arXiv subjects

Simon Scherrer

Publications and source records attributed to Simon Scherrer.

13 recordsLinked to original sources

arXiv2025

A Control-Theoretic Perspective on BBR/CUBIC Congestion-Control Competition

To understand the fairness properties of the BBR congestion-control algorithm (CCA), previous research has analyzed BBR behavior with a variety of models. However, previous model-based work suffers from a trade-off between accuracy and interpretability: While dynamic fluid models generate highly accurate predictions through simulation, the causes of their predictions cannot be easily understood. In contrast, steady-state models predict CCA behavior in a manner that is intuitively understandable, but often less accurate. This trade-off is especially consequential when analyzing the competition between BBR and traditional loss-based CCAs, as this competition often suffers from instability, i.e., sending-rate oscillation. Steady-state models cannot predict this instability at all, and fluid-model simulation cannot yield analytical results regarding preconditions and severity of the oscillation. To overcome this trade-off, we extend the recent dynamic fluid model of BBR by means of control theory. Based on this control-theoretic analysis, we derive quantitative conditions for BBR/CUBIC oscillation, identify network settings that are susceptible to instability, and find that these conditions are frequently satisfied by practical networks. Our analysis illuminates the fairness implications of BBR/CUBIC oscillation, namely by deriving and experimentally validating fairness bounds that reflect the extreme rate distributions during oscillation. In summary, our analysis shows that BBR/CUBIC oscillation is frequent and harms BBR fairness, but can be remedied by means of our control-theoretic framework.

cs.NI↗

arXiv2024

Sliding or Rolling? Characterizing single-particle contacts

Contacts between particles in dense, sheared suspensions are believed to underpin much of their rheology. Roughness and adhesion are known to constrain the relative motion of particles, and thus globally affect the shear response, but an experimental description of how they microscopically influence the transmission of forces and relative displacements within contacts is lacking. Here we show that an innovative colloidal-probe atomic force microscopy technique allows the simultaneous measurement of normal and tangential forces exchanged between tailored surfaces and microparticles while tracking their relative sliding and rolling, unlocking the direct measurement of coefficients of rolling friction, as well as of sliding friction. We demonstrate that, in the presence of sufficient traction, particles spontaneously roll, reducing dissipation and promoting longer-lasting contacts. Conversely, when rolling is prevented, friction is greatly enhanced for rough and adhesive surfaces, while smooth particles coated by polymer brushes maintain well-lubricated contacts. We find that surface roughness induces rolling due to load-dependent asperity interlocking, leading to large off-axis particle rotations. In contrast, smooth, adhesive surfaces promote rolling along the principal axis of motion. Our results offer direct values of friction coefficients for numerical studies and an interpretation of the onset of discontinuous shear thickening based on them, opening up new ways to tailor rheology via contact engineering.

cond-mat.soft↗

arXiv2024

GLIDS: A Global Latency Information Dissemination System

A recent advance in networking is the deployment of path-aware multipath network architectures, where network endpoints are given multiple network paths to send their data on. In this work, we tackle the challenge of selecting paths for latency-sensitive applications. Even today's path-aware networks, which are much smaller than the current Internet, already offer dozens and in several cases over a hundred paths to a given destination, making it impractical to measure all path latencies to find the lowest latency path. Furthermore, for short flows, performing latency measurements may not provide benefits as the flow may finish before completing the measurements. To overcome these issues, we argue that endpoints should be provided with a latency estimate before sending any packets, enabling latency-aware path choice for the first packet sent. As we cannot predict the end-to-end latency due to dynamically changing queuing delays, we measure and disseminate the propagation latency, enabling novel use cases and solving concrete problems in current network protocols. We present the Global Latency Information Dissemination System (GLIDS), which is a step toward global latency transparency through the dissemination of propagation latency information.

cs.NI↗

arXiv2023

ALBUS: a Probabilistic Monitoring Algorithm to Counter Burst-Flood Attacks

Modern DDoS defense systems rely on probabilistic monitoring algorithms to identify flows that exceed a volume threshold and should thus be penalized. Commonly, classic sketch algorithms are considered sufficiently accurate for usage in DDoS defense. However, as we show in this paper, these algorithms achieve poor detection accuracy under burst-flood attacks, i.e., volumetric DDoS attacks composed of a swarm of medium-rate sub-second traffic bursts. Under this challenging attack pattern, traditional sketch algorithms can only detect a high share of the attack bursts by incurring a large number of false positives. In this paper, we present ALBUS, a probabilistic monitoring algorithm that overcomes the inherent limitations of previous schemes: ALBUS is highly effective at detecting large bursts while reporting no legitimate flows, and therefore improves on prior work regarding both recall and precision. Besides improving accuracy, ALBUS scales to high traffic rates, which we demonstrate with an FPGA implementation, and is suitable for programmable switches, which we showcase with a P4 implementation.

