1. Three fun things to work on in your spare time John Wroclawski USC/ISI

2. The mostly theoretical: Reconceiving the intellectual basis of Network & Dist. System Architecture Electricity: Today… (…Architecture ???) Electricity: 1800… (…Architecture Today)

3. Theoretically Derived Architectures MANET resource allocation formulated as global optimization problem Primal-dual decomposition generates a set of dual problems/algorithms/modules: Local (except scheduling) Tied together through congestion prices System Architecture traceable to theoretically provable optimality.. Framework to reason rigorously about tradeoffs.. Utility function U_s{x_s} (strictly concave function of the sending rates) Applications Congestion control Routing Scheduling Channel Cross-layer interaction in form of “congestion prices” (cost per unit flow of sending data along a link to a destination ) Optimal Cross-Layer Congestion Control, Routing, and Scheduling Design in Ad Hoc Wireless Networks. Lijun Chen, Steven H. Low, Mung Chiang †, John C. Doyle (Caltech and † Princeton)

4. Language-Defined Architecture Role Based Architecture † imagined flexible, customizable location and composition of architectural functions But just a data path mechanism. Where do semantics come from? One possible idea: Architecture Composition Languages Explicit description may give: Introspection Run-time Validation … (defmethod (flow :check-security-policy) ((port protocol) `(cond ((eq port 'smtp) (…)))) (defwrapper (flow :check-security-policy) ((port protocol). wrapped-body) `(cond ((eq port 'smtp) (format t "~s no mail for you, monkey-boy~%" self)) (t,@wrapped-body (format t "~s pass traffic for ~s onward~%" self port)))) † From Protocol Stack to Protocol Heap - Role Based Architecture. Robert Braden, Ted Faber, and Mark Handley. Proc. Hotnets-1, ACM SIGCOMM CCR, v33 #1, Jan 2003

5. The possibly practical: Networks that know what they’re doing Network Management is a poster child challenge for the next few years Highly skilled humans… …managing a critical infrastructure of society… …by hand. Oops. Today’s network management is very low level Glossy interfaces often just make the problem harder

6. The alternative: networks that know what they’re trying to do Model based and similar techniques allow the system to understand its goals Separating model and actual implementation.. Allows introspection, consistency evaluation, similar actions.. To be performed by reasoning agents at high level. I think; therefore I am. Yikes!

7. † A survey of fault localization techniques in computer networks. M. Steinder and A. Sethi, Science of Computer Programming 53 (2004) Problem 1: The lack of Domain-Appropriate Algorithms Some limitations of current fault diagnosis algorithms † : Multi-layer fault isolation Temporal correlation among events Distributed fault localization techniques Fault localization in service- oriented environments Fault localization in dynamic networks Obtaining fault localization models Distributed Fault Diagnosis across multiple administrative domains* Partition problem hierarchically, following routing If failure cannot be diagnosed (probabilistically) within local domain… …delegate to “higher level manager” with interdomain routing expertise HL manager calls multiple local managers.. Which report back so HL manager can synthesize result * Multi-domain diagnosis of end to end service failures in hierarchically routed networks. M. Steinder and A. Sethi, Unpublished.

8. Problem 2: Shared, Common Structure High level problem assertion: Fixit! Network (re)builder Network region Network observer High level specs: Goals and constraints High level specs: Goals and constraints DetailsStatus Problem resolver Region composer High level operational characterization: “Success story”! Your region composer Negotiation Design specs Network explainer A Knowledge Plane for the Internet. D. D. Clark, C. Partridge, J. C. Ramming, and J. Wroclawski, Proc. ACM SIGCOMM 2003.

9. The nearly impossible: Building a realistic experimental research facility AnalysisSimulation / EmulationExperiment At Scale Deployment (models)(code) (results) (measurements and feedback Goal: Seamless conception-to-deployment process “GENI is an open, large-scale, realistic experimental facility that will revolutionize research in global communication networks.”

10. Modeling the Real World “Real users” User opt-in Real user workloads Long lived services Economics “virtual costs” assigned to system elements.. Failures Modeled or arbitrary hw failures and sw bugs.. Administrative environment Multiple players with competing interests..