Complex Systems Workshop, September 20-21, 2012 Evaluation of Complex Systems J. Bryan Lyles Program Director CISE/CNS

Credit: MONET Group at UIUC Society Issues We increasingly rely on the Internet but are unsure we can trust its security, privacy or resilience Science Issues We cannot currently understand or predict the behavior of complex, large-scale networks Innovation Issues Substantial barriers to at-scale experimentation with new architectures, services, and technologies Global networks are creating extremely important new challenges

Revolutionary GENI Idea Slices and Deep Programmability Install the software I want throughout my network slice (into firewalls, routers, clouds, …) And keep my slice isolated from your slice, so we don’t interfere with each other We can run many different “networking experiments” in parallel

GENI and Complex Systems Scale Configurability, including configuration re-use Repeatability Tools supporting experimentation

GENI ≤ Problem Solution 2

Research Methodology What is “strange” about this graph? Levin, et al, Sigcomm 2008

The Other (more than) Half How do you plan an experiment? The framing of hypotheses Integration of a priori knowledge Identification of the components that matter Identification of parameter values to be tested Required measurements and instrumentation Experimentation plans that are complete but feasible Interpretation of results Significance & reliability What can we learn about moving beyond testing? Designing for “controlled failure” How do we design systems that are easy to characterize?

At the End of the Day Starting with a hypothesis about a complex system, I want an outside observer to have confidence that I have considered the alternatives, checked the boundary cases and fully understood system behavior. Where are our biggest gaps in being able to do this?