SlideShare a Scribd company logo
1 of 12
Download to read offline
Hazel McKendrick
     Supervised by Henry Fortuna



    Distributing
   Virtual Worlds
“How can the processing of autonomous characters
in a real-time virtual environment benefit from
parallelisation over multiple distributed computer
systems?”
Project Overview.

    Processing virtual worlds

    Single server unsuitable

    Flexibility, scalability, redundancy


    Distributed computing
Project Aim.

    Create a distributed system

    Divide a virtual world

    Update characters in it


    Consider:
      • Processing power
      • Scalability, power and money saving
      • Flexibility
Simulation Design.

    World Maps

    Characters (thousands)
      • A* Pathfinding
System Structure.

    Server & Worker Node architecture

    TCP-IP

    Message Passing


    Node thread pool
World Division.

    Top-down vs Bottom-up


Microcells

    Smallest unit of world

    Nodes process several

    Distributed statically or
    dynamically

    Contain and pass work
Distribution.

    Optimal assignment
      • Can be solved with ILP - Complexity too high

    Two static approaches used

    Dynamic algorithm created
Distribution Results.
                       
                             Amdahl's Law
                       
                             95% to 99% parallelised

                           Processing times with varying numbers of nodes
                       450.000                                                                       Average deviation in processing times, over time
                                                                                                                         4
                       400.000
                                                                                                                        3.5
                       350.000                                                         Server




                                                                                                Average deviation(ms)
                                                                                       Node 1                            3
Processing time (ms)




                       300.000                                                         Node 2
                                                                                                                        2.5
                                                                                       Node 3
                       250.000
                                                                                       Node 4                            2
                       200.000                                                         Node 5
                                                                                                                        1.5
                                                                                       Node 6
                       150.000                                                         Node 7                            1
                                                                                       Node 8
                       100.000                                                                                          0.5
                                                                                       Node 9

                        50.000                                                                                           0
                                                                                                                              0   1      2        3            4   5   6
                           0.000
                                                                                                                                      Time elapsed (minutes)
                                   0   1   2     3   4   5   6   7   8   9   10   11

                                               Number of computers
Scaling Hardware.

    Virtual world load varies greatly

    Gustafson's Law
                                            Minimising Hardware

    Scale Hardware                               Entities   Nodes on


    Improve
                                 5000                                               3

                                 4500

                                 4000


distribution!                    3500
                                                                                    2
                                 3000
                      Entities




                                                                                        Nodes
                                 2500

                                 2000



    (Simulated)
                                                                                    1
                                1500

                                 1000

                                  500

                                    0                                               0
                                        0   20   40    60    80   100   120   140

                                                      Time (s)
Evaluation.

    Scaling nodes

    Dynamic distribution algorithm
      • Over time

    Microcells

    Reducing hardware
Conclusion.

    Reduce processing times

    Balance load

    Lower power and cooling costs


    Further work
      • Redundancy
      • Inter-node communications
      • Scaling factors
Hazel McKendrick
     Supervised by Henry Fortuna



    Distributing
   Virtual Worlds
“How can the processing of autonomous characters
in a real-time virtual environment benefit from
parallelisation over multiple distributed computer
systems?”

More Related Content

Viewers also liked

Ppt on honour killing
Ppt on honour killingPpt on honour killing
Ppt on honour killingmatangi jha
 
Honour killing ppt
Honour killing pptHonour killing ppt
Honour killing pptsamiamer
 
6 writing and presenting literature review-khalid
6 writing and presenting literature review-khalid6 writing and presenting literature review-khalid
6 writing and presenting literature review-khalidKhalid Mahmood
 
Taking ownership
Taking ownershipTaking ownership
Taking ownershipSarah Zink
 
Forms of ownership
Forms of ownershipForms of ownership
Forms of ownershipnonkululekoS
 
Forms of Business Ownership - Intro to Business
Forms of Business Ownership - Intro to BusinessForms of Business Ownership - Intro to Business
Forms of Business Ownership - Intro to BusinessJon Wroten
 
