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Agenda
• What Is PlanetLab?
• Planetary-Scale Services– Evolving the Internet
• Why PlanetLab?
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PlanetLab Is…
• Technology: – An open, global network test-bed for inventing
novel planetary-scale services.– A model for introducing innovations into the
Internet through the use of overlay networks.• Organization:
– A collaborative effort involving academic and corporate researchers from around the world
– Hosted by Princeton, Washington, Berkeley, and MIT; sponsored by Intel, HP, and Google
• Socially– Cutting edge research infrastructure made
available to the global community
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PlanetLab Is…
• IA32 servers (836 1000’s) connected to the Internet at 412 sites• Federated with PlanetLab Europe• Mostly standard Linux distribution and dev environment• A few global services
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Other brands and names are the property of their respective owners.Other brands and names are the property of their respective owners.
Academic Partipants
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Other brands and names are the property of their respective owners.Other brands and names are the property of their respective owners.
Industry Participants
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Agenda
• What Is PlanetLab?
• Planetary-Scale Services– Evolving the Internet Architecture
• Why PlanetLab?
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Content Distribution, 1993
• NCSA’s “What’s New” the most viewed page on the web (100K accesses per month).
• All clients access a single copy of the page stored on a single server.
End-to-End design works pretty well for End-to-End design works pretty well for store-and-forward applicationsstore-and-forward applications
End-to-End design works pretty well for End-to-End design works pretty well for store-and-forward applicationsstore-and-forward applications
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Content Distribution, 1998
• IBM web “server” handles a record 100K hits per minute at the Nagano Olympics
• DFS running on SP2’s used to distribute 70K pages to 9 geographically distributed locations
End-to-End design breaks down at scale End-to-End design breaks down at scale (flash crowds, global distribution, …)(flash crowds, global distribution, …)
End-to-End design breaks down at scale End-to-End design breaks down at scale (flash crowds, global distribution, …)(flash crowds, global distribution, …)
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Content Distribution TodayA Planetary-Scale Service
• Edge services provide 1000’s of points of presence throughout the Internet
• Overlay networks are constructed to move the content around efficiently
The transition from “end-to-end” to “overlay” The transition from “end-to-end” to “overlay” enables reliable planetary-scale servicesenables reliable planetary-scale services
The transition from “end-to-end” to “overlay” The transition from “end-to-end” to “overlay” enables reliable planetary-scale servicesenables reliable planetary-scale services
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Planetary-Scale Services
• Pervasive– Runs everywhere, all the time
• Robust– Robust system from flaky components
• Adaptive– Aware of and adapts to changing
environment
• Scalable– Scales to a global workload
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To Build One, You Need…
• Multiple vantage points on the network– Near the edge—low latency to clients– Near the core—good connectivity– Global presence
• A little computation at many locations– Computation beyond a single machine– Computation beyond a single organization
• Management services appropriate to the task– Resource allocation– Provisioning and configuration– Monitoring nodes, services, networks
• But who can afford it?– No single app can justify the infrastructure costs– Network today is like big-iron before timeshare
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Solution: Share the Platform
• Everyone contributes a piece of the platform; everyone can use the whole platform– Build a “time-sharing” network-service platform– Cost shared among all the apps using it
• Model of future public computing utility– Nodes owned by many organizations– Shared cooperatively to provide resilience
• Platform must provide– Isolation to protect services from one another– Market-based resource allocation
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PlanetLab Service Architecture
Node 1Node 1Node 2Node 2
Node 3Node 3
Node 5Node 5Node 4Node 4
Mg
mt. V
MM
gm
t. VM
HardwareHardware
VMMVMM
ServiceVirtual
Machines
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PlanetLab Services are Running
EventEventProcessingProcessing
NetworkNetworkMappingMapping
DistributedDistributedHash TablesHash Tables
ContentContentDistributionDistribution Web CastingWeb Casting
Infrastructure Services & End-user ServicesInfrastructure Services & End-user Services
Node 1Node 1Node 2Node 2
Node 3Node 3
Node 5Node 5Node 4Node 4
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Resource Reservations
• CPU resources can be scarce during certain periods (before paper deadlines)
