Transcript Berkeley NOW

Massive Cluster
Clusters
Gigabit Ethernet
System
Architecture for
Extreme Devices
David Culler
http://www.cs.berkeley.edu/~culler
U.C. Berkeley
DARPA Meeting
9/21/1999
Recap: Convergence at the Extremes
• Arbitrarily Powerful Services on “Small” Devices
– massive computing and storage in the infrastructure
– active adaptation of form and content “along the way”
• Extremes more alike than either is to the middle
– More specialized in function
– Communication centric design
» wide range of networking options
– Federated System of Many Many Systems
– Hands-off operation, mgmt, development
– Scalability, High Reliability, Availability
– Power and space limited
=> simplicity
• Each extends the other
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State-of-the-Art: Very Large Systems
• Scalable Clusters Established
– high-speed user-level networking + single system image
– naming, authentication, resources, remote exec., storage, policy
• Meta-system glue over full OS and Institutional
structure
– Glunix (UCB), Globus(ANL), Legion (UVA), IPG (NASA), Harness,
NetSolve, Snipe (UTK), ...
– uniform, multiprotocol communication & access mechanism
– personal virtual machine spanning potentially diverse resources
» constructed and managed “by hand”
• Key challenges
– Automatic Composition, Management, and Availability
– Scalability to global scale
– Ease of development for global-scale services
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State-of-the-Art: in the small...
• Unix-like support in a small form factor + real
time seasoning
– microkernels dominate
» Commercial: PSION, GeoWorks, WinCE, Inferno, QNX,
VxWorks, javaos, chorusOS,
» academic: Exokernel, OSKit, ucLinux, ELKS,
– + PalmOS, BeOS,
– Components and mobile objects: jini, corba, dcom, ...
=> tracks the 80386
– when it becomes ~ 1990 PC Unix will run on it
– ability to remove components (modularity) + fault boundaries
more important than performance
– legacy applications less dominant
• add-hoc networking for connectivity
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Design Issues for “Small Device OS”
• Current: Managing address spaces,Thread
scheduling, IP stack, Windowing System, Device
drivers, File system, Applications Programming
Interface, Power management
• Challenge: How can operating systems for tiny
devices be made radically simpler, manageable,
and automatically composable?
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N
Emerging Devices
• RF COTS Mote
– Atmel Microprocessor
– RF Monolithics transceiver
» 916MHz, ~20m, 4800 bps
– 1 week fully active, 2 yr @1%
Laser mote
• 650nm laser pointer
• 2 day life full duty
W
E
S
2 Axis Mag.
Sensor
2 Axis
Accelerometer
Light Intensity
Sensor
Humidity Sensor
Pressure Sensor
Temperature
Sensor
CCR mote
• 4 corner cubes
• 40% hemisphere
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Micro Mote - First Attempt
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Structured Communication-Centric
System Architecture
• Scalable Info. Utility Base
–
–
–
–
highly available
persistent state (safe)
databases, agents
service programming environment
Service
Path
• Active Proxies
– connected to the infrastructure
– soft-state, bootstrap protocol
– transcoding
• Ubiquitous Devices
– billions
– net + sensors / actuators
– net + UI
=> flow devices
• Service Paths
– aggregate flows (rivers)
– transcoding operators
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The Large: Info Utility Platform
• Not just storage and processing, but distributed
innovation of scalable, available services
• Base Pgm extends the Ninja service platform
Scalable, Available Service Platform
Discovery
Registry
PDDS (NB)
service exec. env.
ULN Complex node
traditional OS functions as services
- platform built by push services also
xcode & soft-state
via Active Proxies
automated
smart-client
fail-over & LB
• Path connects device to clustered service through
Soft-State APs, graceful failover within service via nonblocking PDDS and RMI*
• Utility requirement =>
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Key Utility Requirements
• Utility Service Spreads itself over multiple Infra.
Service Providers
– persistent state becomes decoupled from service (Oceanic)
» preserve security model
– contractual relationship between service and platform
– SDS, QoS, LB => negotiation, monitoring, adaptation
– effective incentive-compatible economic mechanisms
• Sevices composed from utility serv. of other providers
– negotiation arch. generalizes path formation
– fail-over across competing services, not homogeneous operations
» self-checking, transactional service API
– economic mechanisms permeate services
• Massive information flows
– via huge data stores and via vast sensor nets (Rivers)
– service-wide auto-scheduling of flows
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The Small: radically simple OS for
management and composition
• Communication is fundamental
– treated as part of the hardware, not “the system”
network
SS
device
network
AA
device
UI
• Push path concept clear into the device
– device fundamentally depends on infrastructure
– devices typically have well-connected proxies
• Focus on scheduling discrete chunks of data
movement not general thread scheduling and
unlimited memory management
– there may be a bounded amount of work per chunk to xform
or check data
– easy to get very predictable scheduling
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Precursors to the next generation
• Operating systems that are not called “operating
systems”
• eg: modern disk controller
– event scheduler handling stream of commands from network
link, controlling complex array of sensors and actuators,
performing sophisticated calculations to determine what and
when (scheduling and caching) as well as transforming data
on the fly
– automatic connection, enumeration, configuration
Network link:
- EIDE, SCSI
- FCAL, SSA
- USB, 1394
- ???
Complex array
of
Sensors and
actuators
– but several simplifying assumptions must be removed
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OS as little more than FSM
• Commands are an event stream merged with
sensor/actuator (or UI) events
• Discrete flows to/from network
• General thread must be compiled to sequence of
bounded atomic transactions
– spaghetti part of an application is configuring the flows
– steady-state is straight-forward event processing + signaling
unusual events
• continuous self-checking and telemetry
– rely on the infrastructure for hard mgmt stuff
• push very simple flow apps into devices
• correct-by-construction techniques for cooperating
FSMs as basis for automated configuration and
mgmt
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UCB Testbed
Massive Cluster
Clusters
Gigabit Ethernet
Servers
Wireless
Cell Phones
PDAs
Desktop
PCs
Future Devices
• 1x300 proc + 10x20 proc SAN clusters across depts.
• integrated through multiple gigabit ethernet
• extended out throug 100s desktops, RF laptop,
IRDA PDA, Cell Phones, Pagers, and numerous
motes
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Plan
• Year 1 (Base):
– Large: Deploy Ninja Service Platform on Cluster-of-Clusters
– Small: Prototype over PalmOS + wince + uc-Linux
• Year 2 (Options 1 & 4)
– Automated service composition architecture
– FSM-OS and negotiation/mgmt architecture
– Broad simulation environment
• Year 3
– Deploy widespread services, devices and feeds
– Evaluate against high-speed decision making applications
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