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A3: APPLICATION AWARE ACCELERATION FOR WIRELESS DATA NETWORKS

A3: APPLICATION AWARE ACCELERATION FOR WIRELESS DATA NETWORKS. Athours: Zhenyun Zhuang and Tae-Young Chang GNAN Research Group, Georgia Tech, Atlanta, GA Raghupathy Sivakumar and Aravind Velayutham Asankya Networks, Inc., Atlanta, GA. MobiCom’06. OUTLINE. Motivation Methodology

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A3: APPLICATION AWARE ACCELERATION FOR WIRELESS DATA NETWORKS

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  1. A3: APPLICATION AWARE ACCELERATION FORWIRELESS DATA NETWORKS Athours: Zhenyun Zhuang and Tae-Young Chang GNAN Research Group, Georgia Tech, Atlanta, GA Raghupathy Sivakumar and Aravind Velayutham Asankya Networks, Inc., Atlanta, GA MobiCom’06

  2. OUTLINE • Motivation • Methodology • Transaction Prediction (TP) • Redundant and Aggressive Retransmissions (RAR) • Prioritized Fetching (PF) • Infinite Buffering (IB) • Application-aware Encoding (AE) • Integrated A3 Results • Pros and Cons

  3. MOTIVATION • Wireless Environments • High loss rate • Large delay • Low bandwidth • Improving the performance of popular applications in wireless environments • Common Internet File Sharing protocol(CIFS) • Simple Mail Transfer Protocol(SMTP) • Hyper-Text Transfer Protocol(HTTP) Common Internet File Sharing protocol(CIFS) Figure from Business Communications Review (April 2006)

  4. A3: APPLICATION-AWARE ACCELERATION • Application aware • Recognize applications • Application transparent • No modifications to applications • A set of design elements • Transaction Prediction (TP) • Redundant and Aggressive Retransmissions(RAR) • Prioritized Fetching (PF) • Infinite Buffering (IB) • Application-aware Encoding (AE)

  5. A3: APPLICATION-AWARE ACCELERATION • Implementation with Netfilter for Linux Systems • Using Netfilter hooks to capture the packets from traffic Deployment Model

  6. EXPERIMENTAL SETUP • Application Emulator (AppEm) • Using IxChariot to generate accurate application specific traffic patterns • A3 Emulator (A3Em) • Wireless Network Emulator(WNetEm) • are implemented with the framework of NS2

  7. TRANSACTION PREDICTION (TP) - DESIGN • CIFS requests only16 – 32KB data in a request • When requested data < BDP • Low utilization • Not pre-fetching • Deterministically predict future requests • Issue requests ahead of time CIFS Traffic Patterns

  8. TRANSACTION PREDICTION (TP) - DESIGN (CONT.) CIFS Traffic Patterns

  9. TRANSACTION PREDICTION (TP) - ISOLATED RESULT

  10. Explicit Loss Notification(ELN) • Only reduce the congestion window due to congestion loss. • Wireless TCP(WTCP) • Any lost segments will have to wait in the WTCP's buffer until the first one is confirmed to have been received.

  11. TRANSACTION PREDICTION (TP) - ISOLATED RESULT

  12. Redundant and Aggressive Retransmissions(RAR) - Design • RAR helps to protect thin session control messages from losses • Not applying to DATA SMTP Traffic Patterns

  13. Redundant and Aggressive Retransmissions(RAR) - Design • The interval between each redundant packets • RTTavg/10 • RTTavg is the average RTT observed so far (dynamical update) • Aggressive retransmission • Setting a timer = RTTavg + c • c is a small guard constant • If client gets response • stop the timer • If all copies of a message are lost • Time out=>Retransmission

  14. REDUNDANT AND AGGRESSIVE RETRANSMISSIONS(RAR) - ISOLATED RESULT

  15. Prioritized Fetching (PF) - Design • Using a plugin of web browser to query current focus window and scrolling information • The visible object will be downloaded immediately • If the object is not visible, then download it later

  16. PRIORITIZED FETCHING (PF) - ISOLATED RESULT

  17. INFINITE BUFFERING (IB) - DESIGN • Mobile device may have small connection buffer and reading slowly from connection buffer • Setting advertised window to MAXIMUM value 2KB data 2KB ACK window=0 0KB 2KB ACK window=2K

  18. INFINITE BUFFERING (IB) - DESIGN • Mobile device may have small connection buffer and reading slowly from connection buffer • Setting advertised window to MAXIMUM value • Exceeded data will be stored to 2nd storage 2KB data 2KB ACK window= MAXIMUM 0KB 2KB data 2KB 2nd Storage

  19. INFINITE BUFFERING (IB) - ISOLATED RESULT • How fast application layer reads the data? • What is the size of connection buffer?

  20. Application-aware Encoding (AE) - Design • Uses application and user specific information • SMTP – Using previous mails • Only available to a pair user • Not binary compression(such as ZIP) 10 Persons (100 emails)

  21. Application-aware Encoding (AE) - Design • A > B • Hi B, Do you have come to play a game with us? • B > A • Hi A, Sorry, I can’t go to play a game with you. => • 0x1 A, Sorry, I can’t go 0x2 0x3 a 0x40x5 you • Using 10-16bit to represent a word(6bytes)

  22. APPLICATION-AWARE ENCODING (AE) - ISOLATED RESULT

  23. INTEGRATED A3 RESULTS

  24. PROS • This paper presents a way to improve the performance of the applications obviously with application transparent • Did not present that how the processing overhead affects the performance • Infinite Buffering result CONS

  25. TRANSACTION PREDICTION (TP) - IMPLEMENTATION

  26. REDUNDANT AND AGGRESSIVE RETRANSMISSIONS(RAR)

  27. PRIORITIZED FETCHING (PF)

  28. Infinite Buffering (IB)

  29. Application-aware Encoding (AE)

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