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Providing Responsiveness to Multicast Congestion Control by Using ANN Predictive Model

Providing Responsiveness to Multicast Congestion Control by Using ANN Predictive Model. ดร . สมนึก พ่วงพรพิทักษ์ , สุชาติ คุ้มมะณี. Topics. Introduction to internet applications Modes of communication Multicast research motivation Multicast research objective

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Providing Responsiveness to Multicast Congestion Control by Using ANN Predictive Model

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  1. Providing Responsiveness to Multicast Congestion Control by Using ANN Predictive Model ดร.สมนึกพ่วงพรพิทักษ์ , สุชาติ คุ้มมะณี

  2. Topics • Introduction to internet applications • Modes of communication • Multicast research motivation • Multicast research objective • Principles of multicast congestion control protocols • Introduction to predictive models • Modeling design to multicast responsiveness • Multicast responsive result • Conclusion • Question

  3. Introduction to internet applications • Distributed Database • Distributed Computing • Real-Time Group Communication * • Video Conferencing * • Media-on-demand Broadcasting * • File Transfer Protocol (FTP) • Etc., * UDP Protocol

  4. Modes of communication • Unicast (1:1) * • Multicast (1:N) * • Broadcast (1:ALL) • Narrowcast (1:N) • Anycast (1:1) nearest • Concast (N:1) * Our interest

  5. Modes of communication (cont’d) • Unicast (1:1) • A flow from one source to one destination • IP packets contain destination IP address

  6. Modes of communication (cont’d) • Multicast (1:N) • A flow from one source transmit to a Group of destinations • IP packets contain a class D address for destination • Ranges from 224.0.0.0 to 239.255.255.255 (256k address)

  7. Modes of communication (cont’d) • Multicast (1:N) • Advantages • Lower overhead at the source • source sends only one packet • Bandwidth is conserved on share links • Only one copy of each packet is sent on each link • Disadvantages • Security • Business models • No Incentive for development (Overlaying L7) • Requirements • Group address Management • Packet duplication at routing nodes

  8. Multicast research motivation • IGMP Leave Latency Problem • IGMP is a group management protocol. It helps a multicast router create and update a list of loyal members related to each router interface * IGMP Leave termination completed about 9 sec No Response

  9. Multicast research motivation • IGMP Leave Latency Problem • IGMP is a group management protocol. It helps a multicast router create and update a list of loyal members related to each router interface • All Congestion control protocols are designed without tackling IGMPleave latency problem. • To solve this problem, we predict the share link bottleneck bandwidth.

  10. Multicast research objective • IGMP Leave Latency Problem Solving • Prediction share link bandwidth between 1-9 sec

  11. Multicast research objective • IGMP Leave Latency Problem Solving (predictive model accurate really ?) • A little variant on Share link bottleneck

  12. Principle of multicast congestion control protocols • two approaches to solve the congestion control problem • Single-Rated Multicast Congestion Control (SR-MCC) • Multi-Rate Multicast Congestion Control (MR-MCC) • Join experiment • Packet-pair probe

  13. Introduction to predictive models • Linear Model (ARIMA, FARIMA) • Higher Accuracy prediction • Cost of prediction complexity • Artificial Neural Network Model (ANN or NN) • High accuracy prediction • Low cost of prediction • Easy to implementation • Linear and non-linear support • Wavelet Model • Middle accuracy prediction • Cost of prediction complexity http://en.wikipedia.org/wiki/Neural_network

  14. Introduction to predictive models (cont’d) • ANN or NN Model

  15. Introduction to predictive models (cont’d) • ANN or NN Model • MLP (multilayer perceptron) • Back-propagation learning algorithm • Non-liner activation function (sigmoid or tansig) • 20 nodes input layer, 6 nodes hidden layer and 1 node output layer

  16. Modeling design to multicast responsiveness 1. 2. 3. 4. 5.

  17. Modeling design to multicast responsiveness (cont’d) 1. Get previous share link bottleneck network traffic • NS-2 Network Simulation • Capture network bandwidth every 1, 2, 3,…,9 sec/ 0.5 hour • Use congestion control protocol is PLM

  18. Modeling design to multicast responsiveness (cont’d) 2. Converting network traffic to ANN Predictive model

  19. Modeling design to multicast responsiveness (cont’d) 3. Adjust network traffic smooth by using Moving Average (MA) EMA = Exponential moving average SF = 2/(n+1) = smoothing factor Pt = current data EMAt-1 = previous exponential moving average

  20. Modeling design to multicast responsiveness (cont’d) 4. Neural network prediction One step ahead prediction

  21. Modeling design to multicast responsiveness (cont’d) 5. Prediction result

  22. Multicast responsive result 1-step-ahead 2-step-ahead 3-step-ahead 1-step-ahead (10 sec)

  23. Conclusion 1. Trying to solve IGMP Leave latency problem. 2. Providing responsiveness to multicast congestion control protocol 3. Using ANN to prediction share link bottleneck network traffic 4. Experimental results show that this model can increase the performance ofmulticast congestion control (in terms of responsiveness).

  24. Any Question. Providing Responsiveness to Multicast Congestion Control by Using ANN Predictive Model

  25. ThanksEND. Providing Responsiveness to Multicast Congestion Control by Using ANN Predictive Model

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