SlideShare a Scribd company logo
1 of 28
Rate Control for
Multimedia Streaming in
High Bandwidth Environment - 3


                Fitri Setyorini
                    Nakazato Lab
Content

   Rate control definition
   Non Linear Theory
   Recent Development of research
   Solution proposal
Facts about Rate Control

   End to end protocol
   It is used to deliver UDP packet, via RTP as the
    carriage
   in certain speed based on the information
   The information used is RTCP packet, which is
    feedbacked through the source
Rate Control

     SOURCE    Receiver
So..we need to keep the traffic
Not to be like this
This is what

RATE CONTROL

      Do
How to control it ?

   We have information from the feedback,
    −   What kind of information available ?
   We have to use equation to control the speed,
    −   What kind of equation we will use ?
Feedback Information

   1. Number of packet delivered at receiver
   2. Loss occurred at receiver
   3. Time needed to travel from source to receiver
    (RTT)
Non Linear Theory

 Total rate defines the rate from the source
 Constitute of the
  − constant source rate, Ini(k) ;
  − feedback rate, U(k).
 We use feedback to control rate
   If packet dropping occurs, the feedback rate is negative
   and source will reduce its rate.
   If no packet dropping, the feedback rate is positive and
   the source will increase the rate
 We called it non linear because the theory predict
 the packet accumulation non linearly
Dumbbell topology
Objectives

   No Drop
   Higher Throughput
State of Research

   We still use priority for RTCP packet on the router
    −   Without priority, RTCP packet will be dropped just
        like RTP packet, therefore the rate control won't work
        efficiently
    −   New time out mechanism is necessary to smooth out
        some lost RTCP packets
   Start up mechanism had not been decided
    −   Before RTCP packet is received, we can not control the
        speed
    −   Any idea ?
   Delayed feedback problem
    −   If the propagation delay is too big, then the
        information will be too late to be received and
        processed. The feedback will be obsolete, because by
        that time the network condition already change
    −   Can not be avoided because this is the nature of
        network
Drop : buffer 200,delay 10ms
Drop : buffer 200,delay 200ms
Throughput : buffer 200,delay 10ms
Throughput : buffer 200,delay 200ms
Solution to Delayed feedback problem


    Simplest thing to do :
      Increase RTCP packets ahead, to avoid lack of
      information which cause losses
1 RTCP/RTT
2 RTCP/RTT
4 RTCP/RTT
Shortcomings :

   If we sent RTCP after drop happens, it will be too
    late to prevent dropping
   We can schedule some RTCP packet to be sent
    ahead in the prescribed interval by looking at
    RTT, but the questions are
    −   How many RTCP is necessary ?
    −   When we need to launch RTCP or what is the ideal
        RTCP interval ?
   We do not want to flood the network with RTCP
    packet
Solution (1/2)

   Start Up problem :
    −   We use back to back packet to detect the bottleneck
        link
    −   We have bottleneck bw, we can start with it ->
        SOLVED
   Back to back (B2B) packet : 1500 bytes
   We measure interval between 2 consecutive B2B
   Bottleneck bandwidth = (1500*8)/interval
   As initial state, we use B2B bandwidth as RTP
    rate
Solution (2/2)

   Delayed Feedback problem :
    −   The RTCP maybe too late whilst network condition
        change.
    −   Why don't we predict the network condition to prevent
        dropping
    −   Prediction by the following method
            Combining ARMAX algorithm and neural network or
            Analyzing group behaviour of group flow
Combining ARMAX with
Neural Network
   The author of non linear already presume the
    problem with variable delay, therefore he propose
    a more complicated NN to deal with delay
   NN can have unpredictable result (which is why
    we do not prefer)
   NN is used to find the parameter for accumulated
    traffic
   What kind of NN suitable for our model ?
Analysing Group Behaviour

   Dropping occurs because all flows put high
    number of packet in the network
   Dropping in one flow reflects all other flow
    condition
   Using this information, we can predict group
    behavior
   Group behavior will be used to detect when we
    should launch RTCP packet
Thank you for your attention

