This document discusses experimentation tools for networking research. It outlines the need to move beyond isolated protocol simulations to evaluations that involve multiple interacting protocols, transient behavior, and real-world testbeds and field tests. This requires new tools that allow for a smooth transition between simulations, emulations, and real implementations. Key challenges include virtualizing the execution environment for real code in simulations, deploying emulation platforms, and maintaining transparency with other simulation models. The document argues these tools are needed to improve the realism and validity of networking protocol evaluations.
This document provides an overview of the history and future of the ns-3 network simulator project. It discusses how the project originated from multiple partners with different goals and requirements, including real-code integration, emulation, education, wireless modeling, and long-term sustainability. A key challenge was developing an open source community to support ongoing maintenance of the large and complex codebase. The document outlines how ns-3 addressed this by adopting an incremental development process and gaining community involvement and support over time.
A fairly extensive tutorial that I gave at the Trilogy summer School. The original presentation was captured as a video stream and is available online at http://inl.info.ucl.ac.be/tutorials/tfiss09-lacage
Future Internet testbeds/experimentation between Brazil and Europe - FIBREFIBRE Testbed
The FIBRE project aims to create a shared experimental space between the EU and Brazil for Future Internet research by building and operating federated testbeds. Over 30 months, the project will build new Future Internet experimental testbeds in Brazil and federate them with existing EU testbeds. This will allow experiments spanning both regions to test technologies like seamless mobility and high-definition content delivery across the federated infrastructure.
This document summarizes a Ph.D. defense presentation on network attack injection. The presentation discusses vulnerabilities, testing methods like fuzzing and fault injection, and proposes an automated and systematic approach to vulnerability discovery. It then outlines a network attack injection framework involving protocol specification, attack generation, injection, monitoring, and analysis.
The document discusses using Python for scientific applications. It describes NumPy arrays as efficient data structures for numerical computing and SciPy as a library for scientific algorithms. It notes that NumPy provides N-dimensional arrays and universal functions for fast array operations, while SciPy builds on NumPy with modules for domains like linear algebra, optimization, integration and more. Together NumPy and SciPy provide the fundamental tools for scientific computing with Python.
An overview of my takeaways from the Information Architecture Summit in New Orleans in March. Presented at Übermind (in Seattle) on April 17th.
[Originally uploaded to Slideshare April 18, 2012]
These are the slides for a plenary talk I gave at GEC 11 in Denver in July 2011. The primary message is that we, the networking community need to fundamentally improve the way we do experimental research.
Infrastructure and Workflow for the Formal Evaluation of Semantic Search Tech...Stuart Wrigley
This paper describes an infrastructure for the automated evaluation of semantic technologies and, in particular, semantic search technologies. For this purpose, we present an evaluation framework which follows a service-oriented approach for evaluating semantic technologies and uses the Business Process Execution Language (BPEL) to define evaluation workflows that can be executed by process engines. This framework supports a variety of evaluations, from different semantic areas, including search, and is extendible to new evaluations. We show how BPEL addresses this diversity as well as how it is used to solve specific challenges such as heterogeneity, error handling and reuse.
Presented at Data infrastructurEs for Supporting Information Retrieval Evaluation (DESIRE 2011) Workshop, Co-located with CIKM 2011, the 20th ACM Conference on Information and Knowledge Management
Friday 28th October 2011, Glasgow, UK
http://www.promise-noe.eu/events/desire-2011/
This document provides an overview of the history and future of the ns-3 network simulator project. It discusses how the project originated from multiple partners with different goals and requirements, including real-code integration, emulation, education, wireless modeling, and long-term sustainability. A key challenge was developing an open source community to support ongoing maintenance of the large and complex codebase. The document outlines how ns-3 addressed this by adopting an incremental development process and gaining community involvement and support over time.
A fairly extensive tutorial that I gave at the Trilogy summer School. The original presentation was captured as a video stream and is available online at http://inl.info.ucl.ac.be/tutorials/tfiss09-lacage
Future Internet testbeds/experimentation between Brazil and Europe - FIBREFIBRE Testbed
The FIBRE project aims to create a shared experimental space between the EU and Brazil for Future Internet research by building and operating federated testbeds. Over 30 months, the project will build new Future Internet experimental testbeds in Brazil and federate them with existing EU testbeds. This will allow experiments spanning both regions to test technologies like seamless mobility and high-definition content delivery across the federated infrastructure.
This document summarizes a Ph.D. defense presentation on network attack injection. The presentation discusses vulnerabilities, testing methods like fuzzing and fault injection, and proposes an automated and systematic approach to vulnerability discovery. It then outlines a network attack injection framework involving protocol specification, attack generation, injection, monitoring, and analysis.
The document discusses using Python for scientific applications. It describes NumPy arrays as efficient data structures for numerical computing and SciPy as a library for scientific algorithms. It notes that NumPy provides N-dimensional arrays and universal functions for fast array operations, while SciPy builds on NumPy with modules for domains like linear algebra, optimization, integration and more. Together NumPy and SciPy provide the fundamental tools for scientific computing with Python.
An overview of my takeaways from the Information Architecture Summit in New Orleans in March. Presented at Übermind (in Seattle) on April 17th.
