With the recent emergence of top grossing real time games in the East (Honour of Kings) and West (Clash Royale, Golf Clash, etc) - the doors have opened for new genres of social games on mobile. However, building a real time multiplayer game for mobile comes with many interesting technical and design challenges. Join us in this session to see how the team at Space Ape Games is approaching these challenges head on with the help of Akka and AWS.

1. Scalability & Big Data challenges in
Real-Time Multiplayer
games

2. Real-Time games in Top 100 Grossing (2017)
2014
2015
2016
2017
(3)
(6)
(8)
(13)
2018 ???

3. Enabling Factors
Source: PC Mag

4. Enabling Factors
Source: OpenSignal

5. Enabling Factors

6. QUIZ TIME: In 2017, which of these games
has made the most revenue?
The world’s most popular
MOBA on PC
The world’s most popular
First Person Shooter
Some game by Blizzard
Some game by EA
A Chinese 5v5 mobile
game you never hear of
Some game by King

7. The world’s most popular
MOBA on PC
The world’s most popular
First Person Shooter
Some game by Blizzard
Some game by EA
A Chinese 5v5 mobile
game you never heard of
Some game by King
QUIZ TIME: In 2017, which of these games
has made the most revenue?

8. >$400M Monthly Revenue
Source: Bloomberg
>80M DAU
Source: Tencent

10. 10-20 inputs/s, sensitive to lags (> 300ms)

11. unpredictable network, limited bandwidth

13. Decisions, decisions...
Build vs Buy?
Self-hosted vs Cloud?
Global deployment vs Centralized?
TCP vs UDP?
Server Authoritative vs Lock-Step?

14. Constraints/Trade-offs
Latency (RTT)
Cost
Complexity
Scalability
Operational overhead

15. Global Deployment
vs
Centralised

18. 10-20 inputs/s, sensitive to lags (> 300ms)

21. optimize for this

22. Global Deployment
● Players are geo-routed to closest multiplayer server.
● Matched with other players in the same geo-region for best UX.
● No need for players to “choose server”, it should just work.

23. Global Deployment
● Should leaderboards be global or regional?
● Should guilds/alliances be global or regional?
● Should chatrooms be global or regional?
● Should liveops events be global or regional?
● Should players be allowed to play with others in another region?
ie. play with distant relatives/friends.
● Should players be allowed to switch default region?
eg. moved to Europe after Brexit

24. Server Authoritative
vs
Lock-Step

25. Server Authoritative
● Server decides game logic.
● Client sends all inputs to server.
● Client receives game state (either full, or delta) from server.

26. Server Authoritative
● Server decides game logic.
● Client sends all inputs to server.
● Client receives game state (either full, or delta) from server.
● Client keeps internal state for game world, which mirrors server state.
● Client doesn’t modify world state directly, only display with some
prediction to mask network latency.

27. Client 1 Client 2Server
C1 control 1 C2 control 1
game state 1

28. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
game state 1
game state 2

29. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
game state 1
game state 2

30. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
game state 1
game state 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 3
C1 control 1
C2 control 1
C2 control 2
C2 control 3

31. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
game state 1
game state 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 4

32. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
game state 1
game state 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 4

33. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
game state 1
game state 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 5
C2 control 3
game state 4

34. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
game state 1
game state 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 3
C1 control 1
C2 control 1
C2 control 2
game state 5
C2 control 3
game state 4

36. Pros
● Always in-sync.
● Hard to cheat - no memory hacks, etc.
● Easy (and quick) to join mid-match.
● Server can detect lagged/DC’d client and take over with AI.

37. Cons
● High server load.
● High bandwidth usage.
● Synchronization on the client is complicated.
● Little experience in the company with server-side .Net stack.
(bus factor of 1)
● .NetCore was/is still a moving target.

