No Traffic to Cry: Traffic-Oblivious Link Deactivation for Green Traffic Engineering
🤖 AI Summary
This work addresses the limitations of traditional green traffic engineering, which relies on specific traffic matrices and thus suffers from frequent reconfigurations and poor adaptability to dynamic traffic. To overcome this, the authors propose a traffic-agnostic link sleeping mechanism that minimizes the number of active links while guaranteeing routability for any scaled traffic demand, thereby reducing energy consumption. The problem is formally formulated for the first time as an NP-hard optimization task, and the paper presents a max(1/(ϱ·λ_min), 2)-approximation algorithm along with two post-processing heuristics. Experimental results demonstrate that the proposed approach rapidly generates near-optimal energy-saving configurations, significantly reducing the number of active links in backbone networks and achieving stable, efficient energy savings.
Application Category
📝 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.
Problem
Research questions and friction points this paper is trying to address.
Green Traffic Engineering
Traffic-Oblivious Routing
Link Deactivation
Energy Efficiency
Network Optimization
Innovation
Methods, ideas, or system contributions that make the work stand out.
traffic-oblivious routing
green traffic engineering
link deactivation
approximation algorithm
energy-efficient networking
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