Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published June 2015 | metadata_only
Book Section - Chapter

A Case Study in Network Architecture Tradeoffs


Software defined networking (SDN) establishes a separation between the control plane and the data plane, allowing network intelligence and state to be centralized -- in this way the underlying network infrastructure is hidden from the applications. This is in stark contrast to existing distributed networking architectures, in which the control and data planes are vertically combined, and network intelligence and state, as well as applications, are distributed throughout the network. It is also conceivable that some elements of network functionality be implemented in a centralized manner via SDN, and that other components be implemented in a distributed manner. Further, distributed implementations can have varying levels of decentralization, ranging from myopic (in which local algorithms use only local information) to coordinated (in which local algorithms use both local and shared information). In this way, myopic distributed architectures and fully centralized architectures lie at the two extremes of a broader hybrid software defined networking (HySDN) design space. Using admission control as a case study, we leverage recent developments in distributed optimal control to provide network designers with tools to quantitatively compare different architectures, allowing them to explore the relevant HySDN design space in a principled manner. In particular, we assume that routing is done at a slower timescale, and seek to stabilize the network around a desirable operating point despite physical communication delays imposed by the network and rapidly varying traffic demand. We show that there exist scenarios for which one architecture allows for fundamentally better performance than another, thus highlighting the usefulness of the approach proposed in this paper.

Additional Information

© 2015 ACM. N. Matni & J. C. Doyle were in part supported by the AFOSR and the Institute for Collaborative Biotechnologies through grant W911NF-09-0001 from the U.S. Army Research Office. A. Tang was in part supported by the ONR under grant N00014-12-1-1055.

Additional details

August 20, 2023
August 20, 2023