[Originally uploaded to Slideshare April 18, 2012]
These are the slides for a plenary talk I gave at GEC 11 in Denver in July 2011. The primary message is that we, the networking community need to fundamentally improve the way we do experimental research.
Infrastructure and Workflow for the Formal Evaluation of Semantic Search Tech...Stuart Wrigley
This paper describes an infrastructure for the automated evaluation of semantic technologies and, in particular, semantic search technologies. For this purpose, we present an evaluation framework which follows a service-oriented approach for evaluating semantic technologies and uses the Business Process Execution Language (BPEL) to define evaluation workflows that can be executed by process engines. This framework supports a variety of evaluations, from different semantic areas, including search, and is extendible to new evaluations. We show how BPEL addresses this diversity as well as how it is used to solve specific challenges such as heterogeneity, error handling and reuse.
Presented at Data infrastructurEs for Supporting Information Retrieval Evaluation (DESIRE 2011) Workshop, Co-located with CIKM 2011, the 20th ACM Conference on Information and Knowledge Management
Friday 28th October 2011, Glasgow, UK
http://www.promise-noe.eu/events/desire-2011/
This document describes the EagleEye network analytics tool from I7 Networks Pvt Ltd. It provides flexible deployment options, scalable data storage and retrieval, seamless integrations, alerts and reports. The tool offers analytics and forensics capabilities including investigating host activity, analyzing trends, live monitoring, usage summaries, and payload search. It also provides unmatched reporting, customizable dashboards, data mining abilities, and forensic capabilities for drill down analysis up to the packet level.
This document describes the EagleEye network analytics tool from I7 Networks Pvt Ltd. It provides flexible deployment options, scalable data storage and retrieval, seamless integrations, alerts and reports. The tool offers analytics and forensics capabilities including investigating host activity, analyzing trends, live monitoring, usage summaries, and payload search. It also provides unmatched reporting, customizable dashboards, data mining abilities, and forensic capabilities for drill down analysis up to the packet level.
The FIBRE project aims to create a shared research facility between the EU and Brazil for experimenting with future internet technologies. It will involve building a new testbed in Brazil and enhancing existing testbeds in Europe. The facilities will be federated to allow experiments using resources from both regions. Several pilot applications will be demonstrated to showcase the capabilities of the federated infrastructure. The project also aims to enhance collaboration between European and Brazilian researchers in future internet areas. It involves six work packages and has 15 partner organizations with the goal of advancing joint internet research between the two regions.
Ichiro Satoh presented his experiences with context-aware services from experiments conducted in real world settings like museums. The experiments tested different methods of providing audio and text annotations to visitors based on their location and past exhibits viewed. Evaluation of over 200 participants found that traditional paper-based posters achieved the highest learning scores, while methods relying on devices distracted visitors. Key lessons included informing users about available services, supporting legacy spaces with constraints, and managing heterogeneous systems in public settings.
The document discusses a project called MADUF that aims to maximize usage of digital video broadcasting (DVB) in Flanders. It will involve analyzing the legal framework, cellular networks, broadcast networks, available content and applications. Field trials will test apps with end users and gather data. Surveys will assess the state of the market, users, and gather feedback after the trials. The project seeks to involve end users from the beginning through completion to account for their different characteristics as innovators, early adopters, or other types of users.
This document summarizes the roles of Waseda University and NECTEC in international collaboration in information and communication technology (ICT) education, research, and standardization. It discusses partnerships between Thailand and Japan, including the launch of a testbed network in 2005 to enable real-time communication and on-demand access between universities. Examples are provided of telemedicine, e-learning, and a tele-education program hosted jointly by Waseda University, Thai universities, and NECTEC. The document also mentions a Japan-Thailand ministerial dialogue on IT and science & technology held at Waseda University in 2006.
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...my Pandit
Dive into the steadfast world of the Taurus Zodiac Sign. Discover the grounded, stable, and logical nature of Taurus individuals, and explore their key personality traits, important dates, and horoscope insights. Learn how the determination and patience of the Taurus sign make them the rock-steady achievers and anchors of the zodiac.
Storytelling is an incredibly valuable tool to share data and information. To get the most impact from stories there are a number of key ingredients. These are based on science and human nature. Using these elements in a story you can deliver information impactfully, ensure action and drive change.
The Genesis of BriansClub.cm Famous Dark WEb PlatformSabaaSudozai
BriansClub.cm, a famous platform on the dark web, has become one of the most infamous carding marketplaces, specializing in the sale of stolen credit card data.
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
In the recent edition, The 10 Most Influential Leaders Guiding Corporate Evolution, 2024, The Silicon Leaders magazine gladly features Dejan Štancer, President of the Global Chamber of Business Leaders (GCBL), along with other leaders.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This PowerPoint compilation offers a comprehensive overview of 20 leading innovation management frameworks and methodologies, selected for their broad applicability across various industries and organizational contexts. These frameworks are valuable resources for a wide range of users, including business professionals, educators, and consultants.
Each framework is presented with visually engaging diagrams and templates, ensuring the content is both informative and appealing. While this compilation is thorough, please note that the slides are intended as supplementary resources and may not be sufficient for standalone instructional purposes.
