Mahout: Low-Overhead Datacenter Traffic Management using End-Host-Based Elephant Detection. Vasileios Dimitrakis

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1 Mahout: Low-Overhead Datacenter Traffic Management using End-Host-Based Elephant Detection Vasileios Dimitrakis Vasileios Dimitrakis

2 Introduction - Motivation (1) Vasileios Dimitrakis

3 Introduction - Motivation (1) Datacenters have enormous demands for bandwidth Vasileios Dimitrakis

4 Introduction - Motivation (1) Datacenters have enormous demands for bandwidth Large fraction of data center traffic is carried in small number of flows Vasileios Dimitrakis

5 Introduction - Motivation (1) Datacenters have enormous demands for bandwidth Large fraction of data center traffic is carried in small number of flows Management of large flows could lead to better utilization of datacenter fabric Vasileios Dimitrakis

6 Introduction - Motivation (2) Current elephant detection methods suffer from limitations Vasileios Dimitrakis

7 Introduction - Motivation (2) Current elephant detection methods suffer from limitations Solution-Mahout: A traffic management method for Elephant Flows Vasileios Dimitrakis

8 Current Approaches Vasileios Dimitrakis

9 Current Approaches Applications identify their flows as elephant Vasileios Dimitrakis

10 Current Approaches Applications identify their flows as elephant Maintain per-flow statistics (Hedera Approach) Vasileios Dimitrakis

11 Current Approaches Applications identify their flows as elephant Maintain per-flow statistics (Hedera Approach) Sampling Method Vasileios Dimitrakis

12 Proposed Solution: Mahout Vasileios Dimitrakis

13 Proposed Solution: Mahout A shim layer on each end host monitors flows Vasileios Dimitrakis

14 Proposed Solution: Mahout A shim layer on each end host monitors flows It detects elephant flows and marks their packets Vasileios Dimitrakis

15 Proposed Solution: Mahout A shim layer on each end host monitors flows It detects elephant flows and marks their packets Switches forward marked packets to controller Vasileios Dimitrakis

16 Proposed Solution: Mahout A shim layer on each end host monitors flows It detects elephant flows and marks their packets Switches forward marked packets to controller Mahout controller computes the best path only for the elephant flows Vasileios Dimitrakis

17 Detection of elephant flows in end host: Mahout approach Advantages of elephant flow detection in end-hosts: Vasileios Dimitrakis

18 Detection of elephant flows in end host: Mahout approach Advantages of elephant flow detection in end-hosts: End host OS has better visibility into the applications behavior Vasileios Dimitrakis

19 Detection of elephant flows in end host: Mahout approach Advantages of elephant flow detection in end-hosts: End host OS has better visibility into the applications behavior Feasible deployment on end-hosts Vasileios Dimitrakis

20 Detection of elephant flows in end host: Mahout approach Advantages of elephant flow detection in end-hosts: End host OS has better visibility into the applications behavior Feasible deployment on end-hosts Very low overhead on commodity servers Vasileios Dimitrakis

21 Mahout Architecture Vasileios Dimitrakis

22 In-band Signaling When an elephant flow is detected, controller is informed! Vasileios Dimitrakis

23 In-band Signaling When an elephant flow is detected, controller is informed! The packets are marked using the Differentiated Services (DS) field Vasileios Dimitrakis

24 Mahout Controller The controller computes the best path for the packet marked as elephant Vasileios Dimitrakis

25 Mahout Controller The controller computes the best path for the packet marked as elephant An example flow table setup at a switch by Mahout controller: Vasileios Dimitrakis

26 Analytical Evaluation Hedera Vasileios Dimitrakis

27 Analytical Evaluation Hedera Table entries need to be maintained for all flows Vasileios Dimitrakis

28 Analytical Evaluation Hedera Table entries need to be maintained for all flows No OpenFlow switch can support this high number of flows Vasileios Dimitrakis

29 Analytical Evaluation Hedera Table entries need to be maintained for all flows No OpenFlow switch can support this high number of flows Sampling Vasileios Dimitrakis

30 Analytical Evaluation Hedera Table entries need to be maintained for all flows No OpenFlow switch can support this high number of flows Sampling Adds low overhead Vasileios Dimitrakis

31 Analytical Evaluation Hedera Table entries need to be maintained for all flows No OpenFlow switch can support this high number of flows Sampling Adds low overhead However, things are getting really bad, when network utilization increases Vasileios Dimitrakis

32 Analytical Evaluation Hedera Table entries need to be maintained for all flows No OpenFlow switch can support this high number of flows Sampling Adds low overhead However, things are getting really bad, when network utilization increases Mahout Vasileios Dimitrakis

33 Analytical Evaluation Hedera Table entries need to be maintained for all flows No OpenFlow switch can support this high number of flows Sampling Adds low overhead However, things are getting really bad, when network utilization increases Mahout Statistics only gathered for elephant flows Vasileios Dimitrakis

34 Analytical Evaluation Hedera Table entries need to be maintained for all flows No OpenFlow switch can support this high number of flows Sampling Adds low overhead However, things are getting really bad, when network utilization increases Mahout Statistics only gathered for elephant flows Significantly lower number of controllers needed compared to Hedera Vasileios Dimitrakis

35 Experimental Results (1) Mahout s detection time of elephant flows is significantly lower than the one of Hedera! Vasileios Dimitrakis

36 Experimental Results (2) Mahout detects elephant flows 3 times sooner than in-network schemes do Vasileios Dimitrakis

37 Experimental Results (3) Vasileios Dimitrakis

38 Strong aspects of Mahout Vasileios Dimitrakis

39 Strong aspects of Mahout Controller handles less flows Vasileios Dimitrakis

40 Strong aspects of Mahout Controller handles less flows Reduces the in-switch resource requirements Vasileios Dimitrakis

41 Strong aspects of Mahout Controller handles less flows Reduces the in-switch resource requirements Significant throughput improvement compared to static load balancing techniques Vasileios Dimitrakis

42 Strong aspects of Mahout Controller handles less flows Reduces the in-switch resource requirements Significant throughput improvement compared to static load balancing techniques Sooner detection of elephant flows Vasileios Dimitrakis

43 Weak aspects of Mahout Vasileios Dimitrakis

44 Weak aspects of Mahout DSCP bits may be needed for other uses in some datacenters Vasileios Dimitrakis

45 Weak aspects of Mahout DSCP bits may be needed for other uses in some datacenters Mahout shim layer needs to be deployed in every virtual machine in virtualized datacenters Vasileios Dimitrakis

46 Weak aspects of Mahout DSCP bits may be needed for other uses in some datacenters Mahout shim layer needs to be deployed in every virtual machine in virtualized datacenters No specific way to propose certain thresholds for the detection of elephant flows Vasileios Dimitrakis

47 Conclusion Mahout is a low overhead yet effective traffic management system Vasileios Dimitrakis

48 Conclusion Mahout is a low overhead yet effective traffic management system Manages elephant flows based on an end-host detection scheme Vasileios Dimitrakis

49 Conclusion Mahout is a low overhead yet effective traffic management system Manages elephant flows based on an end-host detection scheme Experimental results showed the feasibility of its deployment Vasileios Dimitrakis

50 Q & A Thank you very much for your attention! Vasileios Dimitrakis

51 References [1] Mahout: Low-Overhead Datacenter Traffic Management using End-Host-Based Elephant Detection. A. Curtis, W. Kim, P. Yalagandula [2] Hedera: Dynamic Flow Scheduling for Data Center Networks. M. Al-Fares, S. Radhakrishnan Vasileios Dimitrakis

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