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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 2
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Many VMs working together But Applications Look Like This 3
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Networks have increasing amounts of state And Rely on the Network Configuration Learned Software-Defined 4
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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 5
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Some Use Cases 6
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Customer driven – for cost, performance, etc. Provider driven – offload when too full 1. Moving between cloud providers 7
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Reduce energy consumption (turn off servers, reduce cooling) 2. Moving to smaller set of servers 8
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Migrate ensemble to infrastructure dedicated to testing (special equipment) 3. Troubleshooting 9
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Automated migration according to some objective and easy manual migration Goal: General Management Tool Monitoring Objective Migration Ensemble Migration Automation manual 10
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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
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Why Transparent? 12
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Separate Out Functionality Tenant Control Network Virtualization Tenant Control virtual topology 13
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Separate Out Functionality Migration Primitives Migration Orchestration Tenant Control Network Virtualization Tenant Control virtual topology 14
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Multi-tenancy Migration Primitives Migration Orchestration Tenant Control Network Virtualization Tenant Control virtual topology Infrastructure Operator Tenants 15
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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 16
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Applying to Ensemble Iterative copy 17
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Applying to Ensemble Freeze and copy 18
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Applying to Ensemble Resume 19
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Applying to Ensemble Resume Complex to implement Downtime potentially large 20
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Applying to Whole Network Iterative copy 21
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Applying to Whole Network Freeze and copy 22
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Applying to Whole Network Resume 23
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Applying to Whole Network Resume Lots of packet loss Lots of “backhaul” traffic 24
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Applying to Each Switch Iterative copy 25
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Applying to Each Switch Freeze and copy 26
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Applying to Each Switch Resume 27
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Applying to Each Switch Resume Bursts of packet loss Even more “backhaul” traffic Long total time 28
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Clone the network Migrate the VMs individually (or in groups) A Better Approach 29
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Clone the Network Copy state 30
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Clone the Network Cloned Operation 31
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Clone the Network Migrate VMs 32
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Clone the Network Migrate VMs 33
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Minimizes backhaul traffic No packet loss associated with the network (network is always operational) Clone the Network 34
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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_0Switch_A_1 Switch_A Application view Physical reality 35
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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
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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
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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
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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
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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
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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 41
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Eric Keller: eric.keller@colorado.edueric.keller@colorado.edu Soudeh Ghorbani: ghorban2@illinois.edughorban2@illinois.edu Thanks 42
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