No Traffic to Cry: Traffic-Oblivious Link Deactivation for Green Traffic Engineering

TL;DR

This paper introduces a traffic-oblivious approach for energy-efficient network link deactivation that guarantees routing of scaled traffic matrices without frequent reconfigurations, using approximation algorithms and heuristics.

Contribution

It presents a novel NP-hard problem formulation and a max-approximation algorithm for energy savings in networks, avoiding the need for traffic matrix-specific adjustments.

Findings

The approach guarantees routing for scaled traffic matrices with minimal active links.

The proposed algorithms generate near-optimal solutions quickly.

The method reduces the need for frequent network reconfigurations.

Abstract

As internet traffic grows, the underlying infrastructure consumes increasing amounts of energy. During off-peak hours, large parts of the networks remain underutilized, presenting significant potential for energy savings. Existing Green Traffic Engineering approaches attempt to leverage this potential by switching off those parts of the networks that are not required for the routing of specific traffic matrices. When traffic changes, the approaches need to adapt rapidly, which is hard to achieve given the complexity of the problem. We take a fundamentally different approach: instead of considering a specific traffic matrix, we rely on a traffic-oblivious routing scheme. We discuss the NP-hard problem of activating as few connections as possible while still guaranteeing that any down-scaled traffic matrix $\varrho\cdot T$ can be routed, where $\varrho \in (0,1)$ and $T$ is any traffic matrix routable in the original network. We present a $\max(\frac{1}{\varrho\cdot\lambda_{\text{min}}},2)$-approximation algorithm for this problem, with $\lambda_{\text{min}}$ denoting the minimum number of connections between any two connected routers. Additionally, we propose two post-processing heuristics to further improve solution quality. Our evaluation shows that we can quickly generate near-optimal solutions. By design, our method avoids the need for frequent reconfigurations and offers a promising direction to achieve practical energy savings in backbone networks.