Bim Presentation
Bim PresentationBim Presentation
Bim Presentationrsalbin
 
Lit review powerpoint
Lit review powerpointLit review powerpoint
Lit review powerpointKellyh84
 
Revit and Building Information Modeling (BIM) Presentation
Revit and Building Information Modeling (BIM) PresentationRevit and Building Information Modeling (BIM) Presentation
Revit and Building Information Modeling (BIM) Presentationryanabarton
 
Literature review in research
Literature review in researchLiterature review in research
Literature review in researchNursing Path
 
Literature Review (Review of Related Literature - Research Methodology)
Literature Review (Review of Related Literature - Research Methodology)Literature Review (Review of Related Literature - Research Methodology)
Literature Review (Review of Related Literature - Research Methodology)Dilip Barad
 
Types of Business Ownership
Types of Business OwnershipTypes of Business Ownership
Types of Business Ownershipamckean
 

Viewers also liked (15)

Ppt on honour killing
Ppt on honour killingPpt on honour killing
Ppt on honour killing
 
Honour killing ppt
Honour killing pptHonour killing ppt
Honour killing ppt
 
6 writing and presenting literature review-khalid
6 writing and presenting literature review-khalid6 writing and presenting literature review-khalid
6 writing and presenting literature review-khalid
 
Taking ownership
Taking ownershipTaking ownership
Taking ownership
 
Forms of ownership
Forms of ownershipForms of ownership
Forms of ownership
 
Forms of Business Ownership - Intro to Business
Forms of Business Ownership - Intro to BusinessForms of Business Ownership - Intro to Business
Forms of Business Ownership - Intro to Business
 
Bim Presentation
Bim PresentationBim Presentation
Bim Presentation
 
Lit review powerpoint
Lit review powerpointLit review powerpoint
Lit review powerpoint
 
Doing a Literature Review
Doing a Literature ReviewDoing a Literature Review
Doing a Literature Review
 
Revit and Building Information Modeling (BIM) Presentation
Revit and Building Information Modeling (BIM) PresentationRevit and Building Information Modeling (BIM) Presentation
Revit and Building Information Modeling (BIM) Presentation
 
Literature review in research
Literature review in researchLiterature review in research
Literature review in research
 
Literature Review (Review of Related Literature - Research Methodology)
Literature Review (Review of Related Literature - Research Methodology)Literature Review (Review of Related Literature - Research Methodology)
Literature Review (Review of Related Literature - Research Methodology)
 
Literature Review
Literature ReviewLiterature Review
Literature Review
 
Building Information Modeling (BIM)
Building Information Modeling (BIM)Building Information Modeling (BIM)
Building Information Modeling (BIM)
 
Types of Business Ownership
Types of Business OwnershipTypes of Business Ownership
Types of Business Ownership
 

Similar to Honours Project Presentation

Acceleration for big data, hadoop and memcached it168文库
Acceleration for big data, hadoop and memcached it168文库Acceleration for big data, hadoop and memcached it168文库
Acceleration for big data, hadoop and memcached it168文库Accenture
 
Acceleration for big data, hadoop and memcached it168文库
Acceleration for big data, hadoop and memcached it168文库Acceleration for big data, hadoop and memcached it168文库
Acceleration for big data, hadoop and memcached it168文库Accenture
 
Usenix LISA 2012 - Choosing a Proxy
Usenix LISA 2012 - Choosing a ProxyUsenix LISA 2012 - Choosing a Proxy
Usenix LISA 2012 - Choosing a ProxyLeif Hedstrom
 
(ATS4-PLAT07) Interactive Charts Revamped
(ATS4-PLAT07) Interactive Charts Revamped(ATS4-PLAT07) Interactive Charts Revamped
(ATS4-PLAT07) Interactive Charts RevampedBIOVIA
 
Betting On Data Grids
Betting On Data GridsBetting On Data Grids
Betting On Data Gridsgojkoadzic
 
Top Application Performance Landmines
Top Application Performance LandminesTop Application Performance Landmines
Top Application Performance LandminesAndreas Grabner
 
