1 / 9

Evaluation of Complex Systems

Complex Systems Workshop, September 20-21, 2012. Evaluation of Complex Systems. J. Bryan Lyles Program Director CISE/CNS. Credit: MONET Group at UIUC. Global networks are creating extremely important new challenges. Science Issues

kimi
Download Presentation

Evaluation of Complex Systems

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

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

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

  3. Revolutionary GENI IdeaSlices 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

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

  5. GENI ≤ Problem Solution 2

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

  7. 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?

  8. 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?

More Related