Griffin Update: Toward an Agile, Predictive Infrastructure Anthony D. Joseph UC Berkeley Sahara Retreat, January 2004 DE T ER

2 Outline Griffin – Motivation – Goals – Components Tapas Update Tapestry Update REAP/MINO Update Beyond Griffin: DETER

3 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 – 3  5 orders of magnitude of bandwidth from 10's Kb/s  1 Gb/s – 4  6 orders of magnitude of latency from 1  sec  1,000's ms – 5  9 orders of magnitude of loss rates from  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

4 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

5 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

6 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 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

7 Outline Griffin – Motivation – Goals – Components Tapas Update Tapestry Update REAP/MINO Update Beyond Griffin: DETER

8 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 ( ) – 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)

9 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

10 Tapestry Static Resilience (Sim)

11 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 OceanStore application – COMPASS: service instance location service (talk tomorrow)

12 User IMAP Session Lengths (processed to remove auto checks)

13 Outline Griffin – Motivation – Goals – Components Tapas Update Tapestry Update REAP/MINO Update Beyond Griffin: DETER

14 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 DE T ER

15 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 DE T ER

16 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 DE T ER

17 Preliminary UCB Architecture Proposal DE T ER

18 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 DE T ER

Griffin Update: Toward an Agile, Predictive Infrastructure Anthony D. Joseph UC Berkeley Sahara Retreat, January 2004 DE T ER