cs.CR↗

arXiv2023

Quality Competition Among Internet Service Providers

Internet service providers (ISPs) have a variety of quality attributes that determine their attractiveness for data transmission, ranging from quality-of-service metrics such as jitter to security properties such as the presence of DDoS defense systems. ISPs should optimize these attributes in line with their profit objective, i.e., maximize revenue from attracted traffic while minimizing attribute-related cost, all in the context of alternative offers by competing ISPs. However, this attribute optimization is difficult not least because many aspects of ISP competition are barely understood on a systematic level, e.g., the multi-dimensional and cost-driving nature of path quality, and the distributed decision making of ISPs on the same path. In this paper, we improve this understanding by analyzing how ISP competition affects path quality and ISP profits. To that end, we develop a game-theoretic model in which ISPs (i) affect path quality via multiple attributes that entail costs, (ii) are on paths together with other selfish ISPs, and (iii) are in competition with alternative paths when attracting traffic. The model enables an extensive theoretical analysis, surprisingly showing that competition can have both positive and negative effects on path quality and ISP profits, depending on the network topology and the cost structure of ISPs. However, a large-scale simulation, which draws on real-world data to instantiate the model, shows that the positive effects will likely prevail in practice: If the number of selectable paths towards any destination increases from 1 to 5, the prevalence of quality attributes increases by at least 50%, while 75% of ISPs improve their profit.

cs.NI↗

arXiv2022

Carbon-Intelligent Global Routing in Path-Aware Networks

The growing energy consumption of Information and Communication Technology (ICT) has raised concerns about its environmental impact. However, the carbon efficiency of data transmission over the Internet has so far received little attention. This carbon efficiency can be enhanced effectively by sending traffic over carbon-efficient inter-domain paths. However, challenges in estimating and disseminating carbon intensity of inter-domain paths have prevented carbon-aware path selection from becoming a reality. In this paper, we take advantage of path-aware network architectures to overcome these challenges. In particular, we design CIRo, a system for forecasting the carbon intensity of inter-domain paths and disseminating them across the Internet. We implement a proof of concept for CIRo on the codebase of the SCION path-aware Internet architecture and test it on the SCIONLab global research testbed. Further, we demonstrate the potential of CIRo for reducing the carbon footprint of endpoints and end domains through large-scale simulations. We show that CIRo can reduce the carbon intensity of communications by at least 47% for half of the domain pairs and the carbon footprint of Internet usage by at least 50% for 87% of end domains.

cs.NI↗

arXiv2022

Model-Based Insights on the Performance, Fairness, and Stability of BBR

Google's BBR is the most prominent result of the recently revived quest for efficient, fair, and flexible congestion-control algorithms (CCAs). While the performance of BBR has been investigated by numerous studies, previous work still leaves gaps in the understanding of BBR performance: Experiment-based studies generally only consider network settings that researchers can set up with manageable effort, and model-based studies neglect important issues like convergence. To complement previous BBR analyses, this paper presents a fluid model of BBRv1 and BBRv2, allowing both efficient simulation under a wide variety of network settings and analytical treatment such as stability analysis. By experimental validation, we show that our fluid model provides highly accurate predictions of BBR behavior. Through extensive simulations and theoretical analysis, we arrive at several insights into both BBR versions, including a previously unknown bufferbloat issue in BBRv2.