More Related Content

What's hot

Congestion control in tcp
Congestion control in tcpCongestion control in tcp
Congestion control in tcpsamarai_apoc
 
Congestion control
Congestion controlCongestion control
Congestion controlAbhay Pai
 
NZNOG 2020: Buffers, Buffer Bloat and BBR
NZNOG 2020: Buffers, Buffer Bloat and BBRNZNOG 2020: Buffers, Buffer Bloat and BBR
NZNOG 2020: Buffers, Buffer Bloat and BBRAPNIC
 
Tcp Reliability Flow Control
Tcp Reliability Flow ControlTcp Reliability Flow Control
Tcp Reliability Flow ControlRam Dutt Shukla
 
A packet drop guesser module for congestion Control protocols for high speed ...
A packet drop guesser module for congestion Control protocols for high speed ...A packet drop guesser module for congestion Control protocols for high speed ...
A packet drop guesser module for congestion Control protocols for high speed ...ijcseit
 
Congestion avoidance in TCP
Congestion avoidance in TCPCongestion avoidance in TCP
Congestion avoidance in TCPselvakumar_b1985
 
Tcp congestion avoidance algorithm identification
Tcp congestion avoidance algorithm identificationTcp congestion avoidance algorithm identification
Tcp congestion avoidance algorithm identificationBala Lavanya
 
Computer network (13)
Computer network (13)Computer network (13)
Computer network (13)NYversity
 
TCP congestion control
TCP congestion controlTCP congestion control
TCP congestion controlShubham Jain
 
Tcp Immediate Data Transfer
Tcp Immediate Data TransferTcp Immediate Data Transfer
Tcp Immediate Data TransferRam Dutt Shukla
 
Leaky Bucket & Tocken Bucket - Traffic shaping
Leaky Bucket & Tocken Bucket - Traffic shapingLeaky Bucket & Tocken Bucket - Traffic shaping
Leaky Bucket & Tocken Bucket - Traffic shapingVimal Dewangan
 

What's hot (20)

Congestion control in tcp
Congestion control in tcpCongestion control in tcp
Congestion control in tcp
 
Admission control
Admission controlAdmission control
Admission control
 
Tcp(no ip) review part1
Tcp(no ip) review part1Tcp(no ip) review part1
Tcp(no ip) review part1
 
Congestion Control
Congestion ControlCongestion Control
Congestion Control
 
Congestion control
Congestion controlCongestion control
Congestion control
 
Congestion Control
Congestion ControlCongestion Control
Congestion Control
 
Congestion control
Congestion controlCongestion control
Congestion control
 
Lect9 (1)
Lect9 (1)Lect9 (1)
Lect9 (1)
 
Congestion control
Congestion controlCongestion control
Congestion control
 
NZNOG 2020: Buffers, Buffer Bloat and BBR
NZNOG 2020: Buffers, Buffer Bloat and BBRNZNOG 2020: Buffers, Buffer Bloat and BBR
NZNOG 2020: Buffers, Buffer Bloat and BBR
 
Tcp Reliability Flow Control
Tcp Reliability Flow ControlTcp Reliability Flow Control
Tcp Reliability Flow Control
 
Congestion control avoidance
Congestion control avoidanceCongestion control avoidance
Congestion control avoidance
 
A packet drop guesser module for congestion Control protocols for high speed ...
A packet drop guesser module for congestion Control protocols for high speed ...A packet drop guesser module for congestion Control protocols for high speed ...
A packet drop guesser module for congestion Control protocols for high speed ...
 
Congestion avoidance in TCP
Congestion avoidance in TCPCongestion avoidance in TCP
Congestion avoidance in TCP
 
Tcp
TcpTcp
Tcp
 
Tcp congestion avoidance algorithm identification
Tcp congestion avoidance algorithm identificationTcp congestion avoidance algorithm identification
Tcp congestion avoidance algorithm identification
 
Computer network (13)
Computer network (13)Computer network (13)
Computer network (13)
 
TCP congestion control
TCP congestion controlTCP congestion control
TCP congestion control
 
Tcp Immediate Data Transfer
Tcp Immediate Data TransferTcp Immediate Data Transfer
Tcp Immediate Data Transfer
 
