Transcript LUDWIGMAXIMILIANSUNIVERSITY MUNICH DEPARTMENT INSTITUTE FOR INFORMATICS DATABASE SYSTEMS GROUP Managing and Mining Spatio-Temporal Data in Massive Multiplayer Online Games Matthias Schubert joined work with Hans-Peter Kriegel and Andreas Züfle Lehrstuhl für Datenbanksysteme Institut für Informatik Ludwig-Maximilians-Universität.

LUDWIGMAXIMILIANSUNIVERSITY
MUNICH
DEPARTMENT
INSTITUTE FOR
INFORMATICS
DATABASE
SYSTEMS
GROUP
Managing and Mining
Spatio-Temporal Data in
Massive Multiplayer Online Games
Matthias Schubert
joined work with
Hans-Peter Kriegel and Andreas Züfle
Lehrstuhl für Datenbanksysteme
Institut für Informatik
Ludwig-Maximilians-Universität München
DATABASE
SYSTEMS
GROUP
Outlook
1. Spatio-Temporal Research
and Computer Games
2. Managing Spatio-Temporal Game Data
3. Mining Game Data
1. Detecting Cheaters
2. Evaluating Game Balance
4. Conclusions
05.11.2015
2
DATABASE
SYSTEMS
GROUP
Spatio-Temporal Game Data
• Player avatars or units move within a
virtual spatio-temporal environment
• A game server has to manage a unique
valid representation of the game state
• Movement and timing are essential
aspects of most games
• Similarity to other spatio-temporal
applications:
traffic management, simulations,
surveillance systems etc.
05.11.2015
3
DATABASE
SYSTEMS
GROUP
Why do research for Computer Games ?
• Computer games are big business
(market volume 2010:
gaming industry approx. 74 billion USD,
relational databases approx. 20 billion USD)
• There is data:
spatial objects, events,
trajectories, flocks,
• There are applications: Modeling computer
controlled entities, manage servers, analyze
players, detect cheaters
• It’s fun
05.11.2015
4
Why is research interesting for
companies ?
DATABASE
SYSTEMS
GROUP
• Trends in computer games:
–
–
–
–
stand alone games -> Online Games
1-10 players -> massive multi-player (1000+)
Console/PC -> Mobiles, Browsers ..
purchase price -> subscriptions , micro transactions.
Preview of the Diablo III auction house using real money
•
Implications:
– Games need distributed network technologies: Servers, P2P,
synchronization, large data volumes, user management, spatial query
processing
– New threats: cheating, account hijacking, hacking…
– New challenges: keep people investing time and money
05.11.2015
5
Management Challenges
DATABASE
SYSTEMS
GROUP
• Game Servers are high throughput
– several thousand position updates in a tick (ca. 100 ms)
– low jitter: a tick is required to take 100ms at most not on average
• Large Games have to be distributed
–
–
–
–
05.11.2015
a single server cannot maintain enough players
number of possible interactions increase quadratically
Distributing players depends on their spatial positions
fixed zoning via dynamic server relocation
6
Management Challenges
DATABASE
SYSTEMS
GROUP
• Persistency is mandatory
• parts of the game state must be stored permanently
• server must manage all relevant data (no local save games)
• saving the game state must be done without extending tick
processing times
(disk updates must be distributed over time several ticks)
• Temporal Synchronization
• low dependency on heterogeneous connection latencies
• temporal uncertainty: Where is player A when her last position update
arrived 2s ago.
• reduce transferred data volume while maintaining a fluent game play
(e.g. employ dead reckoning)
05.11.2015
7
Mining Game Data
DATABASE
SYSTEMS
GROUP
Analyzing the player behavior to
1. Detect Cheating
• Bots (Programs playing the game for you: Farm bot)
• Hacks (Modifications of the game client: Speed hack)
• Exploits (Flaws in the game allowing unintended
advantages: positions allowing to attack but not being
attacked)
2. Evaluate Game Balance
• Maintain a challenging but non-frustrating game play
• Maintain a fair chance of winning for different character
or faction types.
05.11.2015
8
Why do players cheat?
DATABASE
SYSTEMS
GROUP
• economical reasons
– Sell ingame money or goods for real money:
poker bots, goldfarming, account trading, item trading..:
– Example: playerauctions.com
– Over $1 billion USD in accumulated player-to-player trading value
– Over 25,000 average daily transactions (nearly 20 per minute)
– Over 700 supported Massively Multi-Player Online Games
– Over 30 million accumulative transactions
05.11.2015
9
DATABASE
SYSTEMS
GROUP
Why do players cheat?
• Saving Time:
Example: AFK bots are self-running programs doing simple gaming tasks
without user interactions like collecting ore or herbs.
• Prestige:
Having success is often coupled with high prestige in the gaming
community. Example: Reaching Masters League in Starcraft II
• Fun:
Winning the game is simply fun even without the satisfaction that the
success is well deserved
All types and motivations are a problem because
• the gaming companies directly loses money (micro transactions)
• the game becomes less attractive to other players which might quit
(no fair competition)
05.11.2015
10
DATABASE
SYSTEMS
GROUP
Monitoring Cheats
Challenges:
• game state maintains current entity states
but: analyzing behavior requires recent states as well
• monitoring might strain server resources
• checking all player actions for a reasonable time period requires a lot of
processing overhead
• checking should be as generic as possible
(use rather outlier detection than supervized methods)
• cheating players still have to be penalized (e.g. temporary ban)
05.11.2015
11
DATABASE
SYSTEMS
GROUP
Data Mining and Balancing
challenges:
• detect interesting events like boss
encounters in the logs
• monitor encounter results
• estimate player strength to remove the
bias from statistics
• formalize and cluster encounter tactics
=> More than one successful strategy
indicates interesting game play
• use text mining on community web sites to
measure player happiness
05.11.2015
12
DATABASE
SYSTEMS
GROUP
Conclusions
• Computer games are an interesting application area
• many games rely on a spatio-temporal virtual environment
which is similar to monitoring and tracking systems
• Recent developments will increase the need for managing
and mining techniques
• New challenges arise in real-time spatial querying, updating,
persistency and server distribution
• Cheat dection is a challenging task w.r.t. detection rates and
throughput
• Checking game fairness is statistically challenging
• Measuring game difficulty and diversity requires combined
consideration of game logs and community feedback
05.11.2015
13
DATABASE
SYSTEMS
GROUP
Join us on
MAMIVE‘11
1st International Workshop on Managing and
Mining Virtual Environments
In conjunction with ACM SIGSPATIAL GIS
in Chicago November the 1st, 2011
(Submission deadline September the 2nd)
05.11.2015
14