about how to actually solve these problems. Many interact, and need a unified approach to be able to be solved at all.

Distributed and parallel nature

• Load balancing.
• Latency hiding.
  
• Timing, synchronization and ordering.
• Anticheating/security

Performance

• Threading,
  
• Execution performance,
• Memory performance,
  
• Network performance and message streaming,
• Persistence performance,
• Bandwidth reduction,
• Content streaming/background loading

Scale and seamlessness

• Scale for both casual and intensive styles (reusing the same infrastructure)
  
• Seamlessness at runtime
  
• Entity interaction across server "boundaries"
  
• Seamlessness at edit time
• Transactional entity interaction
• Shardless worlds
  

Ease of Use/Development/Operations

• Ease of use for designers, game developers (code and assets)
  
• Ease of developing large scale content
• Development efficiency and rapid iteration (assets and code),
• Fault tolerance, debuggability of large distributed system,
• Performance debugging,
• Script/behavior debugging, script/behavior ease of use,
• Hosting, operations ease of use (server deployment, control, monitoring, ...)
• In game microtransactions (security)
• Integration to multiple platform services
• Client deployment, patching, binary patching

Bin/Res process synch

Back in the 80's Graham Birtwistle developed Demos (ala Greek citizenry, not that canned thing the publisher is shown), a library extension to Simula. It is one of the earliest and most intuitive process-oriented simulation systems around. Here's one link:
http://cs.ubishops.ca/ljensen/simulation/sync.htm

There is a particular synchronization mechanism I have always liked about Demos. It is called bin/res. These are two queue-like objects that are most easily described as elements in an assembly line. A res is a resource that can be obtained and returned. (Yes, like a semaphore.) A bin is a collection into which items can be placed and removed. The items can contain arbitrary information.

What is interesting here is that when an entity pulls from a bin or a res when it is empty, the entity blocks until something becomes available. If an entity puts something into a bin or res that exceeds its configured maximum the producing entity blocks.

In process-oriented entity modeling, this is a great simple synchronization technique. In the middle of a complex bit of behavior logic, the Entity can block until something important happens.

Another cool thing about bin/res is that it has an event-oriented optimization. When an Entity is blocked, it inserts itself into an entity queue and blocks. When the other Entity changes the bin/res, it uses that queue to notify and wake up the blocked entity. This avoids all polling. It also works between processes using messages. That can be very important and useful in an online game.

Also note that bin/res can have a lot of other extensions. There can be multiple producers/consumers. The queues can be LIFO, FIFO or randomly serviced. And it is easy to put statistics like wait-times on them.

There are a million uses for bin/res. You can make your behavior scripts wait until some property reaches a desired value without polling. You can make two entities wait for each other before proceeding no matter what order they get to the staging area. You can deal with fairness and race conditions between multiple players. Any kind of queuing can be automatically flow controlled.

I've been a fan for almost 30 years. Ever since I came across Demos at University of Calgary. Hi Graham!

Smart pointer leak code worked

I have to brag on a prototype I finished last week. I'd mentioned previously a way to track smart pointer leaks. Well, I used a buddy's stack trace snapshot library and was able to inspect where in code all the smart pointers were set for an arbitrary object.



void LoggerTest::testInit()
{
void *temp = (void*)efd::GetLogger();
if (true) {
efd::SmartPointer thing;
thing = efd::GetLogger(); // assignment should be recorded here.

DarrinTestDumpStack(temp);
}
DarrinTestDumpStack(temp); // The reference above disappears in this printout.
}

And the output:
efd::SmartPointer::SmartPointer + 44
LoggerTest::testInit + 80 <<<<------ See, this was where I grabbed the ref. TestDescription_LoggerTest_testInit::runTest + 22 CxxTest::RealTestDescription::run + 67 CxxTest::TestRunner::runTest + 116 CxxTest::TestRunner::runSuite + 170 CxxTest::TestRunner::runWorld + 172 CxxTest::TestRunner::runAllTests + 80 CxxTest::ErrorFormatter::run + 21 main + 106 __tmainCRTStartup + 424 mainCRTStartup + 15 efd::LoggerSingleton::Initialize + 459 <<<<------ See. This is the only other reference (the factory). InitializeTestApp + 300 EEGlobalFixture::setUpWorld + 22 CxxTest::RealWorldDescription::setUp + 94 CxxTest::TestRunner::runWorld + 103 CxxTest::TestRunner::runAllTests + 80 CxxTest::ErrorFormatter::run + 21 main + 106 __tmainCRTStartup + 424 mainCRTStartup + 15 RegisterWaitForInputIdle + 73 0xffffffffcccccccc *************************************************************** Second dump (only the factory reference is left): efd::LoggerSingleton::Initialize + 459 InitializeTestApp + 300 EEGlobalFixture::setUpWorld + 22 CxxTest::RealWorldDescription::setUp + 94 CxxTest::TestRunner::runWorld + 103 CxxTest::TestRunner::runAllTests + 80 CxxTest::ErrorFormatter::run + 21 main + 106 __tmainCRTStartup + 424 mainCRTStartup + 15 RegisterWaitForInputIdle + 73 0xffffffffcccccccc

Adaptive/Dynamic Categorization

Any static partitioning of data flows using a static algorithm (like a geometric grid) will break down. Either due to something intrinsic, or because the players are evil, and delight in ignoring your simplifying assumptions.

So for stability and performance/scale reasons a categorization policy that is dynamic will be better. Periodically a centralized or distributed computation can inspect the in-use categories and determine whether there is a better mapping.

Imagine there was a flash-crowd come to see an epic battle. The initial mapping had that area mapped to one category. The area can be split into two area and given two distinct categories. At a specific point in time, the new mapping will be instituted. Call that the next epoch. We need to do that across all users of those categories. The easiest way would be to broadcast the new mapping. Once all participants have acknowledged they have the new mapping and re-subscribe using that mapping, producers can start using the new categories. Once all participants have acknowledged adopting the new mapping, the old categories can be unsubscribed from.

There are many interesting dynamic categorization policies. They are based on live measurement of the system as the game is being played. The new categorization is then applied live. Clearly this can provide better efficiency than offline analysis and updating a static mapping, since in-game patterns can change minute to minute.

