# Design and Provision of Traffic Grooming for Optical Wireless Data Center Networks

## TL;DR

This paper proposes a novel traffic grooming approach for optical wireless data center networks, optimizing flow management and resource allocation to improve bandwidth efficiency and reduce congestion.

## Contribution

It introduces a top-down traffic grooming framework with a mixed-integer optimization model and a fast sub-optimal solution for optical wireless DCNs.

## Key findings

- Enhanced bandwidth utilization and flow completion times.
- Effective separation and handling of elephant and mice flows.
- Reduced traffic congestion and improved delay characteristics.

## Abstract

Traditional wired data center networks (DCNs) suffer from cabling complexity, lack flexibility, and are limited by the speed of digital switches. In this paper, we alternatively develop a top-down traffic grooming (TG) approach to the design and provisioning of mission-critical optical wireless DCNs. While switches are modeled as hybrid optoelectronic cross-connects, links are modeled as wavelength division multiplexing (WDM) capable free-space optic (FSO) channels. Using the standard TG terminology, we formulate the optimal mixed-integer TG problem considering the virtual topology, flow conversation, connection topology, non-bifurcation, and capacity constraints. Thereafter, we develop a fast yet efficient sub-optimal solution which grooms mice flows (MFs) and mission-critical flows (CFs) and forward on predetermined rack-to-rack (R2R) lightpaths. On the other hand, elephant flows (EFs) are forwarded over dedicated server-to-server (S2S) express lightpaths whose routes and capacity are dynamically determined based on the availability of wavelength and capacity. To prioritize the CFs, we consider low and high priority queues and analyze the delay characteristics such as waiting times, maximum hop counts, and blocking probability. As a result of grooming the sub-wavelength traffic and adjusting the wavelength capacities, numerical results show that the proposed solutions can achieve significant performance enhancement by utilizing the bandwidth more efficiently, completing the flows faster than delay sensitivity requirements, and avoiding the traffic congestion by treating EFs and MFs separately.