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Agenda
• What Is PlanetLab?
• Planetary-Scale Services– Evolving the Internet
• Why PlanetLab?
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
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
Other brands and names are the property of their respective owners.Other brands and names are the property of their respective owners.
Academic Partipants
Other brands and names are the property of their respective owners.Other brands and names are the property of their respective owners.
Industry Participants
Agenda
• What Is PlanetLab?
• Planetary-Scale Services– Evolving the Internet Architecture
• Why PlanetLab?
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
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, …)
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
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
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
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
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
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
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
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
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
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
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)
We Could Have Done Better (continued)
• Admission control– Good practices make it possible to run
many experiments, but very easy to consume all resources
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
Open Challenges (continued)
• Standardization– Standard interfaces platform stability– Open architecture improved
innovation
• Tech Transfer
Agenda
• What Is PlanetLab?
• Planetary-Scale Services– Evolving the Internet Architecture
• Why PlanetLab?
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…
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)
BACKUP
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
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
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
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)