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Live Migration of an Entire Network (and its Hosts) Eric Keller, Soudeh Ghorbani, Matthew Caesar, Jennifer Rexford HotNets 2012.

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Presentation on theme: "Live Migration of an Entire Network (and its Hosts) Eric Keller, Soudeh Ghorbani, Matthew Caesar, Jennifer Rexford HotNets 2012."— Presentation transcript:

1 Live Migration of an Entire Network (and its Hosts) Eric Keller, Soudeh Ghorbani, Matthew Caesar, Jennifer Rexford HotNets 2012

2 Widely supported to help: Consolidate to save energy Re-locate to improve performance Virtual Machine Migration Hypervisor Apps OS Hypervisor Apps OS Apps OS Apps OS Apps OS Apps OS 2

3 Many VMs working together But Applications Look Like This 3

4 Networks have increasing amounts of state And Rely on the Network Configuration Learned Software-Defined 4

5 Joint (virtual) host and (virtual) network migration Ensemble Migration No re-learning, No re-configuring, No re-calculating Capitalize on redundancy 5

6 Some Use Cases 6

7 Customer driven – for cost, performance, etc. Provider driven – offload when too full 1. Moving between cloud providers 7

8 Reduce energy consumption (turn off servers, reduce cooling) 2. Moving to smaller set of servers 8

9 Migrate ensemble to infrastructure dedicated to testing (special equipment) 3. Troubleshooting 9

10 Automated migration according to some objective and easy manual migration Goal: General Management Tool Monitoring Objective Migration Ensemble Migration Automation manual 10

11 LIve Migration of Ensembles Migration Primitives Migration Orchestration Tenant Control LIME Network Virtualization API to operator/ automation Software-defined network Virtualized servers Tenant Control virtual topology 11 Migration is transparent

12 Why Transparent? 12

13 Separate Out Functionality Tenant Control Network Virtualization Tenant Control virtual topology 13

14 Separate Out Functionality Migration Primitives Migration Orchestration Tenant Control Network Virtualization Tenant Control virtual topology 14

15 Multi-tenancy Migration Primitives Migration Orchestration Tenant Control Network Virtualization Tenant Control virtual topology Infrastructure Operator Tenants 15

16 Can we base it off of VM migration? Iteratively copy state Freeze VM Copy last delta of state Un-freeze VM on new server How to Live Migrate an Ensemble 16

17 Applying to Ensemble Iterative copy 17

18 Applying to Ensemble Freeze and copy 18

19 Applying to Ensemble Resume 19

20 Applying to Ensemble Resume Complex to implement Downtime potentially large 20

21 Applying to Whole Network Iterative copy 21

22 Applying to Whole Network Freeze and copy 22

23 Applying to Whole Network Resume 23

24 Applying to Whole Network Resume Lots of packet loss Lots of “backhaul” traffic 24

25 Applying to Each Switch Iterative copy 25

26 Applying to Each Switch Freeze and copy 26

27 Applying to Each Switch Resume 27

28 Applying to Each Switch Resume Bursts of packet loss Even more “backhaul” traffic Long total time 28

29 Clone the network Migrate the VMs individually (or in groups) A Better Approach 29

30 Clone the Network Copy state 30

31 Clone the Network Cloned Operation 31

32 Clone the Network Migrate VMs 32

33 Clone the Network Migrate VMs 33

34 Minimizes backhaul traffic No packet loss associated with the network (network is always operational) Clone the Network 34

35 Same guarantees as migration-free Preserve application semantics Consistent View of a Switch Migration Primitives Migration Orchestration Network Virtualization Switch_A_0Switch_A_1 Switch_A Application view Physical reality 35

36 Sources of Inconsistency Switch_A_0Switch_A_1 Apps OS Packet 0 Packet 1 R1 R2 Migration-free: packet 0 and packet 1 traverse same physical switch VM (end host) 36

37 1. Local Changes on Switch Switch_A_0Switch_A_1 (e.g. delete rule after idle timeout) Apps OS Packet 0 Packet 1 R1 R2 VM (end host) 37

38 2. Update from Controller Switch_A_0Switch_A_1 Apps OS Packet 0 Packet 1 R_new R1 R2 Install(R_new) (e.g. rule installed at different times) VM (end host) 38

39 3. Events to Controller Switch_A_0Switch_A_1 Apps OS Packet 0 Packet 1 R1 R2 Packet-in(pkt 0) Packet-in(pkt 1) (received at controller first) (e.g. forward and send to controller) VM (end host) 39

40 Consistency in LIME Migration Primitives Migration Orchestration Network Virtualization Switch_A_0Switch_A_1 Switch_A *Restrict use of some features * Use a commit protocol * Emulate HW functions * Combine information 40

41 LIME is a general and efficient migration layer Hope is future SDN is made migration friendly Develop models and prove correctness – end-hosts and network – “Observational equivalence” Develop general migration framework – Control over grouping, order, and approach Conclusions and Future work 41

42 Eric Keller: Soudeh Ghorbani: Thanks 42


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