• Split and merge geometric grid cells or triangles. This is how many mmo systems work today, so if that is your preference you can keep it while migrating to using categories.
• Compute "nearness" between producers and consumers, and identify clusters of entities. The set of entities identified is given a category. As entities move around, they subscribe to other clusters of entities. Once the interconnections become too "stretched", a new clustering can be computed. There are pretty simple clustering algorithms, such as inspecting R-squared for an Entity against various proposed clusters to find the nearest one inside some threshold. Note that this approach can be applied to individual entities incrementally as they move.
  
• A similar clustering algorithm can be applied to actual communication patterns as opposed to assuming that geometric nearness always indicates high interaction rates. The recategorization system would record and analyze metrics of interactions as they change in real time.
• The hosting software can detect overloads of various resources, and indicate to the recategorization system that splitting off instances of busy areas would be valuable (assuming your game design supports that approach).
• As dungeons or PvP arenas are spawned, a new set of categories especially for the players involved will be computed and used. Because the subscribers indicate which instance they are currently assigned to, the categorization policy will compute the Categories for that instance, and a player will not see anything from a different instance.
• A game may have unique capabilities like being able to add, remove or move land masses. As coordinate systems drift around, the categorization policy would need to take this into account. It may be able to do that using relative coordinates, or it may need to completely recategorize space.
• Changes in team or guild size may trigger recategorization.
  
• As a clarification, in contrast to dynamic categorization, consider this scenario: As density increases in an area, the policy can adjust the maximum sight distance. While this doesn't directly change the decomposition of the data, it will result in fewer categories being consumed. (This is really a subscription policy change, not a categorization policy change)

Really, the key thing is to consider that real time feedback can be used to help improve the data distribution performance of your system.

Obviously an algorithmic policy is better than an enumerated one, since distributing new parameters to factor into a computation requires less data than a complete enumeration of the descriptions for each category.

Like almost any distributed computation, recategorization can benefit from incremental changes. Local measurements and performance triggers can instigate a categorization change to just a few mappings, and may be able to be distributed to only a few machines. These incremental changes can quickly ripple through the category space and come to an approximately optimal mapping. One benefit of the incremental approach over the periodic approach is that the trigger to recompute can be an event as opposed to a polling of metrics and a recomputation that may have limited or no effect.

Static Categorization Policy

A Static Categorization policy is one that partitions the data flows in an online game using a fixed function (usually a function of the values of the data being partitioned). The algorithm used does not change, and the tuning values do not change during gameplay. The performance of the system is determined by the designer during development testing. There are many examples:

• A 2-d grid with infinite altitude. Any entity in a grid cell transmits to the associated category. Any entity that can see into that grid cell subscribes to that category. And the grid size does not change. This can lead to lots of categories (not a real problem if your categorization implementation is designed for that), too many entities in a cell (if the cells are tuned too large), too many subscription changes (if the cells are too small). Etc.
  
• Variations of the grid approach include non-uniform grids (quad-trees), or arbitrary polygon "tiling".
  
• The designer could identify rooms, or spaces between rendering portals. Each would be assigned a unique category, and all data within them would be grouped. Only when near doors would a consumer subscribe to more than one category.
  
• FPS engines have used BSP trees to optimize rendering and visibility (and auditory effects) calculations (e.g. http://developer.valvesoftware.com/wiki/BSP_Map_Optimization) Whether automatically computed ahead of time or defined with hints, these 3-d volumes could have a category each. It is easy to query the data structure to determine the category corresponding to the current position. Doing an approximate spherical or convex volume query of the BSP tree should also be easy for consumers to find all their needed categories.
  
• Data limited to team, quest party, or clan can be separated each into its own category. A consumer (client) always knows which "entity set" they are in, so can determine where to publish and where to consume. Same with chat channels.
  
• Chat channels are interesting in that you may want to use a 3rd party chat infrastructure, but use in-game position or group membership to determine connectivity. Categories can be very useful for that, or if you want, could be used to route chat through the game engine. That way gameplay mechanics could affect chat (jamming, ambient "noise", battery charge, ...)

Again, all these are considered static because the algorithm and tuning do not change. If something gets overloaded there is no recourse to retune at runtime. Best you can do is change the policy in the next patch.

Note that membership is dynamic, however. That is how the system is able to limit what data is received (for security and bandwidth reduction), but still get everything that is needed to the right consumers.

Dynamic categorization is even more fun, but has some interesting challenges. More next time.

Subscribing ahead

Interest management is the process of delivering interesting data to those interested. An entity ensures that its sensor model has all the correct entities available to it by subscribing to the set of categories known to contain those entities. That subscription fills the local cache with replicas of the interesting entities. Then the sensor can be implemented to immediately query the cache knowing that it contains accurate data.

The policy the application uses to fill the cache can be as simple as a grid, or as complex as a dynamically determined set of clusters of nearby entities. In either case, the consumer knows the category being used by any entities that might be within the consumer's area of interest, field of view, line of sight, range of hearing or what not. Note that the producer generally produces into a single category.

So now producers send updates, and interested consumers get them. But what if someone moves? They will change the category they produce into, or the set of categories they consume from. But what about latency? That is where it gets "fun". A consumer can use its maximum velocity and an estimate of subscription latency to compute the extra distance needed to guarantee that the cache contains those moving entities even when the producer and consumer are moving toward each other at maximum velocity. That will ensure that its cache is populated with any entities that will-be interesting in a few moments. The cache will necessarily have more entities than are logically visible, so the sensor algorithm must filter out ones that are too far away but have been delivered "just in case".

But what about producers that are moving? We use latency hiding and bandwidth optimization to reduce the number of updates being sent, and then predict where the producer is at the current time. But that increases the latency of the produced data. OK. We increase the subscription range even farther. But you have to factor in the producer's maximum velocity. And you don't know what type of entity it is. So you have to use the maximum velocity of the fastest entity in the game.

That can suck if there are a few jet fighters, but tons of infantry. The solution? Separate the fast movers from the slow movers and use two distinct "layers" of categories. You would subscribe out quite a bit further for fast movers, but wouldn't get any slow movers in that wide subscription because they are produced into a different layer. And there won't be very many fast movers to consume. If you think about it, there is just no way to consume all the data from fast movers that are far away and might suddenly move toward you if there are a lot of them. The worst case example is an entity that can teleport anywhere instantly. Consumers would have to be subscribed to everything. Or you would have to change the game design to hide the latency from subscribing on-demand (like making a poof of smoke, or invulnerable just after teleport, or something).