38. high server load and
bandwidth needs
client has to receive
more data

39. Lock-Step*
● Client sends all inputs to server.
● Server collects all inputs, and buffers them.
● Server sends all buffered inputs to all clients X times a second.
* traditional RTS games tend to use peer-to-peer model

40. Lock-Step*
● Client sends all inputs to server.
● Server collects all inputs, and buffers them.
● Server sends all buffered inputs to all clients X times a second.
● Client executes all inputs in the same order.
● Because everyone is 'guaranteed' to have executed the same input at
the same frame in the same order, we get synchronicity.
● Use prediction to mask network latency.
* traditional RTS games tend to use peer-to-peer model

41. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
C1 control 1
C2 control 1
C2 control 2
C1 control 1
C2 control 1
C2 control 2
C2 control 3
inputs, instead
of game state

42. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
C1 control 1
C2 control 1
C2 control 2
C1 control 1
C2 control 1
C2 control 2
C2 control 3
RTT: time between sending an input
to receiving it back from server

43. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
C1 control 1
C2 control 1
C2 control 2
C1 control 1
C2 control 1
C2 control 2
C2 control 3

44. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
C1 control 1
C2 control 1
C2 control 2
C1 control 1
C2 control 1
C2 control 2
C2 control 3
RTT
frame time

45. Client 1 Client 2Server
C1 control 1 C2 control 1
C2 control 2
C2 control 3
C1 control 1
C2 control 1
C2 control 2
C1 control 1
C2 control 1
C2 control 2
C2 control 3
RTT
frame time
RTT = latency x 2 + X
Xmin = 0, Xmax = frame time

47. Pros
● Light server load.
● Lower bandwidth usage.
● Simpler server implementation.

48. Cons
● Needs deterministic game engine.
● Unity has long-standing determinism problem with floating point.
● Hackable, requires some form of server-side validation.
● All clients must take over lagged/DC’d client with AI.
● Slower to join mid-match, need to process all inputs.
● Need to ensure all clients in a match are compatible.

49. fix-point math,
server validation, ...

52. bandwidth

53. Build vs Buy

55. Pros
● Easy to use.
● Already use it for prototype games.
● Multi-region, lobby, etc. come out-of-the-box.
● Had a long time to optimize their solution.

56. Cons
● Quite expensive, pay for provisioned peak monthly CCU.
● “can we bet the future of our company on a third-party?”.
● Unknown global distribution at scale
● Accessibility of support.
● Limited extensibility.
● Runs on Windows.

57. So, we decided to build our
own networking stack

58. +

59. A model for describing computation, coined by
Carl Hewitt & co in 1973.
Later popularised by Erlang.
Actor Model
Carl Hewitt

60. Everything is an actor.
Every actor has a mailbox.
An actor is the fundamental unit that embodies
the 3 essential things for computation:
● processing
● storage
● communications
Actor Model

61. Actors don’t share memory, they communicate
only via messages.
When an actor receives a message, it can:
● create new actors
● send messages to other actors
● do work
Actor Model

62. Actors don’t share memory, they communicate
only via messages.
When an actor receives a message, it can:
● create new actors
● send messages to other actors
● do work
Actor Model Johnny?
Not sharing memory prevents cascade failures when an actor crashes.

64. Ericsson AXD301

65. Inside an actor, messages are processed one-at-a-time, in a
single-threaded fashion.
No need for locks!
Actor Model
single-threaded

66. Inside an actor, messages are processed one-at-a-time, in a
single-threaded fashion.
No need for locks!
Simplifies concurrency, no deadlocks, race conditions, etc.
Actor Model
single-threaded

67. Lifts concurrency management to the mailbox.
Allows you to “think globally, but act locally”.
Actor Model

68. Lifts concurrency management to the mailbox.
Allows you to “think globally, but act locally”.
Easier to think about a complex system in terms of states and
transitions, than to manage state mutations.
Actor Model

69. MATCH 1
C1 input
C2 input
current frame history
frame 1
frame 2
frame 3
buffering

70. connection open
MATCH 1
C1 input
C2 input
current frame history
frame 1
frame 2
frame 3
buffering

71. connection open
authenticate
MATCH 1
C1 input
C2 input
current frame history
frame 1
frame 2
frame 3C3 joined
buffering

72. connection open
authenticate
send/receive
MATCH 1
C1 input
C2 input
current frame history
frame 1
frame 2
frame 3C3 joined
buffering

73. MATCH 1
C1 input
C2 input
current frame history
frame 1
frame 2
frame 3C3 joined
C3 input
connection open
authenticate
send/receive
buffering

74. MATCH 1
C1 input
C2 input
current frame history
frame 1
frame 2
frame 3C3 joined
C3 input
connection open
authenticate
send/receive
buffering
broadcast!