This compilation is ideal for anyone looking to enhance their understanding of innovation management and drive meaningful change within their organization. Whether you aim to improve product development processes, enhance customer experiences, or drive digital transformation, these frameworks offer valuable insights and tools to help you achieve your goals.
INCLUDED FRAMEWORKS/MODELS:
1. Stanford’s Design Thinking
2. IDEO’s Human-Centered Design
3. Strategyzer’s Business Model Innovation
4. Lean Startup Methodology
5. Agile Innovation Framework
6. Doblin’s Ten Types of Innovation
7. McKinsey’s Three Horizons of Growth
8. Customer Journey Map
9. Christensen’s Disruptive Innovation Theory
10. Blue Ocean Strategy
11. Strategyn’s Jobs-To-Be-Done (JTBD) Framework with Job Map
12. Design Sprint Framework
13. The Double Diamond
14. Lean Six Sigma DMAIC
15. TRIZ Problem-Solving Framework
16. Edward de Bono’s Six Thinking Hats
17. Stage-Gate Model
18. Toyota’s Six Steps of Kaizen
19. Microsoft’s Digital Transformation Framework
20. Design for Six Sigma (DFSS)
To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
Key highlights include Microsoft's Digital Transformation Framework, which focuses on driving innovation and efficiency, and McKinsey's Ten Guiding Principles, which provide strategic insights for successful digital transformation. Additionally, Forrester's framework emphasizes enhancing customer experiences and modernizing IT infrastructure, while IDC's MaturityScape helps assess and develop organizational digital maturity. MIT's framework explores cutting-edge strategies for achieving digital success.
These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
3 Simple Steps To Buy Verified Payoneer Account In 2024SEOSMMEARTH
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Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.AnnySerafinaLove
This letter, written by Kellen Harkins, Course Director at Full Sail University, commends Anny Love's exemplary performance in the Video Sharing Platforms class. It highlights her dedication, willingness to challenge herself, and exceptional skills in production, editing, and marketing across various video platforms like YouTube, TikTok, and Instagram.
Navigating the world of forex trading can be challenging, especially for beginners. To help you make an informed decision, we have comprehensively compared the best forex brokers in India for 2024. This article, reviewed by Top Forex Brokers Review, will cover featured award winners, the best forex brokers, featured offers, the best copy trading platforms, the best forex brokers for beginners, the best MetaTrader brokers, and recently updated reviews. We will focus on FP Markets, Black Bull, EightCap, IC Markets, and Octa.
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
This document describes the EagleEye network analytics tool from I7 Networks Pvt Ltd. It provides flexible deployment options, scalable data storage and retrieval, seamless integrations, alerts and reports. The tool offers analytics and forensics capabilities including investigating host activity, analyzing trends, live monitoring, usage summaries, and payload search. It also provides unmatched reporting, customizable dashboards, data mining abilities, and forensic capabilities for drill down analysis up to the packet level.
This document describes the EagleEye network analytics tool from I7 Networks Pvt Ltd. It provides flexible deployment options, scalable data storage and retrieval, seamless integrations, alerts and reports. The tool offers analytics and forensics capabilities including investigating host activity, analyzing trends, live monitoring, usage summaries, and payload search. It also provides unmatched reporting, customizable dashboards, data mining abilities, and forensic capabilities for drill down analysis up to the packet level.
The FIBRE project aims to create a shared research facility between the EU and Brazil for experimenting with future internet technologies. It will involve building a new testbed in Brazil and enhancing existing testbeds in Europe. The facilities will be federated to allow experiments using resources from both regions. Several pilot applications will be demonstrated to showcase the capabilities of the federated infrastructure. The project also aims to enhance collaboration between European and Brazilian researchers in future internet areas. It involves six work packages and has 15 partner organizations with the goal of advancing joint internet research between the two regions.
Ichiro Satoh presented his experiences with context-aware services from experiments conducted in real world settings like museums. The experiments tested different methods of providing audio and text annotations to visitors based on their location and past exhibits viewed. Evaluation of over 200 participants found that traditional paper-based posters achieved the highest learning scores, while methods relying on devices distracted visitors. Key lessons included informing users about available services, supporting legacy spaces with constraints, and managing heterogeneous systems in public settings.
The document discusses a project called MADUF that aims to maximize usage of digital video broadcasting (DVB) in Flanders. It will involve analyzing the legal framework, cellular networks, broadcast networks, available content and applications. Field trials will test apps with end users and gather data. Surveys will assess the state of the market, users, and gather feedback after the trials. The project seeks to involve end users from the beginning through completion to account for their different characteristics as innovators, early adopters, or other types of users.
This document summarizes the roles of Waseda University and NECTEC in international collaboration in information and communication technology (ICT) education, research, and standardization. It discusses partnerships between Thailand and Japan, including the launch of a testbed network in 2005 to enable real-time communication and on-demand access between universities. Examples are provided of telemedicine, e-learning, and a tele-education program hosted jointly by Waseda University, Thai universities, and NECTEC. The document also mentions a Japan-Thailand ministerial dialogue on IT and science & technology held at Waseda University in 2006.