The beauty of category based subscription is that these game-specific factors can be reduced to a set of integer values that can be computed by both producer and consumer. The consumer doesn't need to know that there are entities in the interesting category. If there are, the publish/subscribe system will deliver them. All that system does is match up integer values: hey this thing goes to these guys. The system doesn't need to assume that the categories are related to geometry, or that they are a linear function, or anything. You can use them as sets. Or unique addresses for multi-point to point communication, or for radio broadcasts on a single station. Or anything.

But my point: you have to use prediction to reduce bandwidth. But you also have to use prediction when subscribing or might miss something "interesting".

Why would you want gateway boxes?

An important aspect of an MMO shard is where and how clients connect. My preference is to have a set of Gateway boxes that responsible for managing those connections. Their responsibilities include:

• Authentication handshakes with the client and account system
• Rapid filtering of malicious traffic (IP filtering or more), denial of service attacks, smurfing (billions of identical, apparently innocuous/legal requests), and so on
• Separation of responsibility. This is valuable in a memory and cache efficiency sense, in that a single machine is focusing on just one thing. Simulators don't have to keep track of clients. They only connect to GW boxes.
• Instead of N clients each connecting to up to K simulators (N*K connections), you have only N client connections, each to only one of J gateways and the K simulators only connect to the J gateways (N+J*K). Since N is much bigger than J, this is a huge advantage both in connection count, connection management processing overhead, and memory on both client and server hosts. Normally N is quite a bit bigger than J (say 4 times).
  
• Message exploding and the majority of connections are happening in the data center over high speed switches, and in a secure environment on the backend switch.
  
• By focusing only on GW functions, and not running game logic, they can be made much more reliable than simulator boxes/processes. This can help a lot with player experience during fault recovery
  
• The Gateway boxes are the only ones with public IP addresses, so it allows a large fraction of your shard to be secure by having no direct route from the WAN. The idea here is GW boxes have (at least) two NICs, one on the switch with the main firewall, the other on the backend network.
  
• This also has physical network topology benefits, since the back end hosts can be on their own switch.
• Message header overhead is reduced when sending to a client, since all data to one client is from a single shard host, and it can do bundling for over the WAN messages (most important).
• Gateways can also "be" the lobby or character selector prior to entering the game world.
• Non simulation messages like chat or game service stuff (auctions, guild management, email, patching/streaming of content, ...) don't bother the simulators.
• The sizing and configuration to optimize for the size of your peak player connections are now independent of that for the simulators and load balancing.
  

I also subscribe to the philosophy of persistent client connections (or with connectionless protocols, staying with one assigned gateway). The major benefit of this is that a client does not have to reauthenticate and renegotiate their connection with another host in the shard when their character moves around in the world, or some other load balancing activity changes the simulators they need to interact with.

To do this, the GW is also responsible for routing messages between the client and the simulators that are "of interest". This gets back to category based routing and channel managers discussed earlier. Data from multiple simulators is sent to the GW box and forwarded to each interested client.

Data from the client tends to be routed to the one Simulator that client is currently using. I.e. the one that owns its "controller" entity where client requests are validated, and (normally) their player character is owned/simulated.

You want multiple gateway processes (not multi threaded) per gateway box to avoid losing as many player connections if something should crash (and then reauthenticating, etc). This also helps deal with file descriptor limitations per process for the connections if your OS configuration limits you.

There are downsides, but not overwhelming:

• An extra hop for most messages. This hop is on a datacenter switch, and will be very fast.
• There are extra machines to buy. Well, not really, the same message handling work is being done but not directly by the simulators, so they can get more done each (and that has other more subtle communcation benefits). We just partition it, and use the same number of machines.
• An extra switch and extra NICs. You can use two VLANs on any decent switch, if you have to.
  

In summary, you are just moving some work from one place to another in the same sized shard, but getting a lot of system simplicity, security, and communication benefits.

Peer to What?

Ever notice how people use exactly the same word to make an important differentiation? Shorthand, laziness, different backgrounds, or maliciousness?

So in our industry what do people really mean, or think they mean when they ask "Hey. Does that support peer to peer?" Here are a couple of definitions and more clear terminology that I prefer. Maybe I can find some sources to back me up. BTW, I'm thinking of small-scale online today. Although many/most of my architectural biases apply here as well. (Other than whether the server is hosted or not).

Academically speaking, peer-to-peer is a communication topology that, in general, indicates that clients or players communicate directly with each other. Like peer-to-peer file sharing. It is used in contrast with the client-server topology where each client has a single connection to the server, and any interaction between clients is performed by means of the server. One benefit of the peer to peer topology is that data can move between clients with one hop of latency instead of two. One benefit of client-server is that each client can be presented the same data in the same order (deterministically).

However, many people are less concerned with whether two clients communicate directly, but instead use the term peer-to-peer to indicate they desire other features:

1. There is no part of the game hosted in a central location like a data center. Note that central-server or authoritative-server is not the same thing as hosted-server.
   
2. There is no stand-alone server that needs to be stood up ahead of time, possibly occupying another piece of hardware. When the player starts their client, the multiplayer game is automatically ready to go. There is no separate server process consuming extra resources on one of the user's machine.
   
3. There is no single point of failure in the distributed system. If the master (usually the first player to start) were to drop out of the game, there is no reason for the remaining players to go through matchmaking again.

It turns out that a client-server topology can be used and still achieve all three of the above features. Obviously, "hosted" or not in #1 is easy. Just run the server on someone's machine. The long-running server in #2 is easy. Either start one up and shut it down when the client is started or stopped, or you join someone else's game session. Or if you are resource constrained (like on a console), and can't abide the second process, make a dual-purpose client. The first player in would have their client become the master/authoritative server. #3 requires a little bit of technology. When the master drops out of the game, another of the clients must become the master, and the other clients connect directly to them. This gets a little tricky in a non-uniform network, but it is a problem that is solvable with automatable algorithms, so the players don't know that it is happening.

So even if you have some of the three problems above, you don't have to jump to the conclusion that client-server is therefore not approprite. And given how much easier it is to get a system running that assumes there is a single authoritative server, I'd recommend you look into it, and prove (ie. measure) whether you have an intractible problem with client server.

