Principal Investigator Eytan Modiano
Project Website http://www.nsf.gov/awardsearch/showAward?AWD_ID=1617091&HistoricalAwards=false
Project Start Date October 2016
Project End Date September 2019
Huge data centers increasingly form the heart of the Internet. This project will develop an optical-fiber-based network architecture for data centers, together with associated network control algorithms, that is highly configurable, scalable, and meets the requirements of future data centers. The proposed architecture is hierarchical and uses low-cost passive optics at the lowest levels of the hierarchy, and a combination of electronic and configurable optical switching at higher layers, thus striking a balance between cost and capability of optical systems and devices. Moreover, the use of passive optics significantly reduces energy consumption, which has become an important consideration in large data centers.
Research plan includes both architecture development and algorithm design, including:
(1) Develop a Wave-Division-Multiplexing (WDM)-based DCN architecture that is low-cost, scalable, and configurable, for meeting the communication requirements of future data centers.
(2) Develop dynamic reconfiguration algorithms for changing the network topology in response to changes in traffic conditions, in order to reduce the communication load on the network.
(3) Investigate the use of passive optics in order to reduce energy consumption, and compare different architectural alternatives in terms of energy consumption.
The proposed architecture has the potential to dramatically change the way that DCNs are designed, significantly improving their scalability, robustness and energy efficiency. In addition, this investigation will include: (1) dissemination of the results through journal and conference publications to advance the field; (2) incorporation of new theory and algorithms developed through this work into advanced graduate classes; (3) development of experimental projects for undergraduate students; (4) technology transfer to industry (including potential early adoption by an industry partner) and (5) training of graduate and undergraduate students.