Current state of affairs No framework for theoretical analysis of (some) protocols –chaos small changes make a lot of difference difficult to tune - or even to predict the effect of a change –deficient performance –not easy to express goals and policies –limited service models –cross-protocol interactions at best obtuse –insecure –poorly understood (but widely used) difficult to troubleshoot horrific to operate

Research Topics and Themes Clean-slate protocol design –Framework for analysis and formal objectives, e.g. Online, adversarial models Network utility maximization objective –Incentive-aware –Evolvable –Manageable –Secure –Robust, self-managing and self-correcting –Flexible service models support for real-time systems –Integration of all parties and across protocols languages for negotiation theory of composition of systems –Employing state-of-the-art theory in both CS and EE, e.g., randomized algorithms worst-case analysis access control theory model checking and verification signal propagation control theory

Improving the protocols NOW Evolving the current designs –Transition technologies Virtualization Tunneling, encapsulation, overlays –Path to adoption Incremental deployability Incentives to adopt Exploring the limits of existing protocols –How much motivation is there for a clean-slate design? –Can we identify operating regimes or paradigms in which the current protocols work well

Interaction between applications and infrastructure –Robust algorithms, e.g., optimal oblivious routing Building a security infrastructure Monitoring and measurement Massive data streaming, sketches

Other sorts of networks Delay tolerant Enterprise Overlay Virtual Private Networks Optical Peer-to-peer

Wireless Networking Routing in wireless and ad-hoc networks Scheduling transmissions Analysis of interference Coding schemes Addressing Geographic? Static?

Whither? Multi-pronged problems Challenge to theory community Need to solve many facets of the problem at the same time Not easy to “quantify” Poor integration across networking research community –Don’t speak the same language Hard to formalize problems Hard to know which problems to formalize Best theoretical techniques aren’t being adopted –Don’t appreciate the best work of others

What NSF might do NSF can kick-start collaborations between theoreticians and systems builders –Funding allocated for programs that require proposals to have a well-integrated theoretical and experimental/systems approach –Curriculum building –Workshops aimed at identifying common ground –Integrated panel reviews