Leaky Bucket & Tocken Bucket - Traffic shaping
Leaky Bucket & Tocken Bucket - Traffic shapingLeaky Bucket & Tocken Bucket - Traffic shaping
Leaky Bucket & Tocken Bucket - Traffic shaping
 

Viewers also liked

Viewers also liked (11)

Tetcon2016 160104
Tetcon2016 160104Tetcon2016 160104
Tetcon2016 160104
 
Gorgona schooltrip
Gorgona schooltripGorgona schooltrip
Gorgona schooltrip
 
台灣國立公園寫真集
台灣國立公園寫真集台灣國立公園寫真集
台灣國立公園寫真集
 
Michael Jackson memorial - first web screens
Michael Jackson memorial - first web screensMichael Jackson memorial - first web screens
Michael Jackson memorial - first web screens
 
Maui Referral
Maui ReferralMaui Referral
Maui Referral
 
Chocolate Storyboard
Chocolate StoryboardChocolate Storyboard
Chocolate Storyboard
 
Asesoria Escolar 1
Asesoria Escolar 1Asesoria Escolar 1
Asesoria Escolar 1
 
Journal of Natural Sciences Ajmer NetAct cover page
Journal of Natural Sciences Ajmer NetAct cover page Journal of Natural Sciences Ajmer NetAct cover page
Journal of Natural Sciences Ajmer NetAct cover page
 
Conformación Gobierno Escolar
Conformación Gobierno EscolarConformación Gobierno Escolar
Conformación Gobierno Escolar
 
Vanktesh Irrigation Systems Pvt Ltd NetAct Technologies
Vanktesh Irrigation Systems Pvt Ltd NetAct TechnologiesVanktesh Irrigation Systems Pvt Ltd NetAct Technologies
Vanktesh Irrigation Systems Pvt Ltd NetAct Technologies
 
RPSC Online : How to Apply
RPSC Online : How to ApplyRPSC Online : How to Apply
RPSC Online : How to Apply
 

Similar to Zemi08july09

RIPE 80: Buffers and Protocols
RIPE 80: Buffers and ProtocolsRIPE 80: Buffers and Protocols
RIPE 80: Buffers and ProtocolsAPNIC
 
Analytical Research of TCP Variants in Terms of Maximum Throughput
Analytical Research of TCP Variants in Terms of Maximum ThroughputAnalytical Research of TCP Variants in Terms of Maximum Throughput
Analytical Research of TCP Variants in Terms of Maximum ThroughputIJLT EMAS
 
Mobile Transpot Layer
Mobile Transpot LayerMobile Transpot Layer
Mobile Transpot LayerMaulik Patel
 
DLC_23 (3).pptx
DLC_23 (3).pptxDLC_23 (3).pptx
DLC_23 (3).pptxzulhelmanz
 
MANET Routing Protocols , a case study
MANET Routing Protocols , a case studyMANET Routing Protocols , a case study
MANET Routing Protocols , a case studyRehan Hattab
 
Aceleracion TCP Mikrotik.pdf
Aceleracion TCP Mikrotik.pdfAceleracion TCP Mikrotik.pdf
Aceleracion TCP Mikrotik.pdfWifiCren
 
Computer Networks Module 2.pdf
Computer Networks Module 2.pdfComputer Networks Module 2.pdf
Computer Networks Module 2.pdfShanthalaKV
 
Computer Communication Networks, network layer performance.pptx
Computer Communication Networks, network layer performance.pptxComputer Communication Networks, network layer performance.pptx
Computer Communication Networks, network layer performance.pptxElectro00
 
Ch 18 intro to network layer - section 3
Ch 18   intro to network layer - section 3Ch 18   intro to network layer - section 3
Ch 18 intro to network layer - section 3Hossam El-Deen Osama
 
AusNOG 2019: TCP and BBR
AusNOG 2019: TCP and BBRAusNOG 2019: TCP and BBR
AusNOG 2019: TCP and BBRAPNIC
 
