ppt - MMLab

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Large-scale Virtualization in the Emulab
Network Testbed
Mike Hibler, Robert Ricci, Leigh Stoller Jonathon Duerig
Shashi Guruprasad, Tim Stack, Kirk Webb, Jay Lepreau
Proc. Of the 2008 USENIX Annual Technical Conference
Hoon-gyu Choi
hgchoi@mmlab.snu.ac.kr
2008.10.27
Contents
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Introduction
Motivation
Key techniques
Results
Conclusion
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Introduction
• Testbed is more realistic than simulation
– Experimenters can use real OS, other software, and obtain
actual performance measures
• Emulab: Network Testbed
– Provide time- and space-shared public facility
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Motivation
• Emulab is not scale
– Too small
– Inefficient
• Original Emulab maps virtual network nodes and links
one-to-one onto dedicated PCs and switched Ethernet link
• Solution
– Multiplex logical nodes and networks onto the physical
infrastructure
– Use Virtualization to perform network experiments using
fewer physical resources
– Should be transparent to applications and should preserves
experiment fidelity
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Three Goals
• Application transparency
– Real application on virtual machines
– Keep most semantics of unshared machines
• Application fidelity
– Physical results ≈ Virtual results
– Avoid virtual node interference
• System capacity
– Low overhead
– Don’t prolong experiments
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Key techniques
• Virtualization technology
– Host and network
• Resource mapping
• Feedback-directed emulation
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Virtualization
• Extending FreeBSD jail
– Namespace isolation
– Virtual disks
– Network virtualization
• Ability to bind to multiple interfaces
• New virtual network device (veth)
• Separate routing tables
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Virtualization
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Mapping
• Map the virtual topology to a physical topology
• Good mapping
– Pack using resources efficiently
• Packs virtual hosts, routers, and links on to a minimum
number of physical nodes without overloading the physical
nodes
– Do it quickly
• Use assign
– A solver for the Network Testbed Mapping Problem
– Pack both nodes and link
– Use Resource-based Packing
• Avoid scarce resources
• Works well for heterogenious virtual and physical nodes
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Mapping quickly
• Apply a heuristic pre-pass to the virtual graph before
running assign
– Exploit the structure of the input topology
– Two coarsening algorithms
• Combine all leaf nodes from the same LAN
• Graph partionining
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Mapping quickly
200
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Mapping quality
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Feedback
• Do I know how tightly I can pack my virtual nodes?
– No, But we have a closed, repeatable world
• Process
1. Pick a packing
2. Run experiment
3. Monitor for artifacts
• CPU near 100%, significant paging activity, disk utilization
4. Re-pack & Repeat
• Measure resource use
• Feed into resource-based packing
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Results
• Application fidelity
• Adaptation
• Application transparency
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Application Fidelity
• Setup
– All results gathered on Emulab’s low-end “pc850” machines
• 850 MHz PCs with 512MB RAM and four 100Mb Ethernet
interfaces
– Uses Pathrate bandwidth measurement tool
– Running p2p file sharing application, Kindex
• Total 60 clients
• Each client
– Uploads a single file’s index, and random searches for other
files
– generates 20-40 request per minute
– Network topology consists of six 10Mbps campus LANs
• Each LAN is connected to a router via a 3Mbps
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Application Fidelity
• Application Fidelity
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Adaptation Results
• Setup
– Java-based web server on one host with 69 clients
• Each clients continually download a 64KB file
• Three different types
– 9 clients were evenly spread across 3 links on a single router
using 2MB LANs (to emulate cable modems)
– 40 clients were directly connected to a single router using
2MB multiplexed link (to emulate DSL modems)
– 20 clients were directly connected to a single router using
56Kb multiplexed link (to emulate phone modems)
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Adaptation results
• Feedback case study
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Conclusion
• Virtualization increase Emulab’s capacity
– Transparently
– Preserves fidelity
• Requires solving several challenging problems
• But, can be useful
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