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7/25/2019 Understanding Performance Interference of IO Workload in Virtualized Clooud Env
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Understanding Performance
Interference of I/O Workload in
Virtualized Cloud EnvironmentsSummarized by: Michael Riera
9/17/2011
University of Central Florida CDA5532
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Agenda
Purpose
Xen I/O Architecture
Experiment Setup
Experiment Results
Base case Measurement
Interference Analysis
Throughput Interference
Conclusion
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Purpose
The purpose of this paper is to quantify the
interference of multiple VMs on the
throughput of an I/O intensive workload
of 1KB, 4KB, 10KB, 30KB, 50KB, 70KB, 100KB.
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Xen Architecture /Description
Is a popular open-source x86 virtual machine
monitor (VMM) based on virtualization
Technologies
- Hypercalls straight to the host operating system
Lower overhead
PCI Pass through
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Xen Architecture /Description
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Example
NIC Receive Packet
Event Channel (Xen VMM) Decides whether the driver has access to HW
Physical Interface Interface to Network card
Bridge Removes from NIC
Demux the network packet and delivers it to the appropriate VM
Backend Raise a hypercall to the VMM requesting space on the guest
I/O Channel Netback and netfront exchange the page descriptor by page remapping over mechanism over
I/O descriptor ring
Frontend Receives a packet as if it came from a NIC card
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Experiment Setup
IBM ThinkCentre A52 Workstation
3.2Ghz Intel Pentium 4
16KB L1 Cache
2MB L2 Cache2GB 400Mhz DDR memory
Seagate 250GB
Intel NIC E100 PRO/100 Network
Client machinesConnected 1Gb/s lines
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Experiment Setup
I/O intensive workload
Running two isolated guest (VM1, VM2)
VMM Sharing physical hardware
Each VM has equal resources
CPU Scheduling: SMP Credit scheduler
VM1 has an Apache HTTP server
VM2 provides the web services Cache buffer data (no disk reading are involved)
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Experiment Setup
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Experiment Results
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Experiment Results
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Experiment Results
CPU Utilization Measured the average CPU utilization of each VM, including CPU usage of
Dom0, VM1 and VM2
VMM events per second VMM adopts asynchronous hypercall mechanism to notify the VMs of system
events.
VM switches Metric for number of times VMM need to context switch
I/O count Pages Exchange
I/O counts per execution Page exchange per execution
VM State Execution state(using CPU), runnable state(waiting for CPU), block state
(waiting for IO)
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Experiment Results
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Experiment Results
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Conclusion
Competing network intensive loads
High Cache misses
High Wait times
ess compe ng resources , p ma
Interference highly sensitive to multiple VMs
Credit Scheduler to blame for large wait in the
larger files compared to the smaller ones