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...my Pandit
Dive into the steadfast world of the Taurus Zodiac Sign. Discover the grounded, stable, and logical nature of Taurus individuals, and explore their key personality traits, important dates, and horoscope insights. Learn how the determination and patience of the Taurus sign make them the rock-steady achievers and anchors of the zodiac.
Storytelling is an incredibly valuable tool to share data and information. To get the most impact from stories there are a number of key ingredients. These are based on science and human nature. Using these elements in a story you can deliver information impactfully, ensure action and drive change.
The Genesis of BriansClub.cm Famous Dark WEb PlatformSabaaSudozai
BriansClub.cm, a famous platform on the dark web, has become one of the most infamous carding marketplaces, specializing in the sale of stolen credit card data.
The 10 Most Influential Leaders Guiding Corporate Evolution, 2024.pdfthesiliconleaders
In the recent edition, The 10 Most Influential Leaders Guiding Corporate Evolution, 2024, The Silicon Leaders magazine gladly features Dejan Štancer, President of the Global Chamber of Business Leaders (GCBL), along with other leaders.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This PowerPoint compilation offers a comprehensive overview of 20 leading innovation management frameworks and methodologies, selected for their broad applicability across various industries and organizational contexts. These frameworks are valuable resources for a wide range of users, including business professionals, educators, and consultants.
Each framework is presented with visually engaging diagrams and templates, ensuring the content is both informative and appealing. While this compilation is thorough, please note that the slides are intended as supplementary resources and may not be sufficient for standalone instructional purposes.
This compilation is ideal for anyone looking to enhance their understanding of innovation management and drive meaningful change within their organization. Whether you aim to improve product development processes, enhance customer experiences, or drive digital transformation, these frameworks offer valuable insights and tools to help you achieve your goals.
INCLUDED FRAMEWORKS/MODELS:
1. Stanford’s Design Thinking
2. IDEO’s Human-Centered Design
3. Strategyzer’s Business Model Innovation
4. Lean Startup Methodology
5. Agile Innovation Framework
6. Doblin’s Ten Types of Innovation
7. McKinsey’s Three Horizons of Growth
8. Customer Journey Map
9. Christensen’s Disruptive Innovation Theory
10. Blue Ocean Strategy
11. Strategyn’s Jobs-To-Be-Done (JTBD) Framework with Job Map
12. Design Sprint Framework
13. The Double Diamond
14. Lean Six Sigma DMAIC
15. TRIZ Problem-Solving Framework
16. Edward de Bono’s Six Thinking Hats
17. Stage-Gate Model
18. Toyota’s Six Steps of Kaizen
19. Microsoft’s Digital Transformation Framework
20. Design for Six Sigma (DFSS)
To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This presentation is a curated compilation of PowerPoint diagrams and templates designed to illustrate 20 different digital transformation frameworks and models. These frameworks are based on recent industry trends and best practices, ensuring that the content remains relevant and up-to-date.
Key highlights include Microsoft's Digital Transformation Framework, which focuses on driving innovation and efficiency, and McKinsey's Ten Guiding Principles, which provide strategic insights for successful digital transformation. Additionally, Forrester's framework emphasizes enhancing customer experiences and modernizing IT infrastructure, while IDC's MaturityScape helps assess and develop organizational digital maturity. MIT's framework explores cutting-edge strategies for achieving digital success.
These materials are perfect for enhancing your business or classroom presentations, offering visual aids to supplement your insights. Please note that while comprehensive, these slides are intended as supplementary resources and may not be complete for standalone instructional purposes.
Frameworks/Models included:
Microsoft’s Digital Transformation Framework
McKinsey’s Ten Guiding Principles of Digital Transformation
Forrester’s Digital Transformation Framework
IDC’s Digital Transformation MaturityScape
MIT’s Digital Transformation Framework
Gartner’s Digital Transformation Framework
Accenture’s Digital Strategy & Enterprise Frameworks
Deloitte’s Digital Industrial Transformation Framework
Capgemini’s Digital Transformation Framework
PwC’s Digital Transformation Framework
Cisco’s Digital Transformation Framework
Cognizant’s Digital Transformation Framework
DXC Technology’s Digital Transformation Framework
The BCG Strategy Palette
McKinsey’s Digital Transformation Framework
Digital Transformation Compass
Four Levels of Digital Maturity
Design Thinking Framework
Business Model Canvas
Customer Journey Map
3 Simple Steps To Buy Verified Payoneer Account In 2024SEOSMMEARTH
Buy Verified Payoneer Account: Quick and Secure Way to Receive Payments
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Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.AnnySerafinaLove
This letter, written by Kellen Harkins, Course Director at Full Sail University, commends Anny Love's exemplary performance in the Video Sharing Platforms class. It highlights her dedication, willingness to challenge herself, and exceptional skills in production, editing, and marketing across various video platforms like YouTube, TikTok, and Instagram.
Navigating the world of forex trading can be challenging, especially for beginners. To help you make an informed decision, we have comprehensively compared the best forex brokers in India for 2024. This article, reviewed by Top Forex Brokers Review, will cover featured award winners, the best forex brokers, featured offers, the best copy trading platforms, the best forex brokers for beginners, the best MetaTrader brokers, and recently updated reviews. We will focus on FP Markets, Black Bull, EightCap, IC Markets, and Octa.
