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VIRTUAL MACHINE MIGRATION
K M Sabidur Rahman
Jan 29, 2015
Friday Group Meeting, Netlab
UC Davis
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Agenda
• Who is interested?
• How VM migration works?
• Related research• Related research
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What is VM Migration?
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/LAN
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Why VM Migration?
Online migration[2]:
• Vacating a VM Host system
• Targeting a particular VM Host
• Balancing Host workloads
• Optimizing physical resource utilization
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Why VM Migration?
Offline migration[2]:
• Less resources (like memory and CPUs) used on the sourceand target VM Hosts
• Different processor types preventing online migration• Different processor types preventing online migration
• Source VM may not support Online VM Migration
• VM may just have stopped, the configuration informationneeds to be moved offline
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Amazon-AWS
• VM Migration from one EC2 to another
• VM migration from EC2 to Virtual Private Cloud(VPC)
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VMWare-vMotion
• Moving VM from one physical server to another
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RackSpace-Migration services
• Migration from cloud service provider to in-house server
• From one cloud service provider to other cloud service provider
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Citrix-XenServer
• Supports live migration
• VM on shared storage
• VM not on shared storage (XenMotion)
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Cisco
• Teamed up with VMWare to enable Virtual Server mobility
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Intel and AMD
• VM migration between heterogeneous processors
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Microsoft-Hyper-V
• Hyper-V is Microsoft’s solution for virtualization in Windows Server
• Migrating VM running on “Virtual Server 2005 R2 SP1” to Hyper-V
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OpenStack and Red Hat
• OpenStack supports live and non-live migrations for cloudadministrators
• Red Hat can live migrate VMs for maintenance, load balancingor power saving
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CloudNet: Dynamic Pooling of Cloud Resources by Live WAN Migration of Virtual Machines
• Timothy Wood and Prashant Shenoy, University ofMassachusetts Amherst
• K.K. Ramakrishnan and Jacobus Van der Merwe, AT&T Labs -Research
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VM Migration over the WAN
• Move from one server to multiple other servers across theinternet
• Cloud computing platform linked by a VPN based networkinfrastructure
• Minimize the cost of transferring storage and virtual machine• Minimize the cost of transferring storage and virtual machinememory
• Enabling migrations over low bandwidth and high latencyInternet links
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Things to consider
•Seamless secure cloud connections
•Resource pool that spans data centers
•Efficient WAN Migration
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Things to consider
•Seamless secure cloud connections
•Resource pool that spans data centers
•Efficient WAN Migration
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Things to consider
•Seamless secure cloud connections
•Resource pool that spans data centers
•Efficient WAN Migration
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Steps in Migration
Step 1: Establish layer-2 connectivity between data centers, if needed.
Step 2: If storage is not shared, transfer Step 2: If storage is not shared, transfer the application’s disk state.
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Steps in Migration
Step 3: Transfer the memory state ofthe application to a server in DataCenter B, as it continues runningwithout interruption.
Step 4: Once the disk and memorystate have been transferred, brieflypause the application for the finaltransition of memory and processorstate to Data Center B.
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Disk State Migration
• Initial copy is made asynchronously
• Synchronous replication, once the remote disk is stable• Synchronous replication, once the remote disk is stable
• Disk updates continuously propagated to the remote disk
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Transferring Memory State
• “Pre-copy” mechanism to iteratively copy the memory contents
• Finally, VM is paused to copy the final memory state
• Time required to transfer a VM’s memory depends on its RAMallocation, working set size and write rate, and availablebandwidthbandwidth
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Traditional approach to Memory transfer
The default Xen migration algorithm will iterate until either
• very small number of pages remain to be sent
• it has already sent more than 3 times the VM’s total memory• it has already sent more than 3 times the VM’s total memory
• limit of 30 iterations is reached
At that point, the VM is paused, and all remaining pages are sent
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Smart Stop and Copy
• Large number of iterations only extends the total migration time and
increases the total data transferred
• The migration algorithm could intelligently pick when to stop iterating
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Smart Stop and Copy
• A heuristic that tracks the number of pages remaining to be sent
• Looks for local minima in the current history window
• Greedy approach works best for window size 5
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Using page Deltas
• After the first iteration, most of the pages are transferred
• Why don’t we send only the changes that happened in the pages• Why don’t we send only the changes that happened in the pages
• Reduces bandwidth consumed during migration
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Results and improvement
Default Xen code vs CloudNet’s optimizations
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Summary of the paper
• CloudNet Connects resources at multiple data center andenterprise sites
• Handles persistent storage, network connections, and memorystate transfer with minimal downtimestate transfer with minimal downtime
• Minimizes the total migration time, application downtime, and thevolume of data transferred
• Evaluates how different application types(web/client-server/development) impact migration performance
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Cost-efficient live VM migration based on varying electricity cost in optical cloud networks
Abhishek Gupta, Uttam Mandal, Pulak Chowdhury, Massimo Tornatoreand Biswanath Mukherjee
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The idea
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The idea
Migration of VMs to Data Centers with cheaper electricity prices
Considering multiple parameters:
• bandwidth for migration
• cost of migration
• duration of migration
• number of servers and racks to be switched on/off
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Problem : High level view
• Minimizing the operating cost of VMs
• Live VM migration• Live VM migration
• Use of mixed-integer linear program (MILP) formulation
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WAN Migration
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Power Model
Power consumptions to consider: •Source DC power consumption•Destination DC power consumption•Data Migration power consumption
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•Data Migration power consumption
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Power Model : On rack and Server
where
Base power in idle state
Additional power ∞ Load
where
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Power Model : Migration
Migrating a VM from a source DC to a destination DC consume power,in the backbone network
Migration power consumption =
the total number of bits transferred in a VM migration *
the power consumed by a core router in transmitting one bit *
the cost of electricity at the core router.
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Formal Optimization-problem Statement
Given optical backbone network topology, a set
of DC nodes, initial locations of each VM, hourly prices of
electricity at each node, link capacities, maximum number of
VMs a DC can host, and a multi-hour period, our objective
is to minimize the operating cost of the VMs over this period
by deciding whether (including when and where) or not to
migrate the VMs.
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Simulation
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VM distribution
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Operational cost vs number of VMs
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24 hour simulation
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Dynamic scenario for the problem
• Service requests coming in Dynamically
• Requests are queued and then served
• Request life can be short or long
• Power modeling can consider more dynamic inputs
• Heterogeneous types and performance of VMs
• Selection of rack to place the VM
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Reference
• [1] www.greenstarnetwork.com
• [2] https://sort.symantec.com/public/documents/sfha/6.0/hp-ux/productguides/html/sfha_virtualization/ch03s02.htm
• [3] T.Wood, P. Shenoy, K.K. Ramakrishnan and J. V. der Merwe, ”CloudNet: Dynamic Pooling of Cloud Resources by Live WAN ”CloudNet: Dynamic Pooling of Cloud Resources by Live WAN Migration of Virtual Machines”.
• [4] A. Gupta, U. Mandal, P. Chowdhury, M. Tornatore and B. Mukherjee
, “Cost-efficient live VM migration based on varying electricity cost in optical cloud networks”.
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