Submission doc.: IEEE 802.11-15/0061r6 January 2015 Allan Jones, ActivisionSlide 1 FPS Network Traffic Model Date: 2015-1-12 Authors:

Slides:



Advertisements
Similar presentations
Submission doc.: IEEE 11-14/0xxx March 2014 Giwon Park, LG ElectronicsSlide 1 Discussion on power save mode for real time traffic Date: Authors:
Advertisements

Colyseus: A Distributed Architecture for Online Multiplayer Games
Cheat-Proofing P2P Online-gaming Albert Lee Spring 2008 Comp 424.
Fundamentals of Multimedia Part III: Multimedia Communications and Networking Chapter 15 : Network Services and Protocols for Multimedia Communications.
Doc.: IEEE /0604r1 Submission May 2014 Slide 1 Modeling and Evaluating Variable Bit rate Video Steaming for ax Date: Authors:
Thin to Win? Network Performance Analysis of the OnLive Thin Client Game System By Mark Claypool, David Finkel, Alexander Grant, and Michael Solano Submitted.
On the Impact of Delay on Real-Time Multiplayer Games Authors: Lothar Pantel, Lars C. Wolf Presented by: Bryan Wong.
A Service Platform for On-Line Games DebanJan Saha, Dambit Sahu, Anees Shaikh (IBM TJ Watson Research Center, NY) Presented by Gary Huang March 17, 2004.
Measurement and Estimation of Network QoS among Peer Xbox Game Players Youngki Lee, KAIST Sharad Agarwal, Microsoft Research Chris Butcher, Bungie Studio.
Provisioning On-line Games: A Traffic Analysis of a Busy Counter-Strike Server Wu-chang Feng, Francis Chang, Wu-chi Feng, Jonathan Walpole.
The Technology of the Game - Latency and Online Games Mark Claypool Associate Professor Computer Science Director Interactive Media and Game Development.
1 On Handling QoS Traffic in Wireless Sensor Networks 吳勇慶.
June 11, 2007 Telia-Sonera (TSIC) Distributed games Prof. Henning Schulzrinne Dept. of Computer Science Columbia University (with material by M. Claypool.
On the Geographic Distribution of On- line Game Servers and Players Wu-chang FengWu-chi Feng Discussion moderated By: John Carter.
Quality of Service in IN-home digital networks Alina Albu 23 October 2003.
The Effects of Loss and Latency on User Performance in Unreal Tournament 2003 Tom Beigbeder, Rory Coughlan, Corey Lusher, John Plunkett, Emmanuel Agu,
The Effects of Loss and Latency on User Performance in Unreal Tournament 2003 Tom Beigbeder, Rory Coughlan, Corey Lusher, John Plunkett, Emmanuel Agu,
Packet Loss and Latency in Unreal Tournament 2003 Tom Beigbeder Rory Coughlan Corey Lusher John Plunkett.
1 Presentation Mads Verwohlt and Martin H. Larsen 6th Semester Communication Network Diploma engineer Previous projects: Text Conference over W3 RTAI linux.
Performance Analysis of the IEEE Wireless Metropolitan Area Network nmgmt.cs.nchu.edu.tw 系統暨網路管理實驗室 Systems & Network Management Lab Reporter :黃文帥.
1 The Effects of Latency on Online Madden NFL Football James Nichols and Mark Claypool Computer Science Department Worcester Polytechnic Institute Massachusetts,
Doc.: IEEE /1167r2 Sept 2014 SubmissionYonggang Fang et. al. (ZTE) TGax Functional Requirement Discussion Date: Slide 1 Authors: NameAffiliationAddress .
A Traffic Characterization of Popular On-Line Games Wu-Chang Feng, Francis Chang, Wu- Chi Feng, and Jonathan Walpole IEEE/ACM Trans. Networking, Jun
The Effects of Latency on User Performance in Warcraft III Nathan Sheldon, Eric Gerard, Seth Borg, Mark Claypool, Emmanuel Agu Computer Science Department.
Network Analysis of Counter-strike and Starcraft Mark Claypool, David LaPoint, Josh Winslow Worcester Polytechnic Institute Worcester, MA, USA
Submission doc.: IEEE /0821r2 July 2014 Alireza Babaei, CableLabsSlide 1 Coexistence Requirements of WLAN and LTE in Unlicensed Spectrum.
Submission doc.: IEEE /0789r0 July 2015 Allan Jones, ActivisionSlide 1 Proposed changes to Evaluation Methodologies Date: ?? Authors:
A Credit-based Home Access Point (CHAP) to Improve Application Performance on IEEE Networks Choong-Soo Lee, Mark Claypool and Robert Kinicki In.
Submission doc.: IEEE 11-14/0026r1 January 2014 Yong Liu, et al.Slide 1 Thoughts on HEW PAR Date: Authors:
Doc.: IEEE C /06 Submission January, 2005 Jim Tomcik,Slide 1 ProjectIEEE Working Group on Mobile Broadband Wireless Access
POSTECH DP&NM Lab. Internet Traffic Monitoring and Analysis: Methods and Applications (1) 2. Network Monitoring Metrics.
Distributed Multimedia Systems David Immordino. Introduction 4 A multimedia application is a real-time system responsible for the delivering and receiving.
Peer-to-Peer AOI Voice Chatting for Massively Multiplayer Online Games (P2P-NVE 2007 workshop) Jehn-Ruey Jiang and Hung-Shiang Chen Adaptive Computing.
Doc.: IEEE /1305r0 Submission W.Carney, et. al. (SONY) Slide 1 Simplification of HEW Traffic Model Simulations Date: Authors:
Armin Bahramshahry August  Background  Problem  Solution  Evaluation  Summary.
ONLINE GAME NETWORK TRAFFIC OPTIMIZATION Jaewoo kim Youngho yi Minsik cho.
A Measurement Based Memory Performance Evaluation of High Throughput Servers Garba Isa Yau Department of Computer Engineering King Fahd University of Petroleum.
Peer-to-Peer AOI Voice Chatting for Massively Multiplayer Online Games (P2P-NVE 2007 workshop) Jehn-Ruey Jiang and Hung-Shiang Chen Presenter: Shun-Yun.
Chapter 8: Internet Operation. Network Classes Class A: Few networks, each with many hosts All addresses begin with binary 0 Class B: Medium networks,
1 Presented by Jari Korhonen Centre for Quantifiable Quality of Service in Communication Systems (Q2S) Norwegian University of Science and Technology (NTNU)
Doc.: IEEE /342r0 Submission March 2014 Naveen Kakani, CSRSlide 1 Short Packet Optimizations Date: Authors:
ﺑﺴﻢﺍﷲﺍﻠﺭﺣﻣﻥﺍﻠﺭﺣﻳﻡ. Group Members Nadia Malik01 Malik Fawad03.
Thin to Win? Network Performance Analysis of the OnLive Thin Client Game System Mark Claypool, David Finkel, Alexander Grant and Michael Solano Computer.
Doc.: IEEE /0065r0 Submission January 2014 William Carney, SONYSlide 1 Comments on Draft HEW PAR Date: Authors:
Multimedia streaming Application Anandi Giridharan Electrical Communication Engineering, Indian Institute of Science, Bangalore – , India Querying.
Latency and Player Actions in Online Games Mark Claypool & Kajal Claypool Worcester Polytechnic Institute Communications of the ACM, Nov Presented.
Submission doc.: IEEE /0061r5 January 2015 Allan Jones, ActivisionSlide 1 FPS Network Traffic Model Date: Authors:
Doc.: IEEE /xxxx Submission July 2007 Lei Du, DoCoMo Beijing Labs Slide 1 End-to-End QoS awareness for admission control Date: Authors:
Doc.: IEEE /1317r0 Submission December 2009 Vinko Erceg, BroadcomSlide 1 Internet Traffic Modeling Date: Authors: NameAffiliationsAddressPhone .
Submission doc.: IEEE 11-14/0866r0 July 2014 Johan Söder, Ericsson ABSlide 1 Traffic modeling and system capacity performance measure Date:
Doc.: IEEE /1263r2 Submission Dec 2009 Z. Chen, C. Zhu et al [Preliminary Simulation Results on Power Saving] Date: Authors: Slide.
Bluetooth: Quality of Service Reference: “QoS based scheduling for incorporating variable rate coded voice in Bluetooth”; Chawla, S.; Saran, H.; Singh,
Doc.: IEEE C /20 Submission March, 2005 Jim Tomcik,Slide 1 ProjectIEEE Working Group on Mobile Broadband Wireless Access
Predicting the Perceived Quality of a First Person Shooter Game The Team Fortress 2 T-Model David Dwyer Eric Finn Advisor: Mark Claypool 1.
Submission doc.: IEEE /0156r0 January 2016 Joseph LEVY (InterDigital)Slide 1 IMT-2020 Discussion Review and Straw Polls Date: Authors:
Doc.: IEEE /2200r2 Submission July 2007 Sandesh Goel, Marvell et alSlide 1 Route Metric Proposal Date: Authors:
Route Metric Proposal Date: Authors: July 2007 Month Year
Accelerating Peer-to-Peer Networks for Video Streaming
FPS Network Traffic Model
Simplified Traffic Model Based On Aggregated Network Statistics
Game Server Selection for Multiple Players
FPS Network Traffic Model
Packet Prioritization Issues
Route Metric Proposal Date: Authors: July 2007 Month Year
FPS Network Traffic Model
ENSC 427: COMMUNICATION NETWORKS SPRING 2018
Modeling and Evaluating Variable Bit rate Video Steaming for ax
Packet Prioritization Issues follow-up
FPS Network Traffic Model
RTA report summary Date: Authors: Jan 2019
Presentation transcript:

Submission doc.: IEEE /0061r6 January 2015 Allan Jones, ActivisionSlide 1 FPS Network Traffic Model Date: Authors:

Submission doc.: IEEE /0061r6 The purpose of this presentation is to provide network traffic details of multiplayer First Person Shooter (FPS) online games. Modern popular FPS games present unique challenges when it comes to network traffic. From this profile we can cooperatively develop a simulation that can be incorporated into simulation scenarios. Slide 2Allan Jones, Activision January 2015 Abstract

Submission doc.: IEEE /0061r6 Characteristics of most FPS games The gaming industry has long understood the basic characteristics of First Person Shooter games. "Client traffic is characterized by an almost constant packet and data rate” [9] (High frequency) "Both, update and server information packets are usually very small since they only contain movement and status information.” [9] (Low data rate) "We find that a ping below 50ms is associated with excellent game play." [9][3][6][7] (Latency sensitive) "In each transmit cycle the server generates a burst of packets - one packet for every active client. Consequently, the total data rate depends on the number of active clients. Thus, it makes sense to evaluate the server traffic per client instead of it’s summary traffic. This also allows to identify client specific variations.“ [9] (Burst traffic) Slide 3Allan Jones, Activision January 2015 FPS Network Traffic Model

Submission doc.: IEEE /0061r6 Architecture – Dedicated Server Slide 4Allan Jones, Activision January 2015 The dedicated server model provides geographically dispersed servers to host the game matches with optimal network paths. Some implementations [1] use virtual servers to provide the necessary matchmaking and virtual world state services while others use a combination of physical dedicated servers and console servers. FPS Network Traffic Model

Submission doc.: IEEE /0061r6 Slide 5Allan Jones, Activision January 2015 Typical modern console game 18 player match (Dedicated Server) FPS Network Traffic Model

Submission doc.: IEEE /0061r6 Architecture – Console (Local) Server Slide 6Allan Jones, Activision January 2015 The console server model elects one of the consoles to host the game and synchronize the other consoles throughout the match. This console also plays the game as well. Statistics are still managed by centralized servers, but the majority of the network traffic is handled by the consoles. This model has key economic advantages as there does not need to be as many dedicated servers in order to host all the games and utilizes the consoles network bandwidth which lowers bandwidth costs as well. FPS Network Traffic Model

Submission doc.: IEEE /0061r6 Typical modern console game 18 player match (Console Server) Slide 7Allan Jones, Activision January 2015 FPS Network Traffic Model

Submission doc.: IEEE /0061r6 Client / Server Communications Slide 8Allan Jones, Activision January 2015 The client to server communications averages will vary for any specific FPS game as will the server to client communication. FPS games all have delay sensitivity (latency and jitter) that creates severe consequences to the quality of gameplay. (e.g. the player can lose the game due to delays in communications). Network requirements for FPS games will increase by the time ax is deployed. Earlier IEEE and other supporting studies show a 50ms round trip tolerance. (e.g. 50ms bursts from the server) [2][4] We can anticipate the 50ms threshold to be around 25-30ms as ax is released. FPS Network Traffic Model