October Rules Fest 2008 - Distributed Data Processing with ILOG JRules
October Rules Fest 2008 - Distributed Data Processing with ILOG JRulesOctober Rules Fest 2008 - Distributed Data Processing with ILOG JRules
October Rules Fest 2008 - Distributed Data Processing with ILOG JRulesDan Selman
 
Cassandra SF 2012 - Technical Deep Dive: query performance
Cassandra SF 2012 - Technical Deep Dive: query performance Cassandra SF 2012 - Technical Deep Dive: query performance
Cassandra SF 2012 - Technical Deep Dive: query performance aaronmorton
 
A Function by Any Other Name is a Function
A Function by Any Other Name is a FunctionA Function by Any Other Name is a Function
A Function by Any Other Name is a FunctionJason Strate
 
Oracle no sql overview brief
Oracle no sql overview briefOracle no sql overview brief
Oracle no sql overview briefInfiniteGraph
 
Capacity Planning for Linux Systems
Capacity Planning for Linux SystemsCapacity Planning for Linux Systems
Capacity Planning for Linux SystemsRodrigo Campos
 
Hyper v.nu-windows serverhyperv-networkingevolved
Hyper v.nu-windows serverhyperv-networkingevolvedHyper v.nu-windows serverhyperv-networkingevolved
Hyper v.nu-windows serverhyperv-networkingevolvedhypervnu
 
Packet shaper datasheet 81
Packet shaper datasheet 81Packet shaper datasheet 81
Packet shaper datasheet 81Zalli13
 
Packet shaper datasheet 81
Packet shaper datasheet 81Packet shaper datasheet 81
Packet shaper datasheet 81Zalli13
 

Similar to Honours Project Presentation (20)

Acceleration for big data, hadoop and memcached it168文库
Acceleration for big data, hadoop and memcached it168文库Acceleration for big data, hadoop and memcached it168文库
Acceleration for big data, hadoop and memcached it168文库
 
Acceleration for big data, hadoop and memcached it168文库
Acceleration for big data, hadoop and memcached it168文库Acceleration for big data, hadoop and memcached it168文库
Acceleration for big data, hadoop and memcached it168文库
 
Usenix LISA 2012 - Choosing a Proxy
Usenix LISA 2012 - Choosing a ProxyUsenix LISA 2012 - Choosing a Proxy
Usenix LISA 2012 - Choosing a Proxy
 
(ATS4-PLAT07) Interactive Charts Revamped
(ATS4-PLAT07) Interactive Charts Revamped(ATS4-PLAT07) Interactive Charts Revamped
(ATS4-PLAT07) Interactive Charts Revamped
 
ASP.NET Best Practices
ASP.NET Best PracticesASP.NET Best Practices
ASP.NET Best Practices
 
I/O Scalability in Xen
I/O Scalability in XenI/O Scalability in Xen
I/O Scalability in Xen
 
Betting On Data Grids
Betting On Data GridsBetting On Data Grids
Betting On Data Grids
 
Top Application Performance Landmines
Top Application Performance LandminesTop Application Performance Landmines
Top Application Performance Landmines
 
October Rules Fest 2008 - Distributed Data Processing with ILOG JRules
October Rules Fest 2008 - Distributed Data Processing with ILOG JRulesOctober Rules Fest 2008 - Distributed Data Processing with ILOG JRules
October Rules Fest 2008 - Distributed Data Processing with ILOG JRules
 
Cassandra SF 2012 - Technical Deep Dive: query performance
Cassandra SF 2012 - Technical Deep Dive: query performance Cassandra SF 2012 - Technical Deep Dive: query performance
Cassandra SF 2012 - Technical Deep Dive: query performance
 
A Function by Any Other Name is a Function
A Function by Any Other Name is a FunctionA Function by Any Other Name is a Function
A Function by Any Other Name is a Function
 
Oracle no sql overview brief
Oracle no sql overview briefOracle no sql overview brief
Oracle no sql overview brief
 
Capacity Planning for Linux Systems
Capacity Planning for Linux SystemsCapacity Planning for Linux Systems
Capacity Planning for Linux Systems
 