Improving Performance of TCP in Wireless Environment using TCP-P
Improving Performance of TCP in Wireless Environment using TCP-PImproving Performance of TCP in Wireless Environment using TCP-P
Improving Performance of TCP in Wireless Environment using TCP-PIDES Editor
 
RTP_RTCP.ppt
RTP_RTCP.pptRTP_RTCP.ppt
RTP_RTCP.pptumas1234
 
Designing TCP-Friendly Window-based Congestion Control
Designing TCP-Friendly Window-based Congestion ControlDesigning TCP-Friendly Window-based Congestion Control
Designing TCP-Friendly Window-based Congestion Controlsoohyunc
 

Similar to Zemi08july09 (20)

Lect9
Lect9Lect9
Lect9
 
CN UNIT III.pptx
CN UNIT III.pptxCN UNIT III.pptx
CN UNIT III.pptx
 
RIPE 80: Buffers and Protocols
RIPE 80: Buffers and ProtocolsRIPE 80: Buffers and Protocols
RIPE 80: Buffers and Protocols
 
Transport layer
Transport layerTransport layer
Transport layer
 
Analytical Research of TCP Variants in Terms of Maximum Throughput
Analytical Research of TCP Variants in Terms of Maximum ThroughputAnalytical Research of TCP Variants in Terms of Maximum Throughput
Analytical Research of TCP Variants in Terms of Maximum Throughput
 
Mobile Transpot Layer
Mobile Transpot LayerMobile Transpot Layer
Mobile Transpot Layer
 
DLC_23 (3).pptx
DLC_23 (3).pptxDLC_23 (3).pptx
DLC_23 (3).pptx
 
MANET Routing Protocols , a case study
MANET Routing Protocols , a case studyMANET Routing Protocols , a case study
MANET Routing Protocols , a case study
 
Aceleracion TCP Mikrotik.pdf
Aceleracion TCP Mikrotik.pdfAceleracion TCP Mikrotik.pdf
Aceleracion TCP Mikrotik.pdf
 
Mcseminar
McseminarMcseminar
Mcseminar
 
Computer Networks Module 2.pdf
Computer Networks Module 2.pdfComputer Networks Module 2.pdf
Computer Networks Module 2.pdf
 
Wmc 023
Wmc  023Wmc  023
Wmc 023
 
Computer Communication Networks, network layer performance.pptx
Computer Communication Networks, network layer performance.pptxComputer Communication Networks, network layer performance.pptx
Computer Communication Networks, network layer performance.pptx
 
Ch 18 intro to network layer - section 3
Ch 18   intro to network layer - section 3Ch 18   intro to network layer - section 3
Ch 18 intro to network layer - section 3
 
AusNOG 2019: TCP and BBR
AusNOG 2019: TCP and BBRAusNOG 2019: TCP and BBR
AusNOG 2019: TCP and BBR
 
presentation
presentationpresentation
presentation
 
Bg4101335337
Bg4101335337Bg4101335337
Bg4101335337
 
Improving Performance of TCP in Wireless Environment using TCP-P
Improving Performance of TCP in Wireless Environment using TCP-PImproving Performance of TCP in Wireless Environment using TCP-P
Improving Performance of TCP in Wireless Environment using TCP-P
 
RTP_RTCP.ppt
RTP_RTCP.pptRTP_RTCP.ppt
RTP_RTCP.ppt
 
Designing TCP-Friendly Window-based Congestion Control
Designing TCP-Friendly Window-based Congestion ControlDesigning TCP-Friendly Window-based Congestion Control
Designing TCP-Friendly Window-based Congestion Control
 

Recently uploaded

Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxRustici Software
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdfSandro Moreira
 
Decarbonising Commercial Real Estate: The Role of Operational Performance
Decarbonising Commercial Real Estate: The Role of Operational PerformanceDecarbonising Commercial Real Estate: The Role of Operational Performance
Decarbonising Commercial Real Estate: The Role of Operational PerformanceIES VE
 
Navigating Identity and Access Management in the Modern Enterprise
Navigating Identity and Access Management in the Modern EnterpriseNavigating Identity and Access Management in the Modern Enterprise
Navigating Identity and Access Management in the Modern EnterpriseWSO2
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Victor Rentea
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxRemote DBA Services
 