75. MATCH 1
current frame history
frame 1
frame 2
frame 3
C1 input
C2 input
C3 joined
C3 input
connection open
authenticate
send/receive
buffering
broadcast!

76. MATCH 1
current frame history
frame 1
frame 2
frame 3
frame 4
connection open
authenticate
send/receive
buffering
broadcast!

77. MATCH 1
current frame history
frame 1
frame 2
frame 3
frame 4
connection open
authenticate
send/receive
buffering
broadcast!
C3 input

79. concurrency

80. MATCH 1
current frame history
frame 1
frame 2
frame 3
...
C1 input
C2 input
C3 joined
C3 input
connection open
authenticate
send/receive
buffering
broadcast!
C1 input

81. MATCH 1
current frame history
frame 1
frame 2
frame 3
...
C1 input
C2 input
C3 joined
C3 input
buffering
broadcast!
C1 input
C2 input

82. MATCH MATCH MATCH MATCH MATCH

83. MATCH MATCH MATCH MATCH MATCH
MATCH MATCH MATCH MATCH MATCH

84. MATCH MATCH MATCH MATCH MATCH
MATCH MATCH MATCH MATCH MATCH
MATCH MATCH MATCH MATCH MATCH

85. MATCH
C1 input
C2 input
current frame history
frame 1
frame 2
frame 3C3 joined
connection open
authenticate
send/receive
buffering
broadcast!

86. MATCH
C1 input
C2 input
current frame history
frame 1
frame 2
frame 3C3 joined
connection open
authenticate
send/receive
buffering
broadcast!

87. MATCH
current frame history
frame 1
frame 2
frame 3
C1 input
C2 input
C3 joined
Socket
actor
Match
actor

88. MATCH
current frame history
frame 1
frame 2
frame 3
C1 input
C2 input
C3 joined
Root Aggregate
Socket
actor
Match
actor

89. MATCH
current frame history
frame 1
frame 2
frame 3
C1 input
C2 input
C3 joined
Root Aggregate
Socket
actor
Match
actor

90. MATCH
current frame history
frame 1
frame 2
frame 3
C1 input
C2 input
C3 joined

91. MATCH
current frame history
frame 1
frame 2
frame 3
C1 input
C2 input
C3 joined
C3 joined
act locally
think globally
how actors interact with each other
aka, the “protocol”

94. the secret to building high
performance systems is simplicity
complexity kills performance

95. Higher CCU per server
Fewer servers
Lower cost
Less operational overhead
Performance Matters

96. We should forget about small
efficiencies, say about 97% of the
time: premature optimization is
the root of all evil. Yet we should
not pass up our opportunities in
that critical 3%.
Performance Matters

97. We should forget about small
efficiencies, say about 97% of the
time: premature optimization is
the root of all evil. Yet we should
not pass up our opportunities in
that critical 3%.
Performance Matters

98. Threads are heavy OS constructs.
Each thread is allocated 1MB stack space by default.
Context Switching is expensive at scale.
Actors are cheap.
Actor system can optimise use of threads to minimise context switching.
Actor Model
>

99. Non-blocking I/O framework for JVM.
Highly performant.
Simplifies implementation of socket servers (TCP/ UDP).
UDP support is “meh”...
Netty

100. Custom network protocol (bandwidth).
Buffer pooling (GC pressure).
Minimise Netty object creations (GC pressure).
Using direct buffers (GC pressure).
Disable Nagle's algorithm (latency).
Epoll.
Performance Tuning

101. AWS Lambda functions to run bot clients (written with Akka):
● Cheaper
● Faster to boot up
● Easy to update
Each Lambda invocation could simulate up to 100 bots.
Automated Load Testing

104. from US-EAST (Lambda)
to EU-WEST (game server)

105. optimize for tail latencies
from US-EAST (Lambda)
to EU-WEST (game server)

106. http://bit.ly/2xgGHXZ

107. Thank You!

108. QUESTIONS?