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FairCloud: Sharing the Network in Cloud Computing Lucian Popa - PowerPoint PPT Presentation

FairCloud: Sharing the Network in Cloud Computing Lucian Popa Gautam Kumar Mosharaf Chowdhury (HP Labs) (UC Berkeley) (UC Berkeley) Arvind Krishnamurthy Sylvia Ratnasamy Ion Stoica (Univ Washington) (UC Berkeley) (UC Berkeley)


  1. FairCloud: Sharing the Network in Cloud Computing Lucian Popa Gautam Kumar Mosharaf Chowdhury (HP Labs) (UC Berkeley) (UC Berkeley) Arvind Krishnamurthy Sylvia Ratnasamy Ion Stoica (Univ Washington) (UC Berkeley) (UC Berkeley)

  2. Motivation Network?

  3. Context Networks are more difficult to share than other resources X

  4. Context • Several proposals that share network differently, e.g.: – proportional to # source VMs (Seawall [NSDI11]) – statically reserve bandwidth (Oktopus [Sigcomm12]) – … • Provide specific types of sharing policies • Characterize solution space and relate policies to each other?

  5. This Talk 1. Framework for understanding network sharing in cloud computing – Goals, tradeoffs, properties 2. Solutions for sharing the network – Existing policies in this framework – New policies representing different points in the design space

  6. Goals 1. Minimum Bandwidth Guarantees – Provides predictable performance – Example: file transfer finishes within time limit B min A 1 A 2 Time max = Size / B min

  7. Goals 1. Minimum Bandwidth Guarantees 2. High Utilization – Do not leave useful resources unutilized – Requires both work-conservation and proper incentives A B B B Both tenants active Non work-conserving Work-conserving

  8. Goals 1. Minimum Bandwidth Guarantees 2. High Utilization 3. Network Proportionality – As with other services, network should be shared proportional to payment – Currently, tenants pay a flat rate per VM  network share should be proportional to #VMs (assuming identical VMs)

  9. Goals 1. Minimum Bandwidth Guarantees 2. High Utilization 3. Network Proportionality – Example: A has 2 VMs, B has 3 VMs Bw A Bw B Bw A 2 A 1 B 3 = Bw B 3 B 1 When exact sharing is not A 2 possible use max-min B 2

  10. Goals 1. Minimum Bandwidth Guarantees 2. High Utilization 3. Network Proportionality Not all goals are achievable simultaneously!

  11. Tradeoffs Not all goals are achievable simultaneously!

  12. Tradeoffs

  13. Tradeoffs Minimum Guarantee A B Access Link L Bw A = 1/2 C Capacity C Bw B = 1/2 C Bw A Bw B Network Proportionality Bw A = 2/13 C Bw B = 11/13 C Bw A ≈ C/N T  0 #VMs in the network 10 VMs

  14. Tradeoffs

  15. Tradeoffs A 1 A 2 L A 4 A 3 B 2 B 1 B 3 B 4

  16. Tradeoffs Network Proportionality Bw A = 1/2 C Bw B = 1/2 C A 1 A 2 L A 4 A 3 B 2 B 1 B 3 B 4

  17. Tradeoffs Uncongested path P A 1 A 2 L A 4 A 3 B 2 B 1 B 3 B 4

  18. Tradeoffs Network Proportionality Uncongested path L P L Bw A +Bw A = Bw B P L L Bw A < Bw B A 1 A 2 L A 4 A 3 Tenants can be disincentivized to use free resources B 2 B 1 If A values A 1  A 2 or A 3  A 4 more than A 1  A 3 B 3 B 4

  19. Tradeoffs Uncongested path P Network proportionality A 1 A 2 applied only for flows traversing congested links L A 4 A 3 shared by multiple tenants B 2 B 1 B 3 B 4

  20. Tradeoffs Uncongested path P A 1 A 2 Congestion Proportionality L L L A 4 A 3 Bw A = Bw B B 2 B 1 B 3 B 4

  21. Tradeoffs Still conflicts with high utilization

  22. Tradeoffs C 1 = C 2 = C L 1 A 1 A 2 B 2 B 1 L 2 A 4 A 3 B 3 B 4

  23. Tradeoffs C 1 = C 2 = C Congestion Proportionality L 1 L1 L1 A 1 A 2 Bw B Bw A = L2 L2 B 2 B 1 Bw A = Bw B L 2 A 4 A 3 B 3 B 4

  24. Tradeoffs C 1 = C 2 = C L 1 A 1 A 2 B 2 B 1 L 2 A 4 A 3 Demand drops to B 3 B 4 ε

  25. Tradeoffs Tenants incentivized to not fully utilize C 1 = C 2 = C resources L 1 ε A 1 A 2 B 2 C - ε B 1 L 2 C - ε A 4 A 3 B 3 B 4 ε

  26. Tradeoffs Tenants incentivized to not fully utilize C 1 = C 2 = C resources L 1 ε A 1 A 2 B 2 C - ε B 1 L 2 C - 2 ε A 4 A 3 Uncongested B 3 B 4 ε

  27. Tradeoffs Tenants incentivized to not fully utilize C 1 = C 2 = C resources L 1 C/2 A 1 A 2 B 2 B 1 C/2 L 2 C - 2 ε A 4 A 3 Uncongested B 3 B 4 ε