TEST BANK For Principles of Anatomy and Physiology, 16th Edition by Gerard J....
TEST BANK For Principles of Anatomy and Physiology, 16th Edition by Gerard J....TEST BANK For Principles of Anatomy and Physiology, 16th Edition by Gerard J....
TEST BANK For Principles of Anatomy and Physiology, 16th Edition by Gerard J....rightmanforbloodline
 
JavaScript Usage Statistics 2024 - The Ultimate Guide
JavaScript Usage Statistics 2024 - The Ultimate GuideJavaScript Usage Statistics 2024 - The Ultimate Guide
JavaScript Usage Statistics 2024 - The Ultimate GuidePixlogix Infotech
 
Simplifying Mobile A11y Presentation.pptx
Simplifying Mobile A11y Presentation.pptxSimplifying Mobile A11y Presentation.pptx
Simplifying Mobile A11y Presentation.pptxMarkSteadman7
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native ApplicationsWSO2
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businesspanagenda
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingEdi Saputra
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Jeffrey Haguewood
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityWSO2
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontologyjohnbeverley2021
 
Stronger Together: Developing an Organizational Strategy for Accessible Desig...
Stronger Together: Developing an Organizational Strategy for Accessible Desig...Stronger Together: Developing an Organizational Strategy for Accessible Desig...
Stronger Together: Developing an Organizational Strategy for Accessible Desig...caitlingebhard1
 
Design and Development of a Provenance Capture Platform for Data Science
Design and Development of a Provenance Capture Platform for Data ScienceDesign and Development of a Provenance Capture Platform for Data Science
Design and Development of a Provenance Capture Platform for Data SciencePaolo Missier
 
API Governance and Monetization - The evolution of API governance
API Governance and Monetization -  The evolution of API governanceAPI Governance and Monetization -  The evolution of API governance
API Governance and Monetization - The evolution of API governanceWSO2
 

Recently uploaded (20)

Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..Understanding the FAA Part 107 License ..
Understanding the FAA Part 107 License ..
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
Decarbonising Commercial Real Estate: The Role of Operational Performance
Decarbonising Commercial Real Estate: The Role of Operational PerformanceDecarbonising Commercial Real Estate: The Role of Operational Performance
Decarbonising Commercial Real Estate: The Role of Operational Performance
 
Navigating Identity and Access Management in the Modern Enterprise
Navigating Identity and Access Management in the Modern EnterpriseNavigating Identity and Access Management in the Modern Enterprise
Navigating Identity and Access Management in the Modern Enterprise
 
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
 
Vector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptxVector Search -An Introduction in Oracle Database 23ai.pptx
Vector Search -An Introduction in Oracle Database 23ai.pptx
 
TEST BANK For Principles of Anatomy and Physiology, 16th Edition by Gerard J....
TEST BANK For Principles of Anatomy and Physiology, 16th Edition by Gerard J....TEST BANK For Principles of Anatomy and Physiology, 16th Edition by Gerard J....
TEST BANK For Principles of Anatomy and Physiology, 16th Edition by Gerard J....
 
JavaScript Usage Statistics 2024 - The Ultimate Guide
JavaScript Usage Statistics 2024 - The Ultimate GuideJavaScript Usage Statistics 2024 - The Ultimate Guide
JavaScript Usage Statistics 2024 - The Ultimate Guide
 
Simplifying Mobile A11y Presentation.pptx
Simplifying Mobile A11y Presentation.pptxSimplifying Mobile A11y Presentation.pptx
Simplifying Mobile A11y Presentation.pptx
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital Adaptability
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
Stronger Together: Developing an Organizational Strategy for Accessible Desig...
Stronger Together: Developing an Organizational Strategy for Accessible Desig...Stronger Together: Developing an Organizational Strategy for Accessible Desig...
Stronger Together: Developing an Organizational Strategy for Accessible Desig...
 