Submission doc.: IEEE /0061r6 January 2015 John Doe, Some CompanySlide 9

Submission doc.: IEEE /0061r6 January 2015 John Doe, Some CompanySlide 10

Submission doc.: IEEE /0061r6 January 2015 John Doe, Some CompanySlide 11

Submission doc.: IEEE /0061r6 January 2015 John Doe, Some CompanySlide 12

Submission doc.: IEEE /0061r6 Client/Server Packet and bandwidth profile Slide 13Allan Jones, Activision January 2015 The client to server communications and server to client averages are presented in the table below. DescriptionFPS 1FPS 2FPS 3 Average Client Packets/sec  server Average Client bits/sec  server Average Server Packets/sec  client Average Server bits/sec  client Average Server Aggregate Packets/sec  clients Average Server Aggregate bits/sec  clients FPS Network Traffic Model

Submission doc.: IEEE /0061r6 January 2015 Allan Jones, ActivisionSlide 14

Submission doc.: IEEE /0061r6 January 2015 Allan Jones, ActivisionSlide 15

Submission doc.: IEEE /0061r6 Recommendation: Slide 16Allan Jones, Activision January 2015 The recommendation is to use the most network intense model (FPS3) that will ensure that our emerging standard can facilitate the needs of FPS games of today and emerging FPS multiplayer games over the next few years. Additionally since FPS games are extremely sensitive to network latency and jitter we need to ensure that our emerging standard adds as little latency as possible. DescriptionFPS 1FPS 2FPS 3 Average Client Packets/sec  server Average Client bits/sec  server Average Server Packets/sec  client Average Server bits/sec  client Average Server Aggregate Packets/sec  clients Average Server Aggregate bits/sec  clients FPS Network Traffic Model

Submission doc.: IEEE /0061r6 Straw Poll: Slide 17Allan Jones, Activision January 2015 Should we add the FPS network model information (FPS 3 Column on Slide 16) to the Simulation Scenarios document(980 r5) in the reference traffic profile sections? Y: N: A: FPS Network Traffic Model

Submission doc.: IEEE /0061r6 Motion: Slide 18Allan Jones, Activision January 2015 Traffic Model # Traffic model name Description Application traffic (Forward / Backward) Application Load (Mbps ) (Forward / Backward) A-MPDU Size (B) (Forward / Backward) Baseline Power Save Mechansim T5 Online game server Moderate UDP traffic load with short large bursts periodically during game synchronization UDP packets2.4Mbps T8 Gaming Small UDP traffic load with short large bursts periodically during game synchronization UDP packets54 Kbps Move to propose to add the following text (highlighted in yellow) to the simulation scenarios document (980r5) in the reference traffic profiles section for traffic model numbers T5 and T8 to reflect the results of the FPS network traffic model (61r5). These values are currently blank.

Submission doc.: IEEE /0061r6January 2015 Allan Jones, ActivisionSlide 19 References [1] Saroj Kar, “Windows Azure: The power behind upcoming game Titanfall for the Xbox One”, Silicon Angle – February 25 th, 2014 ; behind-blockbuster-game-titanfall-for-the-xbox-one/ behind-blockbuster-game-titanfall-for-the-xbox-one/ [2] Mark Claypool, David LaPoint, and Josh Winslow. “Network Analysis of Counter-strike and Starcraft”, In Proceedings of the 22nd IEEE International Performance, Computing, and Communications Conference (IPCCC), Phoenix, Arizona, USA, April 2003 [3] Amit Sinha, Kenneth Mitchell, Deep Medhi “Network Game Traffic: A Broadband Access Perspective”, Computer Networks, vol. 49, no. 1, pp , 2005 [4] L. Pantel, L. Wolf, “On the impact of delay on real-time multiplayer games”, Proc. International Workshop on Network and Operating System Support for Digital Audio and Video (NOSSDAV) (2002) [5] Tristan Henderson, Saleem Bhatti “Networked games — A QoS sensitive application for QoS insensitive users?”, ACM SIGCOMM 2003 Workshops August 25 & 27, 2003, Karlsruhe, Germany [6] Rahul Amin, France Jackson, Juan Gilbert, Jim Martin “Assessing the Impact of Latency and Jitter on the Perceived Quality of Call of Duty Modern Warfare 2”, In HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: users and contexts of use - Volume Part III Pages , (2013) [7] Kjetil Raaen, “Latency Thresholds for Usability in Games”, NIK-2014 conference (2014) [8] Mark Claypool, Kajal Claypool, “Latency Can Kill: Precision and Deadline in Online Games”, February 22–23, 2010, Phoenix, Arizona, USA. [9] J. Färber, “Network game traffic modelling,” in Proceedings of Netgames, April 2002, pp. 53–57.