In the mean time, I'm going to continue to be skeptical when folks say "I need peer-to-peer". My question will be "what feature of peer-to-peer do you think you need?". My "favorite" topology for small scale non-hosted multiplayer is what I call "peered-server" to contrast it to hosted-server. Client server communication topology, single authoritative simulator, no central persistent hosted server process (other than a match maker, which is not the same thing as a simulator).

Really, the thing to keep in mind is that the process communication topology does not have to equate to the network communication topology. It could be a little more efficient if they match, but could be a lot harder to get your project finished.

How to ignore most emails (safely)

At work, I use Outlook. It has "organization" tools. One of the best is found here: View/ArrangeBy/Custom/AutomaticFormatting. It gives you a set of conditions and formatting for each line in the list view. I use the default of unread mail formatting with a bold font.

1) I use my favorite font color for emails that are sent only to me: select "where I am:" "the only person on the To line". Even if others are CC'd on this email, it was sent directly to you. You'd better read it. No one else will.

2) My second favorite font color for emails sent specifically to me (and others): select "where I am:" "on the To line with other people". Someone took the time to direct this email directly to you and some of your peers. You should probably read it. Maybe one of your peers will respond, but you never know.

3) My third favorite font color for emails that I was specifically CC'd on: select "where I am:" "on the CC line with other people." (also covers where you were the only person on the cc line). Someone took the time to include you on the thread, but you know it is FYI (for your information) only, so you can almost certainly ignore it without getting in trouble, or until you have some time. This allows you to decide based on the subject line, for example. Many #3's turn into someone else's thread, and I can get by with skimming only a couple of those.

4) My least favorite color is "all the rest", and will be the default formating. These will almost always be delivered to you because you are on an email group. These can almost always be ignored for several days. If you happen to be on one or two where that is not the case, make a custom rule to highlight these. If you are on a ton of groups that each need immediate attention, you are probably doing something else wrong that I can't give you emperical advice about. I know I wouldn't survive long under that kind of stress. Don't borrow that kind of trouble. Seriously consider whether your response in those forums is honestly needed so urgently. I'l bet if you ignore it and you are the only one that can respond, you are eventually going to get a #1 or #2 email on it.

I also use a custom font color for "followup" emails that I have specifically marked as needing my attention later. Not only do they show up as red, but they sort to the "bottom" of my list view (I read my list like a console window scrolls.

I don't empty my inbox. I think that is "busy work", and just puts important items out of view in other mail boxes where I wind up forgetting about them. I only open half or 2/3rds of my emails, and only when I decide I have time. I'll flip the window open (left on list view) and see if there are any #1's and then just close it. That means almost half my emails are left in the "bold" state, and I don't feel guilty about that. Those are emails that were broadcast, not sent "to" me expecting me to solve a problem. They were FYI to me. If it was an important broadcast, it probably had the "high priority" flag set.

I also use the preview window and set auto-read on (marks the item as read if you "preview" it for more than a few seconds). If I get the sense I need to read this more carefully or later, I'll manually flip it to unread so it stands out and I'll reevaluate it later.

These tricks work well in meetings when you think you need to glance at your queued emails, or any other time when you are very pressed for time. A simple glance at the font colors gets you focused on the one or two emails you should look inside. Often there is little or nothing to do with even those, so mark them unread for when you have a block of time to "clear" the backlog.

What does a "Flexible" architecture look like?

We've all heard the maxim that the only constant is change. This is true on a lot of levels. During the development of a title, the designer is going to come up with some doozies..."Hey, what if the player controls the character *and* his minions?" Maybe it is an important change, but if you have a big complicated (and maybe purpose-built) MMO system, things like that can give you nightmares.

So even if you know (or think that you know) what the game is going to look like, 3-5 years down the road, it won't, and you'll have a lot of difficult refactoring if you don't plan for change. Put in insulation layers so that big changes don't propagate very far. For example, don't assume you are going to be using SQL, and start coding Entity behaviors with embedded queries. Instead, define a persistence interface that could be implemented by any number of technologies. Maybe it starts as a flat file, or an XML DB. But by the time you go live, Microsoft bought your company and they want the DB on SQL Server. And while we are talking about the DB, don't *ever* talk to the DB with a synchronous query that blocks gameplay. You might be surprised by the variance in response times even a good Oracle DB will give. My horror story: chances were 50:50 that when we deployed a new version on TSO that had a schema change, that the DBA's would migrate the data in some hand-cobbled way. And (get this) an index file would disappear. Things looked ok until you got a few hundred live customers connected.

Where was I? Insulation. An architecture that can withstand or localize pretty radical changes is simultaneously flexible. You can use the parts in different ways, or replace things you don't like. And when you replace them the change doesn't ripple very far. I'm arguing you need to do this even for a purpose-build MMO-engine, so doing the same thing for a middleware MMO engine results in no net impact on performance or usability. And since a middleware developer wants to sell their engine to studios doing a variety of titles, that flexibility is required just to make the sale.

I like to think about sitting across from a hard-nosed tech-lead in a sales meeting who absolutely *NEEDS* a certain feature that we don't have. I can say: no, we didn't do that, but its flexible, and you can swap that peice out. They can start with what we have, and do the swap out if they have time; which I cynically think doesn't happen very often. When have you had "extra" time during development? Well, at least we made the sale. Its a lot better than saying no we don't do that, our way is more efficient, and it will be wicked-hard to change. OK, I have to share this too: GDC '07 or '06, I heard Tim Sweeny say: "Modularity is overrated". Makes you wonder why folks love to hate developing with Unreal.

How do you create insulation? Look into PIMPL (pointer to implementation) or Interfaces (pure virtual base classes) to hide all implementation detail from users of a module. Make the modules loosely coupled. Don't assume too much about ordering or synchronous interaction between modules. One of my favorite patterns is the publish/subscribe or producer/consumer pattern. One module sends a message that is categorized, and has no idea who might consume it. Modules that want that data or notification subscribe ahead of time, and run a handler when that message is sent. Now you can add new modules without even recompiling the sender code, much less adding a compile-time dependency. Turns out this approach is good for improved compile times too.

