Network-aware migration control and scheduling of differentiated virtual machine workloads Alexander Stage and Thomas Setzer Technische Universit¨at M¨unchen (TUM) Chair for Internet-based Information Systems ICSE Workshop on Software Engineering Challenges in Cloud Computing, Vancouver, Canada, May 2009 1
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Network-aware migration control and scheduling of differentiated virtual machine workloads
Network-aware migration control and scheduling of differentiated virtual machine workloads. Alexander Stage and Thomas Setzer Technische Universit¨at M¨unchen (TUM) Chair for Internet-based Information Systems - PowerPoint PPT Presentation
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Network-aware migration control and scheduling of differentiated virtual
machine workloads
Alexander Stage and Thomas SetzerTechnische Universit¨at M¨unchen (TUM)
Chair for Internet-based Information Systems ICSE Workshop on Software Engineering
Challenges in Cloud Computing, Vancouver, Canada, May 2009
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Introduction Server virtualization based workload
consolidation is increasingly used. Raise server utilization levels Ensure cost-efficient data center operations.
Unforeseen spikes or shifts in workloads require dynamic workload management to avoid server overload.
Continuously align placements of virtual machines (VMs) ----VM Live Migration
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How does Live Migration Work Phase 1: Setting
Create a TCP connection between source and destination Copy VM’s profile to destination Create a VM on destination
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.BIN.VSV.XML.VHD
Source Node(Host A) Destination Node
(Host B)Network Storage
Configuration Data
How does Live Migration Work Phase 2: Memory migrate
Transfer Memory to destination Trace the difference when transferring Memory Pause the VM on Source Node when starting last transfer
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.BIN.VSV.XML.VHD
Source Node Destination Node
Network Storage
Memory Content
How does Live Migration Work Phase 3: Status migrate
Migrate register in VM in Source Node Starting the VM in Destination Node Clean old VM in Source Node
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.BIN.VSV.XML.VHD
Source Node Destination NodeNetwork Storage
Running State
Motivation VM live migration realizes:
Dynamic resource provisioning Load balancing
But it imposes significant overheads that need to be considered and controlled.
CPU overhead [17] Network overhead and network topology
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[17] T. Wood, P. Shenoy, A. Venkataramani, and M. Yousif. Black-box and gray-box strategies for virtual machine migration. In 4th USENIX Symp. on Networked Systems Design and Impl., pages 229 – 242, 2007.
Network overhead of Live Migration(1/2)
In live migration phase 2, it use iterative, bandwidth adapting pre-copy memory page transfer algorithms.
Objective: Minimize VM downtime Keep total migration time low Lower the aggregated bandwidth consumption for
a migration. Non-neglectable network overhead[5]
500 Mb/s for 10 seconds for a trivial web server VM
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[5]C. Clark, K. Fraser, S. H, J. G. Hansen, E. Jul, C. Limpach, I. Pratt, and A. Warfield. Live migration of virtual machines. In Proc. of 2nd ACM/USENIX Symp. on Network Systems Design and Implementation, pages 273–286, 2005.
Network overhead of Live Migration(2/2)
Example: Requiring the execution of 20 VM migrations
within 5 minutes. Assume each migration consumes 1 Gb/s for
20 seconds. Sequentially scheduling them over a single 10
(1) Gb/s link saturates the link completely for 40 (400) seconds
Outcome: VMs expose sudden network load increases that would possibly lead to resource shortages.
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Migration scheduling architecture In order to deal with the network overhead of live
migration, we propose migration scheduling architecture.
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Data Center
Collect performance parameters
Classify Workload Type, Predict host
utilization
Determines expected resource bottlenecks
and low utilization levels
Handle unexpected situation such as sudden surges in resource demand
Decide operational live migration plan to avoid migration-
related SLA violations
Workload classifier(1/2) We identify the following main workload
attributes for our classification: Predictability:
Predictable means workload behavior can be reliably forecasted for a given period of time.
Forecasting errors are tightly bounded. Trend:
Refers to the degree of upward or downward leading demand trends.
Periodicity: Indicates the length (time scale) and the power of
page transfer algorithms :1. All main memory pages are transferred2. Only transferred memory pages that have been
written to (dirtied) during the previous iteration. Bandwidth usage is adaptively increased in each iteration
3. If the set of dirtied memory pages is sufficiently small or the upper bandwidth limit is reached then go to step 4.
Otherwise go to 2.4. The last pre-copy iteration is started.
Service downtime
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iq = the duration of the q-th iteration of VM ibi =constant bandwidth adaptive rate of VM imi = memory size of VM iri = the constant memory dirtying rate of VM i
Only 2 Migration can be launched simultaneously
(D is Rejected)
Migration Scheduler(2/3) Currently, the bandwidth usage
cannot be control during migration. We can only control maximum