Griffin Update: Toward an Agile, Predictive Infrastructure

Anthony D. Joseph

UC Berkeleyhttp://www.cs.berkeley.edu/~adj/

Sahara Retreat, January 2004

DETER

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Outline

Griffin– Motivation– Goals– Components

Tapas Update Tapestry Update REAP/MINO Update Beyond Griffin: DETER

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Near-Continuous, Highly-Variable Internet Connectivity

Connectivity everywhere: campus, in-building, satellite…– Projects: Sahara (01-04), Iceberg (98-01), Rover (95-97)

Most applications support limited variability (1% to 2x)– Design environment for legacy apps is static desktop LAN– Strong abstraction boundaries (APIs) hide the # of RPCs

But, today’s apps see a wider range of variability– 35 orders of magnitude of bandwidth from 10's Kb/s 1 Gb/s– 46 orders of magnitude of latency from 1 sec 1,000's ms– 59 orders of magnitude of loss rates from 10-3 10-12 BER– Neither best-effort or unbounded retransmission may be ideal– Also, overloaded servers / limited resources on mobile devices

Result: Poor/variable performance from legacy apps

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Griffin Goals

Users always see excellent ( local, lightly loaded) application behavior and performance

– Independent of the current infrastructure conditions– Move away from “reactive to change” model– Agility: key metric is time to react and adapt

Help legacy applications handle changing conditions– Analyze, classify, and predict behavior– Pre-stage dynamic/static code/data (activate on demand)

Architecture for developing new applications– Input/control mechanisms for new applications– Application developer tools

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Griffin: An Adaptive, Predictive Approach

Continuous, cross-layer, multi-timescale introspection– Collect & cluster link, network, and application protocol events– Broader-scale: Correlate AND communicate short-/long-term events and

effects at multiple levels (breaks abstractions)– SOLVED: Building accurate models of correlated events

Convey app reqs/network info to/from lower-levels– Break abstraction boundaries in a controlled way– OPEN: Extensible interfaces to avoid existing least common denominator

problems Overlay more powerful network model on top of IP

– Avoid standardization delays/inertia– Enables dynamic service placement– PARTIAL: Efficient interoperation with IP routing policies

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Some Enabling Infrastructure Components

Tapas network characteristics toolkit– Measuring/modeling/emulating/predicting delay, loss, …– Provides micro-scale network weather information– Mechanism for monitoring/predicting available QoS

REAP protocol modifying / application building toolkit– Introspective mobile code/data support for legacy / new apps– Provides dynamic placement of data and service components– MINO E-mail application, COMPASS service instance locator

Tapestry, Brocade, and Mobile Tapestry– Overlay routing layer providing efficient application-level object

location and routing– Mobility support, fault-tolerance, varying delivery semantics

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Outline

Griffin– Motivation– Goals– Components

Tapas Update Tapestry Update REAP/MINO Update Beyond Griffin: DETER

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Tapas Update

Accurate modeling and emulation for protocol design– Models/artificial traces that are statistically indistinguishable

from real network traces: delay, error, congestion– Study interactions between protocols at different levels

Project completed (1998-2003)– Multitracer trace analysis tool– Two highly-accurate network models (MTA, M3)– Domain analysis tool– Highly-accurate Tapas-based link simulator

PhD dissertation– Almudena Konrad, “TAPAS: A Research Paradigm for the

Modeling, Prediction, and Analysis of Non-stationary Network Behavior,” (Ph.D., December 2003)

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Tapestry Update

Distributed Object Location and Routing (DOLR) overlay network

Improved static resilience (talk tomorrow)– Pre-computed backup paths enable near- instantaneous fail-over

(3 paths/router entry)– Better dynamic resilience through improved repair algorithms to

handle long-term faults– IEEE JSAC article pending

Support for rapid, hierarchical mobility– Scaleable mobility for large crowds traveling together– IPTPS paper in submission

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Tapestry Static Resilience (Sim)

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Instantaneous IP Tapestry / FRLS

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REAP/MINO/COMPASS Update

Introspective code / data migration in 3-tier hierarchies– Distributes server load, empowers limited devices– Provides illusion of high connectivity

Combines static trace analysis w/ dynamic monitoring of clients to predict appl’n / communication behavior

– Identify and optimize code/data placement– Analyzing EECS IMAP server traces for user session length

and inter-session mobility (see poster) Testbed technologies:

– REAP code migration toolkit– MINO E-mail OceanStore application– COMPASS: service instance location service (talk tomorrow)

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User IMAP Session Lengths (processed to remove auto checks)

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session length (seconds)

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50% of sessions <1000 seconds (17 minutes)

1800 seconds (30 minutes) = IMAP server's timeout setting

20% of sessions > 6000 secs

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Outline

Griffin– Motivation– Goals– Components

Tapas Update Tapestry Update REAP/MINO Update Beyond Griffin: DETER

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Cyber DEfense Technology Experimental Research (DETER)

NSF and DHS sponsored cyber-defense research project– Approx $10M total ($2.4 for UCB)

DETER Goals:– Design and construction of a testbed for network security

experiments,– Research on experimental methodology for network security, and– Research on network security.

DETER: focus on 1), but it needs to do some of 2) and 3) Goal: Duplicate observed attack effects in the testbed

– E.g., self-congestion for worms

DETER

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Related Goals

Vendor-heterogeneous environment– Reflects real-world, implementation interactions– Open source versus commercial code (e.g., timers)– Behavior under load/attack

Create a researcher’s electronic notebook– Network topologies, attack traces and generators– Background traffic traces and generators

Many requirements (some conflicting!)– Versatility, Controllability, Accessibility, Usability– Functionality, Transparency, Fairness, Containment– Security, Fidelity, Integrity

DETER

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Background

People: – Anthony Joseph, Ruzena Bajcsy, Shankar Sastry, David

Culler, Doug Tygar, David Wagner, Eric Fraser (staff), Yih-Chun Hu (postdoc)

– Small initial user community (usability versus containment) Hardware

– First cluster of ~64 PCs at USC/ISI West (Jan/Feb 04)– Second cluster at UCB (Mar/Apr 04)

Similar to ISI cluster, but with more hw routers Three experiment areas (EMIST)

– Worms, routing attacks, DDoS attacks Major demo of experimental results in DC in June 04

– Future: DHS, HSARPA, and White House “exercises”– E.g., LiveWire, DarkScreen, JWIG2004

DETER

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Preliminary UCB Architecture Proposal

latigid

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L2 switches

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Some Collaboration Opportunities

Research opportunities– Measuring application behavior under attack

Web servers, file servers, etc.– Strategies for mitigating attacks

Worm defenses, DDoS traceback and block, hardening routing protocols

– Operations and management Substantial knowledgebase from commercial customers (Tiger

teams) Donations

– VIFs: Cluster or security experience/research– Remote administration tools, remote SW installation setup tools– Nodes, Firewall machines, L2/L3 routers, HW sniffers, etc

DETER

Griffin Update: Toward an Agile, Predictive Infrastructure

Anthony D. Joseph

UC Berkeleyhttp://www.cs.berkeley.edu/~adj/

Sahara Retreat, January 2004

DETER