Loose coupling between software modules is really great. Take it to the next step, and avoid (run screaming from?) synchronous interaction between processes. E.g. I wouldn't use CORBA. Too easy to create deadlocks. Instead, prefer sending an asynchronous message. Don't use critical sections in blocks of code, or locks on all kinds of data structures. Too easy to create deadlocks. Instead prefer sending an asynchronous message.

I see a pattern developing here. It leads to the ability to map logical processes to other threads or other remote processes with very little change to your code. The event-oriented, message-based approach to distributed systems is very successful. I guess I've already talked about CSP (Communicating Sequention Processes) in an early post, so I'll just drift off.

Never Too Many Asserts

My friend Keisuke says an assert is like a circuit breaker. It does no harm to be in the circuit when things are operating normally. But when the voltage goes out of bounds, your program stops.

We all accept that a defect costs more to fix the later it is discovered. If you have already checked in, it affects your coworkers. If you have already shipped you will have to go through a new release or public patch. The tenets of extreme programming are that if something is good, taking it to an extreme is probably better. So if we catch a defect in an assert while we are actually developing nothing could be better. If our coworkers "protect" their modules with asserts, we can be more confident that our use of their stuff is legitimate. And we can go faster, and have a more reliable system.

I like to use a number of different kinds of asserts:

• External Interface (ASSERT_EI): validates that the parameters to a method that is expected to be used by other major modules or by the customer are legal and in range. But they should not be used to validate user input. This is a super-critical assert. The more of these the better.
  
• Internal Interface (ASSERT_II): validates the parameters to methods that exist for good code structure and are intended for use only within the current module. Private methods would use these. They are for defensive programming, and reminding yourself what your assumptions were when you designed this method. They can provide a kind of documentation. These are less important than ASSERT_EI, but are great for debugging old code that you don't remember very well or that you didn't write. Again, the hope is that you can go faster. What if you took a short cut, and haven't finished a method for one use case. You can leave an assert such that if you accidentally use the method that way, you will obviously be reminded of the missing work, as opposed to having the method silently do nothing, or fail with some bizzare side effect.
• Internal Consistency (ASSERT_IC): validates that the state of a class remains consistent as it is manipulated. It is an invariant check. The design of your module makes assumptions about its data structures (e.g. an data item is in a list only once). Assert this periodically. I like to add a SanityCheck method to almost every class I build. It executes all the invariant checks I can think of (and yes, it can be pretty slow). It is especially useful to sprinkle around if you are currently tracking down a bug. It makes sense to verify your invariants going into and out of a method. Centralizing those invariants in a SanityCheck function can be pretty useful.
  
• External Consistency (ASSERT_EC): I don't use this very much, since nicely modular systems should not have tight interdependencies. For example, your module may be dependent on the configuration file being parsed before it is initialized. An ASSERT_EC can check (and document) that assumption.

I've seen game programmers take a couple of positions against asserts:

• They slow down the execution of debug builds so much that the app becomes unusable. OK. It really is too slow. There should be easy ways to disable the asserts especially in heavily executed bits of code. In fact, one should think twice about putting asserts inside tight loops. Also, your assert implementation should be able to runtime skip the predicate based on runtime configuration files, and do it fairly efficiently (e.g. check a global boolean). Disabling per module would be a good start. Providing a level-of-detail argument to the asserts should be possible.
  
• I keep having to skip some assert in someone else's code that I don't understand, and that interferes with my workflow. Everyone should be careful not to use asserts to remind us of work that needs doing. Some other mechanism should be used. Or wrap those checks in a per-developer ifdef. On the other hand, if a developer is hitting asserts they don't understand, maybe they are breaking code they don't understand. Using either comments or change-control software, a developer should find the auther of the assert, and learn about that bit of the system, or get them to change the assert if it is now obviated.
  
• I changed one little thing and all these asserts starting going off. This one is pretty funny. Given that the asserts are there for a reason, there is a pretty good chance that the one little change had much further reaching implications than expected. For example: someone now wants to handle a member being NULL. But ASSERT_IC's start going off that the member shouldn't be NULL. The thing is, if the rest of the class was built assuming that member can never be NULL, it could easily derefernce the pointer without checking. An argument that "it should have checked for NULL" doesn't fly. The assumption was built in.

Adopting these "extreme" uses of asserts might even take the place of unit tests for that class.

In Game "Transactions"

There are times when two players (or even other kinds of Entities) need to trade an object or perform some other action that is critical to occur transactionally. Generally, this is meant to mean that no matter what kind of error occurs, the transaction occurred or did not occur. E.g. I paid you 10K, and got a gold bar.

Support for transactions needs to work across server hosts. It is a very disruptive experience to be able to interact in one spot, but not 2 feet to the left. You have to assume that the players can purposely crash one or the other host at the worst possible point in the interaction (like Byzantine Generals). Assuming you can trust you database, the idea is simply to get both sides of the interaction saved to the DB simultaneously (i.e. in one DB transaction).

What if the two Entities are on different hosts? You have to simultaneously change remote variables and get the persistence request from two places to the DB, blah, blah, distributed handshake, Byzantine...brain fry. They do this in Cobal for banking systems. How hard can it be? Well it is too hard to be worth it (if you include failure/backout/retry, etc), even if you think it would be a fun challenge.

So here is a fantastic consequence of the non-geometric load balancing mechanism we've been talking about. Each simulator is single threaded (if you use multiple threads, you have multiple simulators). An Entity Behavior will execute without preemption. So straight-line code will run to completion, a DB save request can occur, and all is good. All you need to do is get both Entities onto the same simulator, and run that straightline code and co-persist the two local Entities (i.e. send the db save request with both entity's states). Boom. Done. Either the transaction makes it to disk or it doesn't. Not just half. This scenario is the origin of a lot of dupe bugs you've heard about.

The fact that migration policy and mechanism are separate means that adding a new policy is easy. E.g. migrate the guy I'm about to interact with over here (or me over there). Once it finishes, the transactional behavior can be scheduled. If things are a little crazy, it may take a while, but it won't fail and start giving away money. And it won't tell the user the transaction succeeded when it didn't.

Clearly, this is not something you want to do all the time. It would be too slow. Just for the stuff that *really* matters to the users.

If you don't like the thought of your Entities migrating around, build an Escrow Entity. Place one side of the transaction into it and copersist. Migrate to the other side, place the other half in and copersist. Move out the half, persist, migrate, move out the other half, persist, done. If there is a failure at any point, the Escrow object is known about by the DB and it can continue, or return the goods. Just like a Lawyer, but not as expensive.

