CS4344 Lecture 10: Player Dynamics
-
Upload
wei-tsang-ooi -
Category
Technology
-
view
600 -
download
5
Transcript of CS4344 Lecture 10: Player Dynamics
Characterizing Virtual Population in Games
1
World of Warcraft
2
Use an add-on written in Lua
3
monitor 1100 random players
over 71 days
4
median num of players per poll vs time of the day polled
5
CDF of all session length, and median session length of each player
6
sufficiently long session length good for P2P games
7
8
can use level to predict session length?
9
CDF of median downtimes andmedian session length of each player
10
Availability of players (time online/total time)in February 2007
11
12
13
monitor 3 locations
Stormwind CityStanglehorn ValeBurning Steppes
14
15
can use zone to predict session length?
16
density: num of players* in a zone
*: out of 1100 players tracked
17
Mean Location density of 117 locations
18
Difference in Density between Dec and Feb
19
20
dynamic load balancing not needed?
21
“My life is so great that I literally wanted a second one!”- Dwight Schrute, The Office
22
256x256 m regions.
23
24
25
26
27
avatar mobility:who is where, when
28
why do we care?
29
research in systems support for NVE
30
31
How to partition a world into regions and assign regions to servers considering
- communication cost- hand-over rate- balancing server load :
32
33
How to predict avatar movement (end therefore what a user will see next)?
34
35
AoI-based scheme
36
How many connections?
How stable are the connections?
37
supernode-based scheme
38
How to pick supernodes?
How stable are the supernodes?
39
how to simulate avatar mobility?
40
random walkrandom waypoint
clustered movement:
41
or, small-scale
implementation
42
no large-scale NVE available until recently
43
482,594residents logged in between 2-9 June 2008
44
secondlife.com/whatis/economy-graphs.php
45
• collect mobility traces of avatars in Second Life
• what it means w.r.t. systems design for NVEs?
46
collecting traces
47
how do avatars move inside a distributed
virtual environment?
48
how are avatars distributed within a
region?
49
how long do they stay at a location?
50
do they move in groups?
51
etc.
52
FPS MMORPG NVE
53
Linden, can we get access to the server traces?
No.
54
• Wrote our own client
• Parses packets using libsecondlife
• Insert bots into regions
• Log positions of avatars every 10s
55
difficulties
56
running out of memory
57
anti-bots policy
58
over crowded region
59
inter-region tracking
60
• Wrote our own client
• Parses packets using libsecondlife
• Insert bots into regions
• Log positions of avatars every 10s
61
who is where, when
(doing what)
62
63
Freebies
64
The Pharm
65
Isis
66
Ross
67
Mobility Patterns
68
Freebies: number of visits to a cell
69
Freebies: average pause time in a cell
70
Freebies: average speed in a cell
71
Isis: number of visits to a cell
72
caching/prefetching based on popularity of
locations?
73
Isis: average pause time in a cell
74
pick supernodes from sticky location?
75
Isis: average speed in a cell
76
mobility model:random walk +
pathway ?
77
churn rate
78
79
80
Reasonably high churn (up to 6/min)
81
1 min 10 min
1 hr 2 hr
Highly skewed. Some stay for hours.
82
cannot pick supernodes uniformly
83
clustering of avatars
84
meeting: encounter between two avatars
(within each other AoI)
85
Meet many different avatars.
86
1 min
10 min
1 hr
2 hr
Most meetings are short.
87
Meeting size is large.
88
high overhead in maintaining AoI
neighbors
89
meeting stability:
avg meeting sizeover
num of avatars met
90
Wide range of stability
91
other tidbits
92
little temporal variations
can use historical information to predict future
93
rotate 18% of the time
Second Life’s prefetching is wasteful
94
25-35% revisits the same region in a day
region-based caching?
95