Building Your Employer Brand with Social MediaLuanWise
Presented at The Global HR Summit, 6th June 2024
In this keynote, Luan Wise will provide invaluable insights to elevate your employer brand on social media platforms including LinkedIn, Facebook, Instagram, X (formerly Twitter) and TikTok. You'll learn how compelling content can authentically showcase your company culture, values, and employee experiences to support your talent acquisition and retention objectives. Additionally, you'll understand the power of employee advocacy to amplify reach and engagement – helping to position your organization as an employer of choice in today's competitive talent landscape.
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1. Experimentation Tools
for Networking
Research
Mathieu Lacage
INRIA, Planète
Nov 15th 2010
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 1 / 55
4. Protocol evaluation
Analytical
analysis
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 3 / 55
5. Protocol evaluation
Analytical
Simulator
analysis
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 3 / 55
6. Protocol evaluation
Analytical
Simulator Testbed
analysis
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 3 / 55
7. Protocol evaluation
Analytical
Simulator Testbed
analysis
Small
scale
field
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 3 / 55
8. Protocol evaluation
Analytical
Simulator Testbed
analysis
Large Small
scale scale
field field
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 3 / 55
9. Protocol evaluation
Analytical
Simulator Testbed
analysis
Large Small
In the
scale scale
wild
field field
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 3 / 55
10. Protocol evaluation
Analytical
Simulator Testbed
analysis
Large Small
In the
scale scale
wild
field field
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 3 / 55
11. Experimentation context
Experimentation
Realism
Time
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 4 / 55
12. Why ?
One protocol isolated
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 5 / 55
13. Why ?
One protocol isolated -> Multiple protocol
interaction
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 5 / 55
14. Why ?
One protocol isolated -> Multiple protocol
interaction
Steady state
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 5 / 55
15. Why ?
One protocol isolated -> Multiple protocol
interaction
Steady state -> Transient behavior
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 5 / 55
16. Cheaper hardware
Hardware
Cost
Time
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 6 / 55
17. Consequences
More testbeds
More Field tests
Time
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 7 / 55
18. Consequences
Less More testbeds
Simulations More Field tests
Alone
Time
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 7 / 55
19. Consequences
More Testbed+
Simulation
Time
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 7 / 55
21. Downsides
A lot more work
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 8 / 55
22. Downsides
A lot more work
Must master many experimentation
environments
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 8 / 55
23. Downsides
A lot more work
Must master many experimentation
environments
Must implement protocols twice
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 8 / 55
26. Objectives
Smooth transition simulations/testbed/field tests
Run real protocol implementation in simulation
Real
Code
Simulation Field
Simulation
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 9 / 55
27. Objectives
Smooth transition simulations/testbed/field tests
Run real protocol implementation in simulation
Use simulation as realtime emulator
Real RT
Code Sim
Simulation Field
Simulation Field
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 9 / 55
28. Problems
Run real protocol implementation in simulation
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
29. Problems
Run real protocol implementation in simulation
Virtualization of execution environment
Real Code
Simulation
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
30. Problems
Run real protocol implementation in simulation
Virtualization of execution environment
Use simulation as realtime emulator
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
31. Problems
Run real protocol implementation in simulation
Virtualization of execution environment
Use simulation as realtime emulator
Setup, deployment, of emulation platforms
RT RT
Field Field
Sim Sim
Deployment
Control
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
32. Problems
Run real protocol implementation in simulation
Virtualization of execution environment
Use simulation as realtime emulator
Setup, deployment, of emulation platforms
In both cases
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
33. Problems
Run real protocol implementation in simulation
Virtualization of execution environment
Use simulation as realtime emulator
Setup, deployment, of emulation platforms
In both cases
Transparency with other simulation models
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
34. Problems
Run real protocol implementation in simulation
Virtualization of execution environment
Direct Code Execution
Use simulation as realtime emulator
Setup, deployment, of emulation platforms
In both cases
Transparency with other simulation models
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
35. Problems
Run real protocol implementation in simulation
Virtualization of execution environment
Direct Code Execution
Use simulation as realtime emulator
Setup, deployment, of emulation platforms
NEPI
In both cases
Transparency with other simulation models
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
36. Problems
Run real protocol implementation in simulation
Virtualization of execution environment
Direct Code Execution
Use simulation as realtime emulator
Setup, deployment, of emulation platforms
NEPI
In both cases
Transparency with other simulation models
Simulated Packets
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 10 / 55
43. Scientific Contributions
Simulated packets
More CPU efficient than other simulators
Automatic conversion simulation/network format
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 12 / 55
44. Scientific Contributions
Simulated packets
More CPU efficient than other simulators
Automatic conversion simulation/network format
Direct Code Execution
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 12 / 55
45. Scientific Contributions
Simulated packets
More CPU efficient than other simulators
Automatic conversion simulation/network format