Either of these approaches can support multi-Entity Transactions.

Networking Resource

Here's an article with lots of links to classic networking techniques:
http://gafferongames.com/2009/01/25/game-networking-resources/

Here are some research papers leaning toward large scale issues:
http://maggotranch.com/biblio.html

Entity Migration Mechanism

From earlier posts, we see that to achieve scalability, we need:

• large numbers of simulators
• an ability to load balance based on load (not just geography)
• an authoritative simulator to avoid DB bottlenecks
• a single-write paradigm to avoid overly complex synchronization

And since our world scales with the number of Entities, not the number of functions in the game, then load balancing, and thus, scalability is realized using Entity migration.

Setting aside the policy and impetus for initiating an Entity migration, lets talk about the mechanics. By separating policy and mechanism, we can experiment or customize the policy to use application-specific information, resulting in a closer to optimal solution. And we won't have to reimplement the mechanism each time.

We know we can run an Entity on any host by using interest management as discussed earlier to feed an Entity everything it needs to operate correctly. So all we really need to realize a migration is:

• getting the Entity state onto the new host
• getting the data flowing to that host that is needed by that Entity
• doing this quickly enough that there are no hiccups visible to the players
• avoid all ordering and race conditions so there is no game logic difference compared to not migrating (no side effects)
  
• survive crashes of any component at the worst possible moment (i.e. preserve important transactionality) without significant impact to the players

First, we use a data-driven means to identify which state variables need to be transferred to the new host. There is no reason to transfer truly temporary variables, but there are reasons to transmit variables that are not needed in the persistent database. E.g. current target. There are many mechanisms to serialize an entity and reconstitute it. One challenging aspect is whether to transfer the execution context (e.g. the stack and program counter) if your simulator uses coroutines to support blocking and waiting in a Behavior script. For example, Stackless Python is famous for pickling coroutines and reconstituting them.

There is a handshake needed to get this state across:

• suspend further execution of the entity so things don't change during the migration
• transmit the state
• recreate the entity on the target host
• resume execution of the entity.
  

Seems simple, but consider that update messages to players from the original and destination host might get out of order, the DB request queue might get backed up on the source (after all you are migrating away from a busy simulator) and save requests to the DB might get out of order, replicated state on the source and target might be at different versions (the entity may see a neighbor jump backward or forward in time).

So we need to add some steps:

• Get the target subscriptions set up and acknowledged before the transfer so when the Entity arrives, all data is available there that it had in its original location
• Have the original simulator "flush" its DB queue so the DB never sees out of order persistence requests, and then stop persisting that entity until after the migration.
  
• increment an "epoch" counter to allow us to discard any replication messages or requests from the past
• Given the increase in time and complexity, it may be worth optimizing the process by pre-loading the target host without actually pausing the original entity. Then once everything is set up, resend states that may have changed during the preload. Of course, you might also make use of any state that was previously replicated to the target.
  

There a quite a few trick available and needed to get this to come out right and be efficient. But distributed transactions like this happen reliably in a lot of "critical" systems in other industries so it is quite solvable. You can see how the need for migration and the requirement to do it quickly without player-visible hitches requires us to adopt many of the design principles already accepted: authoritative simulator, interest management, data-driven persistence and replication traits describing entity state variables, ... All of these key features are intertwined, so if your systems goes off track somewhere there, you may be buying a lot trouble elsewhere.

One of the coolest features of interest management is that you can choose to not migrate and the game still runs the same (but may use more datacenter-only networking). So if you can't migrate an entity until it finishes a behavior (because you can't migrate your stack), no problem, just wait. Program that into your policy. If you find that hitches are visible but only when a player is in a heavy combat situation, your policy can delay initiating the migration until the participants have been quiescent for a while.

Debugging leaked references

Everyone likes using smart pointers and reference counting to manage the lifetime of objects that are passed through modular interfaces. They can avoid a lot of copying and callers don't have to read a lot of documentation to figure out if they are responsible for deleting the object.

One big problem with using ref counted objects is when they "leak". It is extremely difficult to debug what code has taken an extra reference to an object that you think should have a single remaining reference. Why didn't this object destroy itself when I cleared this "last" smart pointer? When an object is passed through many layers and stored in various containers, there can be quite a few increment/decrement references occurring, so putting in breakpoints is not very useful. I have found this to be one of the most difficult and tedious problems to fix in a large application like a game.

Regular memory leak detectors are not too useful, since they just say "it leaked", not why. What you really want to know is the location of every outstanding reference to a block that you think should have already been deleted. You can ask this question at the end of a run on the unexpectedly outstanding blocks, or in the middle of a run when you have found something strange and want to backtrack.

It is "easy" but not much use getting the memory address of every smart pointer that points at the problem object. Make multi-map keyed on object addresses. Each time you assign or clear a smart pointer (increment or decrement a reference on an object), modify that map to include or exclude the address of that smart pointer. Done.

Making this "useful" is a matter of recording information about each smart pointer for later logging. Ideally, you would record a partial stack trace so you can see where the smart pointer was affected and what caused that. This requires another chunk of data beyond the smart pointer's memory location.

If you are only concerned about extra references, you could probably get away with recording the stack trace only on addRef. Note that for each smart pointer, there is only a single outstanding reference, so you only need the one stack trace per smart pointer.

If you have a situation where you have too many decRefs, you may need to record the stack trace of each addRef and decRef for the broken object. Garbage collecting that data is going to be interesting, because you can never be sure when an extra decRef might happen.

Putting this together, you can use regular memory leak detection to identying unexpectedly outstanding ref counted objects. Then ask this ref count debugging system for the stack trace(s) of the where the smart pointers where initialized that are still holding a reference to that object.

What is a memory leak and why do we care?

I am a big fan of Purify. It is a tool that helps programmers deal with the challenging memory systems of C and C++ . In those languages, we can "leak" memory.

We try to get rid of all the leaks (usually a few days before we ship). I've seen this take quite a lot of effort. Superficially, it seems like wasted effort since modern operating systems keep track of your memory and recover it when your processes exits. So, really, we could just exit and kill the process. The app would shut down a whole lot faster.

