Embed Size (px)
DESCRIPTION
Cloud gaming, i.e., real-time game playing via thin clients, relieves players from the need to constantly upgrade their computers and deal with compatibility issues when playing games. As a result, cloud gaming is generating a great deal of interest among entrepreneurs and the public. However, given the large design space, it is not yet known which platforms deliver the best quality of service and which design elements constitute a good cloud gaming system. This study is motivated by the question: How good is the real-timeliness of current cloud gaming systems? To address the question, we analyze the response latency of two cloud gaming platforms, namely, OnLive and StreamMyGame. Our results show that the streaming latency of OnLive is reasonable for real-time cloud gaming, while that of StreamMyGame is almost twice the former when the StreamMyGame server is provisioned using an Intel Core i7-920 PC. We believe that our measurement approach can be generally applied to PC-based cloud gaming platforms, and that it will further the understanding of such systems and lead to improvements.
Citation preview
Kuan-Ta Chen1, Yu-Chun Chang12, Po-Han Tseng1, Chun-Ying Huang3, and Chin-Laung Lei2
1Academia Sinica 2National Taiwan University 3National Taiwan Ocean University
Measuring The Latency of Cloud Gaming Systems
Conclusion We proposed a general methodology to measure the latency
components of cloud gaming systems
OnLive provides shorter latency for real-time gaming than SteamMyGame
Future work
Improve the proposed methodology
Apply the methodology to more platforms and derive general guidelines for designing quality cloud gaming systems
Cloud Gaming
Motivation Game software becomes more complex
The overhead of setting up a game is significant
Games have software and hardware compatibility with computers
Real-time game playing via thin clients
Advantages of cloud gaming
No set up overheads or compatibility issues
People can play games anywhere, anytime
Cloud gaming services
OnLive, StreamMyGame, GAIKAI, G-cluster Global, OTOY, T5-Labs
Which platform provides the best quality of service?
Measurement Methodology Response delay : In each experiment, send ESC key in the game and see
when the corresponding MENU frame will be displayed
Response delay (RD) = Network delay (ND) + Processing delay (PD) + Playout delay (OD)
Scatter Plot of tblock_succeed and tblock_failed
Measurement Results
How to determine the occurrence of t3
Blocking is successful : add tblock to the set tblock_succeeded
Blocking is failed : add tmenu to the set tblock_failed
We then estimate t3 as the point that yield the minimum sum of the
two density functions formed by tblock_succeeded and tblock_failed
Blocking : Block the incoming data on the client
Blocking is successful
Blocking is failed
Experiment Setup
• Game: Lego Batman: The VideoGame (Batman) Warhammer 40,000: Dawn of War (DOW) F.E.A.R. 2: Project Origin (FEAR)
• Platform: OnLive (OnLive) StreamMyGame (SMG)
Network delay (ND) = network RTT
Processing delay (PD) = t3 – t0 – ND
Playout delay (OD) = t4 – t3
tblock tblock+1 Time tmenu
Menu screen appears
tblock tblock+1 Time tmenu
Internet
LAN
LAN
Switch
Client (Intel Core i7-920)
Server (Intel Core i7-920)
OnLive Server
t0 t1 t2 t4
(controllable)
t3
(probable) (observable)
Processing delay Playout delay
Probing range
Time
Academia Sinica
Server Client
Game Servers
PC
Laptop
Mobile
Streaming
Streaming
Streaming
Internet
t0 (Key event sent) t1 (Key event received)
t2 (Frame sent) t3 (Frame received)
Menu frame
Menu screen shown
t4 (Frame displayed)
