Abstract

A scalable, low-latency, high-speed, and energy-efficient data center network is a key element in the deployment of future large-scale data centers, and photonic switching has recently been recognized as a promising solution to fulfill these goals. In this study, we present a packet-switched optical network (PSON) architecture with centralized control for intra-data-center connectivity. For efficient PSON operation, intelligent yet low-complexity bandwidth-scheduling algorithms are critical. To align with realistic traffic flows in a data center, we consider “mice flow,” which occurs frequently but carries a small number of bytes, and “elephant flow,” which occurs occasionally but has a huge number of bytes. To classify traffic flows with different characteristics, we investigate various machine-learning (classification) techniques, such as C4.5 and Naïve Bayes Discretization, and compare their performance in terms of accuracy and classification speed. We also develop a priority-aware scheduling algorithm for packet switching, which is optimized for PSON, and is adaptive to flow classification under a dynamic traffic scenario. Numerical simulations show that our proposed scheduling algorithm assisted by flow-classification techniques can outperform a benchmark algorithm in terms of average delay and packet-loss ratio.

© 2018 Optical Society of America

Multicast Scheduling of Wavelength-Tunable, Multiqueue Optical Data Center Switches

Kamran Keykhosravi, Houman Rastegarfar, and Erik Agrell
J. Opt. Commun. Netw. 10(4) 353-364 (2018)

TCP Flow Classification and Bandwidth Aggregation in Optically Interconnected Data Center Networks

Houman Rastegarfar, Madeleine Glick, Nicolaas Viljoen, Mingwei Yang, John Wissinger, Lloyd LaComb, and Nasser Peyghambarian
J. Opt. Commun. Netw. 8(10) 777-786 (2016)

HiFOST: A Scalable and Low-Latency Hybrid Data Center Network Architecture Based on Flow-Controlled Fast Optical Switches

Fulong Yan, Xuwei Xue, and Nicola Calabretta
J. Opt. Commun. Netw. 10(7) B1-B14 (2018)

Machine-Learning-Based Prediction for Resource (Re)allocation in Optical Data Center Networks

Sandeep Kumar Singh and Admela Jukan
J. Opt. Commun. Netw. 10(10) D12-D28 (2018)

Scalable and low server-to-server latency data center network architecture based on optical packet inter-rack and intra-rack switching

Georgios Drainakis, Peristera Baziana, and Adonis Bogris
J. Opt. Commun. Netw. 15(11) 804-819 (2023)