• The Sirius Resource Calendar Service allows PlanetLab users to schedule an increase a slice’s CPU priority for certain time periods– Only CPU and not work
• Seems to work well:– Rarely 50% subscribed– Services often deal with CPU loading
themselves
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PlanetLab Today…
• 836 IA32 machines at 412 sites– Principally universities, some enterprise – Research networks: I2, CANet/4, RNP, CERNet– Globally distributed– Some co-location centers– Federated with PlanetLab Europe
• Machines virtualized at syscall level– Name space isolation for security– Network, CPU, memory, file system isolation– Interface is a Linux machine with minimal install
• Complete access to the network
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What We Got Right
• Immediate impact– Within 18 months 25% of publications at
top OS & Comm conferences were PlanetLab experiments
– Became a “expectation” for validation of large system results
– And we learned some very interesting things
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What We Got Right (continued)
• Incident response– Early: very conservative
• Don’t get turned off before value is established
– Later: less restrictions• Local administrators defend their researchers
– Education• Researchers: the kind of experiment that
causes alarms• Administrators: touchy IDS implementations
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We Could Have Done Better
• Community contributions to the infrastructure– Infrastructure development remained
centralized, we are paying the price now
• Support for long-running services– Researchers aren’t motivated to keep
services running for multiple years– Decreased the amount of service
composition (can’t trust the dependent services will continue to run)
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We Could Have Done Better (continued)
• Admission control– Good practices make it possible to run
many experiments, but very easy to consume all resources
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Open Challenges
• Community ownership of availability– Need to motivate decentralized
management• Who keeps the nodes running?• What happens when the nodes aren’t
running?
• Resource allocation aligned objectives– Performance, innovation, stability
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Open Challenges (continued)
• Standardization– Standard interfaces platform stability– Open architecture improved
innovation
• Tech Transfer
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Agenda
• What Is PlanetLab?
• Planetary-Scale Services– Evolving the Internet Architecture
• Why PlanetLab?
![Page 25: PlanetLab: A Platform for Planetary-Scale Services Mic Bowman (mic.bowman@intel.com)](https://reader031.vdocuments.mx/reader031/viewer/2022032806/56649f045503460f94c17a9f/html5/thumbnails/25.jpg)
PlanetLab and Industry
• Global communications company– Incubator for future Internet infrastructure– Emerging services become a part of the Internet
• Global computer vendor– Platform for planetary-scale services– Need to understand for our customers
• Software company– Testbed for next generation applications– Cost-effective way to test new ideas
• Fortune 500 company– Next generation opportunities for IT staff– Leverage deployed PlanetLab services for CDN, object
location, network health…
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Summary
• PlanetLab is:– A globally distributed testbed that facilitates experimentation and
deployment of scalable Internet services.
• The testbed has successfully established itself as a platform for cutting edge research.– Active research community using it for a wide variety of
technologies.
– Multiple papers published top academic conferences, e.g. OSDI, SOSP, NSDI, Sigcomm, …
– 300+ active projects
• Come join the fun (www.planet-lab.org)
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BACKUP
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Princeton: CoDeeN
• Content distribution– Partial replication of content
– Redirect requests to optimal location of content
• PlanetLab Deployment– 100 nodes, 150+ GB of data
moved among the sites
– Working to build service redirector
• Key Learnings– First service targeted for end
users (proxy cache)
– Maintaining server health is hard and unpredictable
BBB
B
B
B
B
A
A
A
A
AA
C
CC
C
CCC
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UWashington: Scriptroute
• Distributed Internet debugging and measurement
– Distribute measurement points throughout the network
– Allow user to connect & make a measurement (upload scripts)
• PlanetLab Deployment– Running on about 100 nodes– Basic service used by other
services• Observations
– Experiments look like port scan attacks
– Low BW traffic to lots of addrs breaks some routers
– Scriptroute adjusted spray of packets to avoid the problem
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Cornell: Beehive
• DHT for object location– High performance– Self-organizing– Scalable
• Proactive-replication– Hash buckets replicated– O(1) lookup times for queries
• CoDoNs: DNS replacement– High performance P2P– Adaptive, load balancing– Cache coherent
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Usage Stats
• Slices: 600+
• Users: 2500+
• Bytes-per-day: 4 TB
• IP-flows-per-day: 190M
• Unique IP-addrs-per-day: 1M
(source: Larry Peterson, May 2007)