Why does that sound like such a bad idea? Why do we even care about leaks?

• We don't want to have our process use more resources than it needs. It could crash or make other apps unhappy.
• It makes for higher quality software. We are strictly disciplined about who owns what.
• Managing the scope/lifetime of an object is occasionally very important. For example, we may be holding some I/O that needs to be flushed.
  

There are two competing definitions of leak. Obviously I like the Purify definition better. I'm going to argue that the other (more common) definition is an oversimplification and a compromise:

• Precise: a leak is an allocated block of memory that you don't have a pointer to anymore. So you can't ever delete it. A potential leak is one where you only have a pointer to an address somewhere in the middle of the block. This might happen if you do some funky pointer arithmetic, and intend to undo it to later delete the block. Anything else is referred to as an in-use allocation.
• Traditional: a leak is a block that is still allocated (outstanding) when the application shuts down.

Most custom memory allocators use the traditional definition, because developers have no good way of providing the more precise definition. They require the application writer to build good quality code that carefully deletes all the memory it allocates such that none is left outstanding at the end of execution. Certainly that definition subsumes the Precise definition. The traditional definition is saying there are no leaks, potential leaks, nor outstanding allocations. Nothing. Period. How can you argue with that?

The tools used are simple. They keep track of outstanding allocations, but don't and can't subtract precise leaks. They have neat ways of showing where the memory was allocated, and so on. The app writer finds all those outstanding allocations and carefully clears them as the application shuts down.

But you don't super-need-to clear the in-use memory. It is not hurting anything. You could delete it any time, if you really wanted to (sounds like an addict). OK. There is one way it can hurt something. You could accidentally have lists or free-lists that bloat up and it will look like you really are using that memory. However, since it is in-use, you should be able to instrument your lists as watch them bloat up.

You do super-need-to clear precise leaks. They are caused by overwriting or clearing your pointers without doing the deallocate first. If you don't plug those leaks, you are going to sink, or crash, or lose oil pressure or air pressure, or some other analogy.

How could Purify possibly differentiate between precise leaks and in-use? Believe it or not, it watches every pointer assignment. And sees when the last reference to a block is lost. It does this with something called Object Code Instrumentation, so it doesn't care what compiler you are using. It inserts assembly code into your executable (e.g. around assignments), fixes up jumps and symbol addresses it changes when making room for the inserted code. It consequently knows what you have done or accidentally done to every pointer (including nasty things with pointer math).

As a result it can focus the coders attention on blocks that are unreferencable. It can even (theoretically) throw a breakpoint at the instruction that overwrites the pointer. I know it can break at the instruction where you read an uninitialized variable. At any point during debugging, you can make a call and have it dump unreferencable blocks of memory and where they were allocated. Of course you can also dump all in-use blocks by calling a function when paused in the debugger. I believe you can make a checkpoint and then later dump all blocks that are in-use that were allocated since the checkpoint.

If you insert some code in your custom allocator, the Purify SDK can even use your allocator to do its magic. You could make calls to it at run time to dump metrics or react to issues.

As you can see, unreferencable blocks are the real leaks. We only have to clear out all in-use blocks because we don't use tools like Purify, and have overreact and compromise. I don't like the busy work of clearing every last legitimate in-use block. I don't think I should have-to-have-to. (As long as I'm careful about my "other" resources like I/O buffers.) It makes for better code if I do, but if I want to trade time for quality or one feature for another, I still have to clear the real leaks, and like the option of ignoring the other blocks swept up by the tradition definition.

It has a bunch of other cool stuff too. Like knowing when you access memory that is uninitialized, or already deallocated. It knows when you run off the end of an array. It can instrument third party object code even if you don't have source, and it doesn't use your allocator.

Of course there is a runtime performance hit, but it isn't super bad. And you can control which modules are instrumented, so you might exclude your rendering for example.

It has a UI that integrates to Visual Studio and gives you a nice report of these various kinds of memory errors at the end of your run, or whenever you ask. It will even take you to the offending line of code.

Don't balk at the price either. Just remember the amount of time the poor guy spent that was stuck with clear every last in-use block. It more than pays for itself very quickly.

The Manifesto of Multithreading (for High Performance)

This document is a statement of principles that Emergent software developers adhere to concerning issues of concurrency, parallelism, multiprocessing and multithreading.
Related Docs:

• http://twiki.emergent.net/bin/view/ServerDev/ServerProcessModel
• http://cache-www.intel.com/cd/00/00/05/15/51534_developing_multithreaded_applications.pdf (Great comments on Granularity in section 3.2. Add comments on dynamic agglomeration.)
• Communicating Sequential Processes, C. A. R. Hoare. http://www.usingcsp.com/
• http://en.wikipedia.org/wiki/Von_Neumann_architecture

Principles:

• Multi-threading on a single processor is beneficial only in rare circumstances such as when we expect a program to block repeatedly, such as doing I/O.
• When concerned about performance, this is unlikely to be the case, so we should see only one or two threads created per core.
  
