Amidst global warming and climate change, reducing the energy consumption of our telecommunication infrastructure becomes increasingly important. A popular approach to do so is switching off underutilized hardware components during low-load phases, supplemented by Traffic Engineering (TE) to free them from the remaining traffic. While there already is a body of work examining the potential of this Green TE concept, most of these approaches focus solely on maximizing the switched-off hardware while not overutilizing the network, thereby not considering other crucially important operational constraints and requirements (e.g., regarding latency). This renders the actual practical usability of these approaches questionable at best. To address this issue, this paper proposes two Segment Routing-based Green TE algorithms for maximizing energy savings while also adhering to a broad set of operational constraints. In extensive evaluations on a variety of networks, including recent data from a Tier-1 Internet Service Provider, we show that our approaches are able to maintain near-optimal power saving levels, while substantially reducing configuration effort, satisfying latency bounds, and adhering to other important constraints as well.

Many state-of-the-art Segment Routing (SR) Traffic Engineering (TE) algorithms rely on Linear Program (LP)-based optimization. However, the poor scalability of the latter and the resulting high computation times impose severe restrictions on the practical usability of such approaches for many use cases. A promising way to address these issues is to preemptively limit the number of SR paths considered during optimization by employing certain preprocessing strategies. In the first part of this paper, we conduct an extensive literature review of such preprocessing approaches together with a large-scale comparative performance study on a plethora of real-world topologies, including recent data from a Tier-1 Internet Service Provider (ISP). In the second part, we then use the insights gained from the former study to develop a novel combined preprocessing approach which also guarantees to not interfere with the satisfiability of practically important latency bound constraints. Our approach is able to reduce the number of SR paths to consider during optimization by as much as 97%–99%, while still allowing to achieve close to optimal solutions. This facilitates an around 10 × speedup for different LP-based SR TE algorithms, which is more than twice as good as what is achievable with any of the previously existing methods. Finally, we also study the applicability of the path preprocessing paradigm to the use case of tactical TE, showing that it facilitates an around 37% speedup in this context as well. All in all, this constitutes a major improvement over the current state-of-the-art and further facilitates the reliable use of LP-based TE optimization for large segment-routed networks.

Recent advancements in the context of Segment Routing (SR) have shown that the Midpoint Optimization (MO) concept enables a substantial reduction in the number of SR policies required to implement Traffic Engineering (TE) configurations. In this paper, we demonstrate that this concept can also be applied to the use case of tactical TE to considerably reduce the number of network changes required to react to critical events, thereby facilitating lower provisioning times and a generally improved time-to-repair. For this, we develop MOLS, a Local Search-based optimization routine that is able to provide close to optimal solutions within just a couple of seconds. The latter is shown based on extensive evaluations featuring various real-world topologies, including data from the backbone of a Tier-1 Internet Service Provider. Compared to state-of-the-art approaches relying on conventional SR, MOLS achieves similar or better solution quality while requiring substantially fewer configuration changes to implement the respective solutions. Furthermore, MOLS is able to resolve over 99% of overutilization scenarios resulting from different failure types, mostly within sub-second fashion and with an exceptionally small number of changes. Lastly, we also extend MOLS to adhere to specified latency bounds while even fixing initially violated ones.

Increasing the robustness of networks against failures or traffic changes is an important objective for many operators. Instead of only adapting network configurations to the new conditions in a reactive fashion after a critical event has already occurred, proactively hedging networks against those events has gained increasing popularity over the recent years. A variety of approaches have been proposed that implement this concept of proactive robustness using Segment Routing (SR). However, all of those focus solely on the use of conventional end-to-end SR. In this paper, we show that this can be a limiting factor regarding the achievable level of robustness and that utilizing the Midpoint Optimization concept for SR, instead, facilitates (sometimes considerably) more robust durable Traffic Engineering configurations. Furthermore, it also allows to reduce the number of SR policies required to implement the respective configurations. This is not only discussed from a theoretical perspective but also confirmed by evaluations on real-world data from the backbone network of a Tier-1 Internet Service Provider.

A recent innovation in the context of Segment Routing (SR) Traffic Engineering (TE) is the use of the Midpoint Optimization (MO) concept to substantially reduce the number of SR policies required to implement TE solutions. However, these benefits come at the price of a potential deterioration of traffic steering capabilities as the individual, per-demand traffic control of end-to-end (E2E) SR is lost. In this paper, we show that a hybrid SR approach utilizing both MO as well as E2E SR allows to combine the individual benefits of both approaches. It results in improved TE capabilities and, thus, enables better TE solutions. Besides discussing this with theoretical examples, we also confirm our findings in an extensive evaluation on real-world network topologies. For this, we propose a TE algorithm based on the hybrid SR approach and show that it outperforms state-of-the-art algorithms that rely solely on MO or E2E SR. Furthermore, we demonstrate that the hybrid SR approach is also suitable for the use-case of time-constrained, tactical TE.

Improving the energy efficiency of Internet Service Provider (ISP) backbone networks is an important objective for ISP operators. In these networks, the overall traffic load throughout the day can vary drastically, resulting in many backbone networks being highly overprovisioned during periods of lower traffic volume. This paper proposes a new Segment Routing (SR)-based traffic engineering algorithm to reduce power consumption of a backbone network in times of low utilization. The traffic steering capabilities of Segment Routing are utilized to remove traffic from as many links as possible. This is used to turn off the corresponding hardware components. Furthermore, it simultaneously ensures that solutions comply to additional operator requirements regarding the overall Maximum Link Utilization in the network. Based on data from a Tier-l ISP and a public available dataset, we show that our approach allows for up to 70 % of the overall linecards to be switched off, corresponding to an around 56 % reduction of the overall energy consumption of the network in times of low traffic demands.

In this paper, we discuss the concept of Midpoint Optimization (MO) for Segment Routing (SR). It is based on the idea of integrating SR policies into the Interior Gateway Protocol (IGP) to allow various demands to be steered into them. We discuss the benefits of this approach when compared to end-to-end SR and potential challenges that might arise in deployment. We further develop an LP-based optimization algorithm to assess the Traffic Engineering capabilities of MO for SR. Based on traffic and topology data from a Tier-1 Internet Service Provider as well as other, publicly available data, we show that this algorithm is able to achieve virtually optimal results with regards to the maximum link utilization, that are on par with state-of-the-art end-to-end SR approaches. However, our MO approach requires substantially less policies to do so. For some instances the achieved reduction ranges up to more than 99%.

Over the recent years, Segment Routing (SR)-based Traffic Engineering (TE) received more and more attention in the research community. However, what has been mostly neglected so far is its capability to configure looping forwarding paths that visit nodes or even edges multiple times. In this paper, we show that, against intuition, the configuration of such loops can inherit (in some occasions significant) benefits with regards to common TE objectives if Equal Cost Multipath (ECMP) is used. This is not only illustrated on small theoretical examples but also confirmed for 2SR with real-world data from the backbone network of a Tier-1 Internet Service Provider, as well as other publicly available topologies.