Direct Code Execution
10x more CPU efficient than other DCE
frameworks
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 12 / 55
46. Scientific Contributions
Simulated packets
More CPU efficient than other simulators
Automatic conversion simulation/network format
Direct Code Execution
10x more CPU efficient than other DCE
frameworks
Large applicability scope
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 12 / 55
47. Scientific Contributions
Simulated packets
More CPU efficient than other simulators
Automatic conversion simulation/network format
Direct Code Execution
10x more CPU efficient than other DCE
frameworks
Large applicability scope
NEPI
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 12 / 55
48. Scientific Contributions
Simulated packets
More CPU efficient than other simulators
Automatic conversion simulation/network format
Direct Code Execution
10x more CPU efficient than other DCE
frameworks
Large applicability scope
NEPI
Unified experiment description
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 12 / 55
49. Scientific Contributions
Simulated packets
More CPU efficient than other simulators
Automatic conversion simulation/network format
Direct Code Execution
10x more CPU efficient than other DCE
frameworks
Large applicability scope
NEPI
Unified experiment description
Automated deployment
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 12 / 55
53. Related Work
Two approaches
Packet is list of headers: GTNetS, OMNeT++,
SSFNet
MAC IP TCP Payload
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 15 / 55
54. Related Work
Two approaches
Packet is list of headers: GTNetS, OMNeT++,
SSFNet
MAC IP TCP Payload
Packet is buffer of bytes: Yans, GloMoSim
MAC IP TCP Payload
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 15 / 55
55. Pros and Cons
List Buffer
Fragmentation, Reassembly
Conversion real bytes
Simulation-only data
Pretty printing
CPU, memory efficiency
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 16 / 55
56. Our solution
Packet as buffer of bytes
Fragmentation, Reassembly
Automatic conversion to/from real bytes
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 17 / 55
57. Our solution
Packet as buffer of bytes
Fragmentation, Reassembly
Automatic conversion to/from real bytes
Tags
Simulation-only data
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 17 / 55
58. Our solution
Packet as buffer of bytes
Fragmentation, Reassembly
Automatic conversion to/from real bytes
Tags
Simulation-only data
Metadata
Pretty printing
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 17 / 55
59. Our solution
Packet as buffer of bytes
Fragmentation, Reassembly
Automatic conversion to/from real bytes
Tags
Simulation-only data
Metadata
Pretty printing
Copy On Write (COW)
CPU, memory efficiency
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 17 / 55
63. Contributions
More CPU efficient than other simulators
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 20 / 55
64. Contributions
More CPU efficient than other simulators
Transparent support for real network bytes
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 20 / 55
66. The manual approach
Global variables
static int g_var; static int [100]g_var_array;
g_var ++; g_var_array[current_id ()] ++;
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 22 / 55
67. The manual approach
Global variables
static int g_var; static int [100]g_var_array;
g_var ++; g_var_array[current_id ()] ++;
Redirect system calls
clock (); dce_clock ();
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 22 / 55
68. The manual approach
Global variables
static int g_var; static int [100]g_var_array;
g_var ++; g_var_array[current_id ()] ++;
Redirect system calls
clock (); dce_clock ();
Re-implement all system calls
clock_t dce_clock (void) {
return Simulator::Now ().GetMicroSeconds ();
}
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 22 / 55
69. The problem
Manual modifications: does not scale
Painful to do once
Impossible to do for software updates
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 23 / 55
71. Related work
Network Simulation Cradle
Automated source modifications for C code
Hard to extend to C++
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 24 / 55
72. Related work
Network Simulation Cradle
Automated source modifications for C code
Hard to extend to C++
Weaves
Automated textual assembly modifications
Invalid assumptions about compiler-generated
code
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 24 / 55
73. Related work
Network Simulation Cradle
Automated source modifications for C code
Hard to extend to C++
Weaves
Automated textual assembly modifications
Invalid assumptions about compiler-generated
code
COOJA
Automated memory virtualization
Slow
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 24 / 55
74. ns-3 DCE
Executable and Linkable Format (ELF) loader
Fast
Automated memory virtualization
Automated system call redirection
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 25 / 55
75. ns-3 DCE
Executable and Linkable Format (ELF) loader
Fast
Automated memory virtualization
Automated system call redirection
Userspace system calls
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 25 / 55
76. ns-3 DCE
Executable and Linkable Format (ELF) loader
Fast
Automated memory virtualization
Automated system call redirection
Userspace system calls
Kernelspace system calls
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 25 / 55
77. Loader Performance
Scenario:
udp-perf udp-perf
userspace DCE userspace DCE
Linux Linux Linux
UDP/IP UDP/IP UDP/IP
kernelspace DCE kernelspace DCE kernelspace DCE
PointToPointLink PointToPointLink
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 26 / 55
78. Loader Performance
100000
Cooja
ns-3
Packets per
10000
wall clock
second
vs
1000
Number of
nodes
100
0 10 20 30 40 50 60 70
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 27 / 55
79. Loader Performance
35000
Cooja
ns-3
30000
25000
Memory(bytes)
20000
vs
Number of 15000
nodes 10000
5000
0
0 10 20 30 40 50 60 70
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 28 / 55
80. System Performance
1e+06
dce-none
dce-user
dce-user+kernel
Packets per
100000
wall clock
second
vs
10000
Number of
nodes
1000
0 2 4 6 8 10 12 14 16 18 20
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 29 / 55
83. Contributions
10x more efficient than existing alternatives
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 32 / 55
84. Contributions
10x more efficient than existing alternatives
Larger scope than existing alternatives
Userspace: ping, traceroute, quagga, etc.