  28. Tradeoffs L 1 A 1 A 2 Proportionality applied to B 2 B 1 each link independently L 2 A 4 A 3 B 3 B 4

  29. Tradeoffs L 1 A 1 A 2 Full incentives for high utilization B 2 B 1 L 2 A 4 A 3 B 3 B 4

  30. Goals and Tradeoffs

  31. Guiding Properties Break down goals into lower-level necessary properties

  32. Properties

  33. Work Conservation • Bottleneck links are fully utilized • Static reservations do not have this property

  34. Properties

  35. Utilization Incentives • Tenants are not incentivized to lie about demand to leave links underutilized • Network and congestion proportionality do not have this property • Allocating links independently provides this property

  36. Properties

  37. Communication-pattern Independence • Allocation does not depend on communication pattern • Per flow allocation does not have this property – (per flow = give equal shares to each flow)  Same Bw 

  38. Properties

  39. Symmetry • Swapping demand directions preserves allocation • Per source allocation lacks this property – (per source = give equal shares to each source)  Same Bw   Same Bw 

  40. Goals, Tradeoffs, Properties

  41. Outline 1. Framework for understanding network sharing in cloud computing – Goals, tradeoffs, properties 2. Solutions for sharing the network – Existing policies in this framework – New policies representing different points in the design space

  42. Per Flow (e.g. today)

  43. Per Source (e.g., Seawall *NSDI’11+)

  44. Static Reservation (e.g., Oktopus *Sigcomm’11+)

  45. New Allocation Policies 3 new allocation policies that take different stands on tradeoffs

  46. Proportional Sharing at Link-level (PS-L)

  47. Proportional Sharing at Link-level (PS-L) • Per tenant WFQ where weight = # tenant’s VMs on link WQ A = #VMs A on L A Bw A = #VMs A on L Bw B #VMs B on L B Can easily be extended to use heterogeneous VMs (by using VM weights)

  48. Proportional Sharing at Network-level (PS-N)

  49. Proportional Sharing at Network-level (PS-N) • Congestion proportionality in severely restricted context • Per source-destination WFQ, total tenant weight = # VMs

  50. Proportional Sharing at Network-level (PS-N) • Congestion proportionality in severely restricted context • Per source-destination WFQ, total tenant weight = # VMs A 1 WQ A1  A2 = 1/N A1 + 1/N A2 A 2 N A2 N A1 Total WQ A = #VMs A

  51. Proportional Sharing at Network-level (PS-N) • Congestion proportionality in severely restricted context • Per source-destination WFQ, total tenant weight = # VMs WQ A = #VMs A WQ B #VMs B

  52. Proportional Sharing on Proximate Links (PS-P)

  53. Proportional Sharing on Proximate Links (PS-P) • Assumes a tree-based topology: traditional, fat-tree, VL2 (currently working on removing this assumption)

  54. Proportional Sharing on Proximate Links (PS-P) • Assumes a tree-based topology: traditional, fat-tree, VL2 (currently working on removing this assumption) • Min guarantees – Hose model – Admission control Bw A1 Bw An Bw A2 A n A 1 A 2 …

  55. Proportional Sharing on Proximate Links (PS-P) • Assumes a tree-based topology: traditional, fat-tree, VL2 (currently working on removing this assumption) • Min guarantees – Hose model – Admission control • High Utilization – Per source fair sharing towards tree root

  56. Proportional Sharing on Proximate Links (PS-P) • Assumes a tree-based topology: traditional, fat-tree, VL2 (currently working on removing this assumption) • Min guarantees – Hose model – Admission control • High Utilization – Per source fair sharing towards tree root – Per destination fair sharing from tree root

  57. Deploying PS-L, PS-N and PS-P • Full Switch Support – All allocations can use hardware queues (per tenant, per VM or per source-destination) • Partial Switch Support – PS-N and PS- P can be deployed using CSFQ *Sigcomm’98+ • No Switch Support – PS-N can be deployed using only hypervisors – PS-P could be deployed using only hypervisors, we are currently working on it

  58. Evaluation • Small Testbed + Click Modular Router – 15 servers, 1Gbps links • Simulation + Real Traces – 3200 nodes, flow level simulator, Facebook MapReduce traces

  59. Many to one One link, testbed PS-P offers guarantees A B Bw A Bw B Bw A N N

  60. MapReduce One link, testbed 5 M PS-L offers link proportionality Bw B (Mbps) Bw A Bw B M 5 R M+R = 10

  61. MapReduce Network, simulation, Facebook trace

  62. MapReduce Network, simulation, Facebook trace PS-N is close to network proportionality

  63. MapReduce Network, simulation, Facebook trace PS-N and PS-P reduce shuffle time of small jobs by 10-15X

  64. Conclusion • Sharing cloud networks is not trivial • First step towards a framework to analyze network sharing in cloud computing – Key goals (min guarantees, high utilization and proportionality), tradeoffs and properties • New allocation policies, superset properties from past work – PS-L: link proportionality + high utilization – PS-N: restricted network proportional – PS-P: min guarantees + high utilization

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