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Differentiated Congestion Management of Data Traffic for Data center Ethernet

Differentiated Congestion Management of Data Traffic for Data center Ethernet. B99705025 資管三 陳育旋. author. Shuo Fang, Student Member, IEEE, Chuan Heng Foh , Senior Member, IEEE, and Khin Mi Mi Aung , Senior Member, IEEE. I ntroduction. Fibre Channel over Ethernet ( FCoE )

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Differentiated Congestion Management of Data Traffic for Data center Ethernet

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  1. Differentiated Congestion Management of Data Traffic for Data center Ethernet B99705025 資管三 陳育旋

  2. author ShuoFang, Student Member, IEEE, Chuan HengFoh, Senior Member, IEEE, and Khin Mi MiAung, Senior Member, IEEE

  3. Introduction Fibre Channel over Ethernet(FCoE) -- use Ethernet technology to carry Fibre Channel -- Fibre Channel are encapsulated in Ethernet to be transmitted FCoE has some benefit -- reduce power consumption for I/O operation -- eliminate redundancy in the network -- I/O consolidation among Local Area Networks(LANs) and Storage Area Networks(SANs)

  4. SANs (reference) • Storage Area Networks • 將許多儲存裝置從區域網路獨立出來成為另一個網路 • 透過光纖通道﹙Fibre Channel﹚與伺服主 機做連結 • 具備快速備份與災難復原能力 • 但成本較高、且建置費時 http://goo.gl/TxKBj

  5. Introduction • However…. --Fibre Channel (FC) is designed to achieve high speed lossless packet transportation -- Ethernet has no control on the traffic congestion How to consolidate? Differentiated congestion control in Ethernet!

  6. outline • Introduction • Ethernet Congestion Management • Differentiated Congestion Control • Analysis (experiment) • conclusion

  7. outline • Introduction • Ethernet Congestion Management • Differentiated Congestion Control • Analysis (experiment) • conclusion

  8. Ethernet Congestion Management • Implementing a particular ECN at switches and rate limiter at host

  9. Ethernet Congestion Management Qoff is the offset of the current buffer utilization with respect to Qeq (+ or - ) Qdeltais the change in length of the queue since the last sampled frame

  10. Ethernet Congestion Management • In ECM, each rate limiter implements a variation of AIMD for its rate adjustment. • A rate limiter periodically increase its sending rate • Fb = feedback signal

  11. outline • Introduction • Ethernet Congestion Management • Differentiated Congestion Control • Analysis (experiment) • conclusion

  12. Differentiated Congestion Control • we propose using different AIMD parameter sets for the rate limiters to achieve congestion control differentiation

  13. Differentiated Congestion Control • Queue Management in Congestion Point • Rate Limiters in the Reaction Point

  14. Differentiated Congestion Control • Queue Management in Congestion Point • Rate Limiters in the Reaction Point

  15. Queue Management in Congestion Point • A congestion point (CP) features a queue management • which is mainly responsible for congestion detection, congestion , notification and packet drop policy. • when the buffer utilization exceeds Tsc, all LAN traffic, being the low priority traffic, will be dropped.

  16. Differentiated Congestion Control • Queue Management in Congestion Point • Rate Limiters in the Reaction Point

  17. Rate Limiters in the Reaction Point • A rate limiter regulates the traffic flow by controlling the transmission rate using an AIMD based rate adjustment operation • the rate limiter maintains a variable called congestion window to regulate the transmission rate

  18. Rate Limiters in the Reaction Point • The value of congestion window is initialized to be one. This value increases linearly over a predefined constant time interval called a slot.

  19. outline • Introduction • Ethernet Congestion Management • Differentiated Congestion Control • Analysis (experiment) • conclusion

  20. Analysis(experiment) SAN (a1,b1) LAN (a2,b2) destination destination destination Buffer (bottleneck) Background traffic

  21. Analysis(experiment) • Performance comparison with various schemes • Protections with presence of misbehaved hosts • Bandwidth utilization differentiation • Setting of marking probabilities • A case study of multiple types of traffic

  22. Analysis(experiment) • Performance comparison with various schemes • Protections with presence of misbehaved hosts • Bandwidth utilization differentiation • Setting of marking probabilities • A case study of multiple types of traffic

  23. Performance comparison with various schemes • to investigate the effectiveness and system stability of our congestion control

  24. Analysis(experiment) • Performance comparison with various schemes • Protections with presence of misbehaved hosts • Bandwidth utilization differentiation • Setting of marking probabilities • A case study of multiple types of traffic

  25. Protections with presence of misbehaved hosts • we consider the situation where LAN sources do not regulate their rates based on the notification instructions

  26. Analysis(experiment) • Performance comparison with various schemes • Protections with presence of misbehaved hosts • Bandwidth utilization differentiation • Setting of marking probabilities • A case study of multiple types of traffic

  27. Bandwidth utilization differentiation • we analyze the bandwidth differentiation feature of our proposed system

  28. Bandwidth utilization differentiation

  29. Analysis(experiment) • Performance comparison with various schemes • Protections with presence of misbehaved hosts • Bandwidth utilization differentiation • Setting of marking probabilities • A case study of multiple types of traffic

  30. Setting of marking probabilities • Although setting a higher marking probability canensure a stable buffer level around equilibrium threshold aswell, this is unnecessary due to the more overhead it mayintroduce

  31. Setting of marking probabilities

  32. Analysis(experiment) • Performance comparison with various schemes • Protections with presence of misbehaved hosts • Bandwidth utilization differentiation • Setting of marking probabilities • A case study of multiple types of traffic

  33. A case study of multiple types of traffic

  34. A case study of multiple types of traffic • Our scenario deals with uploading of files from clients and a total of three types of traffic are involved

  35. A case study of multiple types of traffic 1.Client1 and Client2 first connect to ApplicationServer1 sending upload requests of LAN traffic type, and this traffic is light. 2. On reception of any request, Application Server1connects to Metadata Server for data index

  36. A case study of multiple types of traffic 3.&3.5 MetadataServer replies with index to identify and track data storage locations. Traffic load between ApplicationServer1 and MetadataServer can be high 4. After index being obtained, Client1 and Client2 connect to the storage directly for file writing, which is SAN traffic # HPCServer1 communicates with HPC Server2 with Inter Process Computing (IPC) traffic

  37. A case study of multiple types of traffic • Lowest priority : LAN • Higher priority : SAN • Highest priority : IPC • We adopt a target bandwidth utilization ratio of 1:1.4:1.8 for W1:W2:W3 where W1:W2:W3 describe bandwidth utilization for LAN, SAN and IPC traffic.

  38. A case study of multiple types of traffic

  39. outline • Introduction • Ethernet Congestion Management • Differentiated Congestion Control • Analysis (experiment) • conclusion

  40. conclusion • Our proposed method considered using different AIMD settings for the rate limiter operations and took protection of high priority traffic into account to regulate malicious parties

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