Kernelspace: Linux IP, TCP, etc.
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 32 / 55
85. Contributions
10x more efficient than existing alternatives
Larger scope than existing alternatives
Userspace: ping, traceroute, quagga, etc.
Kernelspace: Linux IP, TCP, etc.
Potential usecases:
Debugging platform: single debugger controls
all protocol instances
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 32 / 55
86. Contributions
10x more efficient than existing alternatives
Larger scope than existing alternatives
Userspace: ping, traceroute, quagga, etc.
Kernelspace: Linux IP, TCP, etc.
Potential usecases:
Debugging platform: single debugger controls
all protocol instances
Development platform
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 32 / 55
87. Contributions
10x more efficient than existing alternatives
Larger scope than existing alternatives
Userspace: ping, traceroute, quagga, etc.
Kernelspace: Linux IP, TCP, etc.
Potential usecases:
Debugging platform: single debugger controls
all protocol instances
Development platform
Test platform
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 32 / 55
94. Easy Deployment
Problem
Tap/VM creation and setup
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 35 / 55
95. Easy Deployment
Problem
Tap/VM creation and setup
Coherent IP address assignment across
simulation and VMs
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 35 / 55
96. Easy Deployment
Problem
Tap/VM creation and setup
Coherent IP address assignment across
simulation and VMs
Coherent IP forwarding tables across
simulation and VMs
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 35 / 55
97. Easy Deployment
Problem
Tap/VM creation and setup
Coherent IP address assignment across
simulation and VMs
Coherent IP forwarding tables across
simulation and VMs
Solution
Automate everything
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 35 / 55
98. Easy Deployment
Problem
Tap/VM creation and setup
Coherent IP address assignment across
simulation and VMs
Coherent IP forwarding tables across
simulation and VMs
Solution
Automate everything
BUT
Need global view of experiment topology
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 35 / 55
100. Related Work
Emulab Tcl: ad hoc, hard to generalize
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 36 / 55
101. Related Work
Emulab Tcl: ad hoc, hard to generalize
OMF Ruby: unclear how to extend it to model
complex topologies
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 36 / 55
102. Related Work
Emulab Tcl: ad hoc, hard to generalize
OMF Ruby: unclear how to extend it to model
complex topologies
OMNeT++ NED: hard to ensure correctness
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 36 / 55
103. Related Work
Emulab Tcl: ad hoc, hard to generalize
OMF Ruby: unclear how to extend it to model
complex topologies
OMNeT++ NED: hard to ensure correctness
SSF DML: hard to ensure correctness
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 36 / 55
104. Related Work
Emulab Tcl: ad hoc, hard to generalize
OMF Ruby: unclear how to extend it to model
complex topologies
OMNeT++ NED: hard to ensure correctness
SSF DML: hard to ensure correctness
Geni RSPEC: hard to ensure correctness
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 36 / 55
105. Related Work
Emulab Tcl: ad hoc, hard to generalize
OMF Ruby: unclear how to extend it to model
complex topologies
OMNeT++ NED: hard to ensure correctness
SSF DML: hard to ensure correctness
Geni RSPEC: hard to ensure correctness
Geni Omnispec: hard to ensure correctness
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 36 / 55
107. NEPI Object Model
Functional unit / Box Example:
IP stack
TCP stack
Ethernet card
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 37 / 55
108. NEPI Object Model
Functional unit / Box Example:
Attributes IP checksum
IP forwarding
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 37 / 55
109. NEPI Object Model
Functional unit / Box Example:
Attributes Out packets
Trace sources
In packets
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 37 / 55
110. NEPI Object Model
Functional unit / Box IP
Attributes
Trace sources dev
Connectors
node
Ethernet
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 37 / 55
111. NEPI Object Model
Functional unit / Box IP
Attributes
Trace sources dev app
Connectors
Connection checking node node
Ethernet Ethernet
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 37 / 55
112. NEPI Object Model
Functional unit / Box Node
Attributes
dev
Trace sources
Connectors cable
node node
cable
Connection checking Ethernet Ethernet
Hierarchical
Switch
port0 port1
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 37 / 55
113. Objective Scenario
VLC Wifi
Router
Server STA
Wifi VLC
Router
AP Client
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 38 / 55
114. NEPI Representation
NetNs IP ICMP ARP ns-3 IP ICMP ARP NetNs
Vlc Vlc
Node Mobility Mobility Node
Node Node
Wifi Loss Delay Wifi
TapNode FDNet Manager Manager FDNet TapNode
Net Net
Interface Device YansWifiChannel Device Interface
ApMac Device Device StaMac
YansWifiPhy YansWifiPhy
Nist Nist
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 39 / 55
115. Global IP topology
n0 n1 n2 n3
Tap net0 Fd Wifi Ap net1 Wifi Sta Fd net2 Tap
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 40 / 55
120. Papers Published
“Yet another network simulator”, Proceedings of
the 2006 workshop on ns-2
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 44 / 55
121. Papers Published
“Yet another network simulator”, Proceedings of
the 2006 workshop on ns-2
“NEPI: using independent simulators,
emulators, and testbeds for easy
experimentation”, SIGOPS Operating
Systems Review
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 44 / 55
122. Papers in progress
“The ns-3 network simulator: experience
