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David Choffnes, Winter 2006 Autonomic Computing A Knowledge Plane for the Internet, D. Clark, J. Ramming, J. Wroclawski, SIGCOMM, August. 2003..

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Presentation on theme: "David Choffnes, Winter 2006 Autonomic Computing A Knowledge Plane for the Internet, D. Clark, J. Ramming, J. Wroclawski, SIGCOMM, August. 2003.."— Presentation transcript:

1 David Choffnes, Winter 2006 Autonomic Computing A Knowledge Plane for the Internet, D. Clark, J. Ramming, J. Wroclawski, SIGCOMM, August

2 CS 395/495 Autonomic Computing Systems EECS, Northwestern University 2 The Internet is great, but… Intelligence is only at the edges –When failures occur, takes a long time to debug and fix –Difficult to configure and administer New goal for the network –Understand what it’s being asked to do –Take care of itself Internet needs AI/CogSci –Need to abstract high-level goals from low-level details –Make decisions based on incomplete/imperfect information –Learn from previous experience/examples

3 CS 395/495 Autonomic Computing Systems EECS, Northwestern University 3 A Knowledge Plane Distributed cognitive system –Global vs. regional perspective –Edge involvement –Composition ability –Unified approach –Cognitive framework Make judgments in the face of partial/conflicting information Incorporate knowledge representation, learning, reasoning

4 CS 395/495 Autonomic Computing Systems EECS, Northwestern University 4

5 5 Why? Do we need a new construct? –Data plane hides information, control plane exposes everything Need middle ground to express goals at a high level and have them automatically fulfilled by tuning at the low level Unified approach –Network measurement (everyone uses same info) –Tracing a hurricane to the flap of a butterfly’s wings Cognitive System –“close the loop” on the network as does an ordinary control system –recognize-explain cycle => recognize-explain-suggest cycle => recognize-act cycle for many management tasks –the KP must be able to learn and reason –model behavior, dependencies, and requirements of applications

6 CS 395/495 Autonomic Computing Systems EECS, Northwestern University 6 What is it good for? Fault diagnosis/mitigation –WHY, FIX constructs Automatic (re)configuration –Ongoing operation to meet goals –KP as assistant to network admins Overlay networks –KP maintains performance information Knowledge-enhanced IDS –Data gathering and correlation

7 CS 395/495 Autonomic Computing Systems EECS, Northwestern University 7 Knowledge Plane Architecture Distributed organization –Bottom-up –Constraint-driven E.g., “no multicast” May adopt behavior not specifically constrained –Compositional (moves from simple to complex) Global perspective –Data/knowledge integration –Expect imperfect info –Reason about tradeoffs

8 CS 395/495 Autonomic Computing Systems EECS, Northwestern University 8 Functional/Structural Requirements Functional –Gather/Acquire/Generate observations, assertions and explanations about network conditions –Cross-regional reasoning –Knowledge-driven routing w/ understanding of tradeoffs –Trust/Robustness Structural –Sensors and actuators –Don’t do: Each region reasons about only itself –Maybe: Multiple regions compete to provide info about an AS

9 CS 395/495 Autonomic Computing Systems EECS, Northwestern University 9

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11 CS 395/495 Autonomic Computing Systems EECS, Northwestern University 11 Creating a KP Building blocks –Epidemic algs (dist), Bayesian NWs (learning), rank aggregation (trust), constraint satisfaction algs, policy-based management. Challenges –Representing and utilizing knowledge –Scalability –Routing knowledge –Economic incentives –Malicious users and trust


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