Design and Development of a Provenance Capture Platform for Data Science
Design and Development of a Provenance Capture Platform for Data ScienceDesign and Development of a Provenance Capture Platform for Data Science
Design and Development of a Provenance Capture Platform for Data Science
 
API Governance and Monetization - The evolution of API governance
API Governance and Monetization -  The evolution of API governanceAPI Governance and Monetization -  The evolution of API governance
API Governance and Monetization - The evolution of API governance
 

Zemi08july09

  • 1. Rate Control for Multimedia Streaming in High Bandwidth Environment - 3 Fitri Setyorini Nakazato Lab
  • 2. Content  Rate control definition  Non Linear Theory  Recent Development of research  Solution proposal
  • 3. Facts about Rate Control  End to end protocol  It is used to deliver UDP packet, via RTP as the carriage  in certain speed based on the information  The information used is RTCP packet, which is feedbacked through the source
  • 4. Rate Control SOURCE Receiver
  • 5. So..we need to keep the traffic
  • 6. Not to be like this
  • 7. This is what RATE CONTROL Do
  • 8. How to control it ?  We have information from the feedback, − What kind of information available ?  We have to use equation to control the speed, − What kind of equation we will use ?
  • 9. Feedback Information  1. Number of packet delivered at receiver  2. Loss occurred at receiver  3. Time needed to travel from source to receiver (RTT)
  • 10. Non Linear Theory Total rate defines the rate from the source Constitute of the − constant source rate, Ini(k) ; − feedback rate, U(k). We use feedback to control rate If packet dropping occurs, the feedback rate is negative and source will reduce its rate. If no packet dropping, the feedback rate is positive and the source will increase the rate We called it non linear because the theory predict the packet accumulation non linearly
  • 12. Objectives  No Drop  Higher Throughput
  • 13. State of Research  We still use priority for RTCP packet on the router − Without priority, RTCP packet will be dropped just like RTP packet, therefore the rate control won't work efficiently − New time out mechanism is necessary to smooth out some lost RTCP packets  Start up mechanism had not been decided − Before RTCP packet is received, we can not control the speed − Any idea ?
  • 14. Delayed feedback problem − If the propagation delay is too big, then the information will be too late to be received and processed. The feedback will be obsolete, because by that time the network condition already change − Can not be avoided because this is the nature of network
  • 15. Drop : buffer 200,delay 10ms
  • 16. Drop : buffer 200,delay 200ms
  • 17. Throughput : buffer 200,delay 10ms
  • 18. Throughput : buffer 200,delay 200ms
  • 19. Solution to Delayed feedback problem  Simplest thing to do : Increase RTCP packets ahead, to avoid lack of information which cause losses
  • 23. Shortcomings :  If we sent RTCP after drop happens, it will be too late to prevent dropping  We can schedule some RTCP packet to be sent ahead in the prescribed interval by looking at RTT, but the questions are − How many RTCP is necessary ? − When we need to launch RTCP or what is the ideal RTCP interval ?  We do not want to flood the network with RTCP packet
  • 24. Solution (1/2)  Start Up problem : − We use back to back packet to detect the bottleneck link − We have bottleneck bw, we can start with it -> SOLVED  Back to back (B2B) packet : 1500 bytes  We measure interval between 2 consecutive B2B  Bottleneck bandwidth = (1500*8)/interval  As initial state, we use B2B bandwidth as RTP rate
  • 25. Solution (2/2)  Delayed Feedback problem : − The RTCP maybe too late whilst network condition change. − Why don't we predict the network condition to prevent dropping − Prediction by the following method  Combining ARMAX algorithm and neural network or  Analyzing group behaviour of group flow
  • 26. Combining ARMAX with Neural Network  The author of non linear already presume the problem with variable delay, therefore he propose a more complicated NN to deal with delay  NN can have unpredictable result (which is why we do not prefer)  NN is used to find the parameter for accumulated traffic  What kind of NN suitable for our model ?
  • 27. Analysing Group Behaviour  Dropping occurs because all flows put high number of packet in the network  Dropping in one flow reflects all other flow condition  Using this information, we can predict group behavior  Group behavior will be used to detect when we should launch RTCP packet
  • 28. Thank you for your attention