learned”, Software Practice & Experience
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 45 / 55
123. Papers in progress
“The ns-3 network simulator: experience
learned”, Software Practice & Experience
“Direct Code Execution”, Networked Systems
Design and Implementation
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 45 / 55
125. Simulated Packets
More CPU efficient than other simulators
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 47 / 55
126. Simulated Packets
More CPU efficient than other simulators
Transparent support for real network bytes
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 47 / 55
127. Direct Code Execution
10x more CPU efficient than other DCE frameworks
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 48 / 55
128. Direct Code Execution
10x more CPU efficient than other DCE frameworks
A robust implementation
Userspace and kernelspace protocols
C,C++ protocols
ABI compatibility for userspace protocols
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 48 / 55
129. NEPI
An integrated experimentation environment
Unified experiment description
Entire workflow support
Automated deployment
Strong coherency checking
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 49 / 55
131. Impact
Instrumental in creating an
Active
Growing
Open source
Simulation community
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 50 / 55
132. Impact
Instrumental in creating an 0.6
0.5
Active
0.4
Growing
0.3
Open source
0.2
Simulation community
0.1
Contributors > 80
0
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 50 / 55
133. Impact
Instrumental in creating an 800
700
Active 600
Growing 500
400
Open source
300
Simulation community 200
Contributors > 80 100
0
Hundreds of users
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 50 / 55
134. Impact
Instrumental in creating an
Active
Growing
Open source
Simulation community
Contributors > 80
Hundreds of users
> 30 papers by users
2 sigcomm’09
1 sigcomm’10
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 50 / 55
137. Tracing with DCE
Need to recompile for tracing changes
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 52 / 55
138. Tracing with DCE
Need to recompile for tracing changes
Ideal workflow:
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 52 / 55
139. Tracing with DCE
Need to recompile for tracing changes
Ideal workflow:
Trace function foo in bar.cc
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 52 / 55
140. Tracing with DCE
Need to recompile for tracing changes
Ideal workflow:
Trace function foo in bar.cc
Trace line 122 in bar.cc
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 52 / 55
141. Tracing with DCE
Need to recompile for tracing changes
Ideal workflow:
Trace function foo in bar.cc
Trace line 122 in bar.cc
Trace variable foo at line 144 in bar.cc
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 52 / 55
142. Tracing with DCE
Need to recompile for tracing changes
Ideal workflow:
Trace function foo in bar.cc
Trace line 122 in bar.cc
Trace variable foo at line 144 in bar.cc
BUT, not Java: no introspection
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 52 / 55
145. Dynamic instrumentation
Locate code in memory
Parse dynamic loader data structures
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 53 / 55
146. Dynamic instrumentation
Locate code in memory
Parse dynamic loader data structures
Parse debugging information
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 53 / 55
147. Dynamic instrumentation
Locate code in memory
Parse dynamic loader data structures
Parse debugging information
Insert assembly hooks
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 53 / 55
148. Dynamic instrumentation
Locate code in memory
Parse dynamic loader data structures
Parse debugging information
Insert assembly hooks
Simple case (not thread-safe)
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 53 / 55
149. Dynamic instrumentation
Locate code in memory
Parse dynamic loader data structures
Parse debugging information
Insert assembly hooks
Simple case (not thread-safe)
General case harder
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 53 / 55
150. Dynamic instrumentation
Locate code in memory
Parse dynamic loader data structures
Parse debugging information
Insert assembly hooks
Simple case (not thread-safe)
General case harder
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 53 / 55
155. Multi-threaded Scheduler
Conservative algorithm implemented:
Fully transparent for users
Measurable speedup
Thread-safety is easy
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 54 / 55
156. Multi-threaded Scheduler
Conservative algorithm implemented:
Fully transparent for users
Measurable speedup
Thread-safety is easy
Efficient thread-safety is hard
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 54 / 55
157. Multi-threaded Scheduler
Conservative algorithm implemented:
Fully transparent for users
Measurable speedup
Thread-safety is easy
Efficient thread-safety is hard
Can we build more efficient thread-safety ?
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 54 / 55
158. Multi-threaded Scheduler
Conservative algorithm implemented:
Fully transparent for users
Measurable speedup
Thread-safety is easy
Efficient thread-safety is hard
Can we build more efficient thread-safety ?
Can we use optimistic algorithm transparently ?
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 54 / 55
159. Multi-threaded Scheduler
Conservative algorithm implemented:
Fully transparent for users
Measurable speedup
Thread-safety is easy
Efficient thread-safety is hard
Can we build more efficient thread-safety ?
Can we use optimistic algorithm transparently ?
Transparency is key !
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 54 / 55
160. Thank you !
Questions ?
Lacage (INRIA) Experimentation Tools & Network Research Nov 2010 55 / 55