DCT_TR802
DCT_TR802DCT_TR802
DCT_TR802
 
DCT_TR802
DCT_TR802DCT_TR802
DCT_TR802
 
DCT_TR802
DCT_TR802DCT_TR802
DCT_TR802
 
Hyper v.nu-windows serverhyperv-networkingevolved
Hyper v.nu-windows serverhyperv-networkingevolvedHyper v.nu-windows serverhyperv-networkingevolved
Hyper v.nu-windows serverhyperv-networkingevolved
 
Packet shaper datasheet 81
Packet shaper datasheet 81Packet shaper datasheet 81
Packet shaper datasheet 81
 
Packet shaper datasheet 81
Packet shaper datasheet 81Packet shaper datasheet 81
Packet shaper datasheet 81
 
iSLC Technology
iSLC TechnologyiSLC Technology
iSLC Technology
 

Recently uploaded

Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...shyamraj55
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesSinan KOZAK
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Allon Mureinik
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhisoniya singh
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel Araújo
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptxHampshireHUG
 

Recently uploaded (20)

Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
Automating Business Process via MuleSoft Composer | Bangalore MuleSoft Meetup...
 
Unblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen FramesUnblocking The Main Thread Solving ANRs and Frozen Frames
Unblocking The Main Thread Solving ANRs and Frozen Frames
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)Injustice - Developers Among Us (SciFiDevCon 2024)
Injustice - Developers Among Us (SciFiDevCon 2024)
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
Transcript: #StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | DelhiFULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
FULL ENJOY 🔝 8264348440 🔝 Call Girls in Diplomatic Enclave | Delhi
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
04-2024-HHUG-Sales-and-Marketing-Alignment.pptx
 

Honours Project Presentation

  • 1. Hazel McKendrick Supervised by Henry Fortuna Distributing Virtual Worlds “How can the processing of autonomous characters in a real-time virtual environment benefit from parallelisation over multiple distributed computer systems?”
  • 2. Project Overview.  Processing virtual worlds  Single server unsuitable  Flexibility, scalability, redundancy  Distributed computing
  • 3. Project Aim.  Create a distributed system  Divide a virtual world  Update characters in it  Consider: • Processing power • Scalability, power and money saving • Flexibility
  • 4. Simulation Design.  World Maps  Characters (thousands) • A* Pathfinding
  • 5. System Structure.  Server & Worker Node architecture  TCP-IP  Message Passing  Node thread pool
  • 6. World Division.  Top-down vs Bottom-up Microcells  Smallest unit of world  Nodes process several  Distributed statically or dynamically  Contain and pass work
  • 7. Distribution.  Optimal assignment • Can be solved with ILP - Complexity too high  Two static approaches used  Dynamic algorithm created
  • 8. Distribution Results.  Amdahl's Law  95% to 99% parallelised Processing times with varying numbers of nodes 450.000 Average deviation in processing times, over time 4 400.000 3.5 350.000 Server Average deviation(ms) Node 1 3 Processing time (ms) 300.000 Node 2 2.5 Node 3 250.000 Node 4 2 200.000 Node 5 1.5 Node 6 150.000 Node 7 1 Node 8 100.000 0.5 Node 9 50.000 0 0 1 2 3 4 5 6 0.000 Time elapsed (minutes) 0 1 2 3 4 5 6 7 8 9 10 11 Number of computers
  • 9. Scaling Hardware.  Virtual world load varies greatly  Gustafson's Law Minimising Hardware  Scale Hardware Entities Nodes on Improve 5000 3  4500 4000 distribution! 3500 2 3000 Entities Nodes 2500 2000 (Simulated) 1  1500 1000 500 0 0 0 20 40 60 80 100 120 140 Time (s)
  • 10. Evaluation.  Scaling nodes  Dynamic distribution algorithm • Over time  Microcells  Reducing hardware
  • 11. Conclusion.  Reduce processing times  Balance load  Lower power and cooling costs  Further work • Redundancy • Inter-node communications • Scaling factors
  • 12. Hazel McKendrick Supervised by Henry Fortuna Distributing Virtual Worlds “How can the processing of autonomous characters in a real-time virtual environment benefit from parallelisation over multiple distributed computer systems?”