Live Migration of an Entire Network (and its Hosts)
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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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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
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Many VMs working together
But Applications Look Like This
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Networks have increasing amounts of state
And Rely on the Network
Configuration Learned Software-Defined
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Joint (virtual) host and (virtual) network migration
Ensemble Migration
No re-learning,No re-configuring,No re-calculating
Capitalize on redundancy
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Some Use Cases
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• Customer driven – for cost, performance, etc.• Provider driven – offload when too full
1. Moving between cloud providers
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• Reduce energy consumption(turn off servers, reduce cooling)
2. Moving to smaller set of servers
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• Migrate ensemble to infrastructure dedicated to testing (special equipment)
3. Troubleshooting
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Automated migration according to some objectiveand easy manual migration
Goal: General Management Tool
Monitoring
Objective
Migration
Ensemble Migration
Automation
manual
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LIve Migration of Ensembles
Migration Primitives
Migration Orchestration
Tenant Control
LIMENetwork Virtualization
API to operator/ automation
Software-defined networkVirtualized servers
Tenant Control
virtual topology Migration is transparent
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Why Transparent?
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Separate Out FunctionalityTenant Control
Network Virtualization
Tenant Control
virtual topology
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Separate Out Functionality
Migration Primitives
Migration Orchestration
Tenant Control
Network Virtualization
Tenant Control
virtual topology
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Multi-tenancy
Migration Primitives
Migration Orchestration
Tenant Control
Network Virtualization
Tenant Control
virtual topology
InfrastructureOperator
Tenants
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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
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Applying to Ensemble
Iterative copy
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Applying to Ensemble
Freeze and copy
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Applying to Ensemble
Resume
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Applying to Ensemble
Resume
Complex to implementDowntime potentially large
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Applying to Whole Network
Iterative copy
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Applying to Whole Network
Freeze and copy
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Applying to Whole Network
Resume
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Applying to Whole Network
Resume
Lots of packet lossLots of “backhaul” traffic
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Applying to Each Switch
Iterative copy
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Applying to Each Switch
Freeze and copy
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Applying to Each Switch
Resume
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Applying to Each Switch
Resume
Bursts of packet lossEven more “backhaul” traffic
Long total time
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• Clone the network• Migrate the VMs individually (or in groups)
A Better Approach
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Clone the Network
Copystate
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Clone the Network
Cloned Operation
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Clone the Network
MigrateVMs
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Clone the Network
MigrateVMs
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• Minimizes backhaul traffic• No packet loss associated with the network
(network is always operational)
Clone the Network
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• Same guarantees as migration-free
• Preserve application semantics
Consistent View of a Switch
Migration Primitives
Migration Orchestration
Network Virtualization
Switch_A_0 Switch_A_1
Switch_A
Application view
Physical reality
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Sources of Inconsistency
Switch_A_0 Switch_A_1
Apps
OS
Packet 0 Packet 1
R1R2
R1R2
Migration-free: packet 0 and packet 1 traverse same physical switch
VM(end host)
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1. Local Changes on Switch
Switch_A_0 Switch_A_1
(e.g. delete rule after idle timeout)
Apps
OS
Packet 0 Packet 1
R1R2
R1R2
VM(end host)
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2. Update from Controller
Switch_A_0 Switch_A_1
Apps
OS
Packet 0 Packet 1
R_newR1R2
R1R2
Install(R_new)
(e.g. rule installed at different times)
VM(end host)
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3. Events to Controller
Switch_A_0 Switch_A_1
Apps
OS
Packet 0Packet 1
R1R2
R1R2
Packet-in(pkt 0)
Packet-in(pkt 1)(received at controller first)
(e.g. forward and send to controller)
VM(end host)
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Consistency in LIME
Migration Primitives
Migration Orchestration
Network Virtualization
Switch_A_0 Switch_A_1
Switch_A
*Restrict use of some features* Use a commit protocol
* Emulate HW functions* Combine information
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• 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