IP networking is a spectacular success, catalyzing the diffusion of data networking across academic institutions, governments, businesses, and homes, world-wide. Yet, despite the fundamental importance of this infrastructure, today's networks are surprisingly fragile and increasingly difficult to configure, control, and maintain. Using a clean-slate approach, the research team will explore a number of fundamental questions related to network control and management. The focus of the research agenda is on IP (layer-3) networks, though the principal investigators (PIs) intend to create networking primitives and services that apply equally well to other technologies, such as layer-2 networks (e.g., Ethernet networks). The starting point for the work is a small set of principles, guiding the control of the network: network-wide views, network-level objectives, and direct control. These principles lead the PIs to a refactoring of network functionality into four components---the data, discovery, dissemination, and decision planes. Via this architecture, which the PIs term the 4D approach to network control and management, the team intends to create, prototype, and demonstrate breakthrough mechanisms that will dramatically simplify and strengthen data networking.
INTELLECTUAL IMPACT: The proposed research will address fundamental questions that are key to improving IP control and management: How to go from networks that blend decision logic with specific protocols and mechanisms to an architecture that abstracts and isolates the decision logic and admits a range of efficient implementations? How to go from networks that consist of numerous uncoordinated, error-prone mechanisms, to ones where the low-level mechanisms are driven in a consistent manner by network-level objectives? How to go from networks where people set parameters (twist knobs), hoping to coax the system to reach a desired state, to one where network designers can directly express controls that automatically steer the system toward the desired state? How to go from networks where human administrators leverage network-wide views and box-level capabilities at slow timescales in decision-support systems, to one where the network itself leverages this information in real time?
BROADER IMPACT: The proposed research seeks to produce fundamental knowledge that will advance the state-of-the-art in large-scale network architecture, control and management. It intends to lay the groundwork for data networks (in academic campuses, data centers, enterprises, metro areas, backbones) that are more robust, more evolvable, and less prone to security breaches. The involvement of industrial partners in this project will accelerate the transfer of the research results into operation.
The general educational impacts are in the training of students, postdocs and researchers, allowing them to cross boundaries between theoretical and system-oriented research. It offers students the unique opportunity to pursue systems work, guided by a deep understanding of fundamental principles, and to use their knowledge creatively to conceive and design innovative software tools and systems. The research team will use existing institutional programs to recruit and involve students from underrepresented groups into the research program from its earliest stages. The results of the research project will be integrated into the undergraduate and graduate computer science program. The software tools to be developed will provide the basis for class projects in the graduate-level courses of the participating institutions. The PIs will create graduate-level courses based on the project's research priorities and goals. The findings will also be used as case studies in undergraduate studies to enhance students' understanding of the main architectural design challenges and control issues of large-scale networks