• Operating system context switching between threads can be very expensive. It involves saving and loading processor state, tends to result in complete cache invalidation, and most expensively entails updating of OS process management data structures. For systems that provide virtual memory, reprogramming the MMU and swapping out kernel resources such as file pointers can make switching even more expensive. Some system calls can force a scheduling quantum to end.
• Avoid context switching by keeping the number of threads low. Avoid system calls.
• Decompose the problem into large segments to minimize the number of context switches and total overhead. This is most easily done by decomposing into as many pieces as possible, then using a policy to agglomerate them back into large sequential computations.
• Reducing the number of threads will make the job of an SMP OS scheduler trivial and inexpensive. Ideally it could map a thread to a processor and leave it there indefinitely. Any load balancing needed can be accomplished by the application using app-specific knowledge without affecting the number of threads and their scheduling.
• The measure of efficiency of using available multiprocessors is determined by how much processing time is wasted or spent idle.
• For ease of measurement and tuning, an application should avoid consuming as much processing as possible, but should try to consume as little as possible, then idle, making inefficiencies much more visible.
• Never use a spin lock.
• Idle time of this sort can be filled by work scheduled to be done on processors that are already fully utilized or overloaded. This is the reason for load balancing and is one component of thread scheduling.
• Processors interfere with each other’s efficiency when accessing shared data. This happens directly if the other processor hits a lock that is already acquired. If the blocked thread suspends, another thread on that processor may be able to take over. But that adds a context switch on top of the lock check. Mutual exclusion (mutex) mechanisms and other atomic instructions cause cache flushes on remote processors, or lock the entire memory bus. These costs are hidden when doing performance analysis since they don’t affect the requestor, and are not attributable to any single instruction on the remote processor (other than as apparently “spontaneous” cache misses). Even storage barriers used in out of order memory access modes can add overhead from cache effects.
• Avoid the need for shared data. Either partition the data so it is exclusively used by one processor, or hand off entire blocks of data to a processor so the data has a single-writer at any one time.
• Minimize the number of interactions with shared objects, as each interaction bears an overhead. This relates to the (TBD) agglomeration policy mechanism discussed above.
• Even computations that only read data owned/written to by another thread concurrently must be guarded.
• In some cases managing a replica of the data for remote readers will simplify programming (removing the need for the guards), and have other benefits similar to double buffering such as removing a serial sequencing.
• Guarding disjoint blocks of code with a critical section mutex mechanism is error prone because the coordination code is not collocated. Overly conservative exclusion will impact performance. Surprising interactions (side-effects or reading shared objects) can lead to errors/races.
• Avoid code-based mutual exclusion (critical sections) for commonly/widely accessed systems. If it is the “only” approach, consider centralizing it (e.g. single reader and writer), as opposed to requiring almost every method of an object to grab the mutex.
• Consider whether the object being guarded must be a singleton or can be replicated per thread (in which case, no exclusion is required).
• Don’t confuse thread exclusion with reentrancy.
• Locks on data or code blocks that require more than one resource to be locked can lead to deadlocks, or priority inversion or self-blocking. If the deadlock is of low probability, it may not be observed in testing. Even though some consider it easy to detect and fix a deadlock, they are very risky since it is so hard to guarantee they don’t exist.
• If you find yourself resolving conflicts from multiple locks, it is time to redesign the system.
• Lock contention tends to not gracefully degrade in terms of performance and fairness/starvation. More sophisticated locking is required such as a ticket mutex for fairness. Simpler locks consume even more resources, mask their caller’s logical idleness, and cause memory performance side effects as threads busily contend for the lock.
• Avoid high contention resources. Duplicate them, or rethink whether they are as shared as you think.
• In the spirit of CSP (Communicating Sequential Processes), assign the ownership of the resource to a single thread and use message communication to access it.
• Before devising a more sophisticated and special purpose mechanism or data structure to address the high contention, reconsider the larger problem. Often a more coarse approach using CSP will fit better with the rest of the system. The task to be parallelized may not turn out to significantly contribute to overall performance. Optimize globally.
• Scheduling preemption should not be relied on to provide performance. Each forced context switch is an unwanted overhead. Near 100% of the CPU can be used by a single thread that has enough load assigned to it. Preemption should only be used for rarely invoked latency sensitive functions like I/O or for long running low priority background processing where the preemption rate can be very low.

Guidance:
Hoare’s Communicating Sequential Processes (CSP) can be used to solve any concurrency problem (any concurrent computation can be realized/reimplemented as CSP) and has a very easily understood mental model. A logical process (LP) contains its own state variables and performs computation concurrently to other LPs. LPs interact only via messages whose content and ownership is atomically transferred as it is sent.

By leaving the computation sequential, and avoiding all concurrency within each sequential process, algorithm development returns to the familiar Von Neumann Architecture. This approach is better for our customers as we do not require them to be concurrency experts when coding. It is better for Emergent since not all the developers need to be aware of the concurrency consequences in various systems they are less familiar with. Performance analysis becomes trivial, since algorithms are sequential, and message queuing can be analyzed to inspect workload. Critical paths and idealized parallelism analysis of the communication graph can be used to determine if a better load balance is possible, or if the problem itself needs to be further decomposed to realize a performance gain, or if more processors would improve performance.

• A thread is treated as a CSP logic process. While it may share a single address space with other threads, by policy it does not share any writeable (and ideally, any readable) data.
• The only point of concurrency is the message queue. A message with its content belongs to one logical process xor another.
• A large amount of data that needs to be “shared” among threads is handed off in a message. Copying can be avoided by using a pointer in the message to the transferring data and adopting the policy that the data “belongs” to the message once it is attached, and belongs to the target logical process once it arrives. This effectively uses SMP shared memory as a communication medium.
• The principles of CSP apply equally well in a multi-threaded shared-memory environment as in a multi-process SMP, in a NUMA or in a distributed processing environment. This future-proofs our software and allows reconfiguration and performance tuning by changing policies without rewriting code. This addresses application design and load changes as it evolves.
• Minimizing the number of LPs reduces context switch overhead but requires better load balancing algorithms. A good static balance based on the expected application behavior can extract quite a lot of CPU capability, especially when the workload does not fluctuate very much over time. This should be a design goal even without considering concurrency to avoid frame rate jitter. Dynamic load balancing can use recent history to predict a better near term balance. However, to do this there is work-migration overhead. This takes the form of per-task “global” scheduling onto available processors (less desirable as this is a continuing cost), or periodic analysis, extracting and transferring workload between LPs. Note that in most cases it is not worth the effort of eking out the last amount of performance with sophisticated load balancing techniques.
• Mapping similar work to an LP increases the likelihood of instruction cache hits. So when agglomerating small tasks, create large lists of similar tasks as opposed to doling them out round-robin.
• Always optimize at the end. Getting perfect parallelism out of a system that is only 10% of the application computation is probably a waste of effort.

Other Concerns
Note that strict CSP suffers from communication overhead. For systems which are extremely fine-grained and latency sensitive, a custom approach might be considered if the extra work and risk are justified. But it should be sufficiently encapsulated to avoid having its tradeoffs unknowingly cause performance side effects elsewhere.

Concurrency for utility reasons like background loading can also benefit from techniques used for high performance concurrency, but being less performance sensitive, the benefit is primarily in reuse of common facilities and ease of development.

The CSP focused approach and infrastructure can be reused trivially to implement most kinds of parallelism: functional parallelism, data parallelism, master/worker thread parallelism, pipelined parallelism, etc. It is not appropriate for very fine grained parallelism such as parallel loops, or SIMD computation but that should be rarely needed when considering the application as a whole.