cs.NI↗

arXiv2021

An Axiomatic Perspective on the Performance Effects of End-Host Path Selection

In various contexts of networking research, end-host path selection has recently regained momentum as a design principle. While such path selection has the potential to increase performance and security of networks, there is a prominent concern that it could also lead to network instability (i.e., flow-volume oscillation) if paths are selected in a greedy, load-adaptive fashion. However, the extent and the impact vectors of instability caused by path selection are rarely concretized or quantified, which is essential to discuss the merits and drawbacks of end-host path selection. In this work, we investigate the effect of end-host path selection on various metrics of networks both qualitatively and quantitatively. To achieve general and fundamental insights, we leverage the recently introduced axiomatic perspective on congestion control and adapt it to accommodate joint algorithms for path selection and congestion control, i.e., multi-path congestion-control protocols. Using this approach, we identify equilibria of the multi-path congestion-control dynamics and analytically characterize these equilibria with respect to important metrics of interest in networks (the 'axioms') such as efficiency, fairness, and loss avoidance. Moreover, we analyze how these axiomatic ratings for a general network change compared to a scenario without path selection, thereby obtaining an interpretable and quantititative formalization of the performance impact of end-host path-selection. Finally, we show that there is a fundamental trade-off in multi-path congestion-control protocol design between efficiency, stability, and loss avoidance on one side and fairness and responsiveness on the other side.

cs.NI↗

arXiv2021

Enabling Novel Interconnection Agreements with Path-Aware Networking Architectures

Path-aware networks (PANs) are emerging as an intriguing new paradigm with the potential to significantly improve the dependability and efficiency of networks. However, the benefits of PANs can only be realized if the adoption of such architectures is economically viable. This paper shows that PANs enable novel interconnection agreements among autonomous systems, which allow to considerably improve both economic profits and path diversity compared to today's Internet. Specifically, by supporting packet forwarding along a path selected by the packet source, PANs do not require the Gao-Rexford conditions to ensure stability. Hence, autonomous systems can establish novel agreements, creating new paths which demonstrably improve latency and bandwidth metrics in many cases. This paper also expounds two methods to set up agreements which are Pareto-optimal, fair, and thus attractive to both parties. We further present a bargaining mechanism that allows two parties to efficiently automate agreement negotiations.

cs.NI↗

arXiv2021

Low-Rate Overuse Flow Tracer (LOFT): An Efficient and Scalable Algorithm for Detecting Overuse Flows

Current probabilistic flow-size monitoring can only detect heavy hitters (e.g., flows utilizing 10 times their permitted bandwidth), but cannot detect smaller overuse (e.g., flows utilizing 50-100% more than their permitted bandwidth). Thus, these systems lack accuracy in the challenging environment of high-throughput packet processing, where fast-memory resources are scarce. Nevertheless, many applications rely on accurate flow-size estimation, e.g. for network monitoring, anomaly detection and Quality of Service. We design, analyze, implement, and evaluate LOFT, a new approach for efficiently detecting overuse flows that achieves dramatically better properties than prior work. LOFT can detect 1.5x overuse flows in one second, whereas prior approaches fail to detect 2x overuse flows within a timeout of 300 seconds. We demonstrate LOFT's suitability for high-speed packet processing with implementations in the DPDK framework and on an FPGA.

cs.NI↗

arXiv2020

Incentivizing Stable Path Selection in Future Internet Architectures

By delegating path control to end-hosts, future Internet architectures offer flexibility for path selection. However, there is a concern that the distributed routing decisions by end-hosts, in particular load-adaptive routing, can lead to oscillations if path selection is performed without coordination or accurate load information. Prior research has addressed this problem by devising path-selection policies that lead to stability. However, little is known about the viability of these policies in the Internet context, where selfish end-hosts can deviate from a prescribed policy if such a deviation is beneficial fromtheir individual perspective. In order to achieve network stability in future Internet architectures, it is essential that end-hosts have an incentive to adopt a stability-oriented path-selection policy. In this work, we perform the first incentive analysis of the stability-inducing path-selection policies proposed in the literature. Building on a game-theoretic model of end-host path selection, we show that these policies are in fact incompatible with the self-interest of end-hosts, as these strategies make it worthwhile to pursue an oscillatory path-selection strategy. Therefore, stability in networks with selfish end-hosts must be enforced by incentive-compatible mechanisms. We present two such mechanisms and formally prove their incentive compatibility.

cs.NI↗

arXiv2020

The Value of Information in Selfish Routing

Path selection by selfish agents has traditionally been studied by comparing social optima and equilibria in the Wardrop model, i.e., by investigating the Price of Anarchy in selfish routing. In this work, we refine and extend the traditional selfish-routing model in order to answer questions that arise in emerging path-aware Internet architectures. The model enables us to characterize the impact of different degrees of congestion information that users possess. Furthermore, it allows us to analytically quantify the impact of selfish routing, not only on users, but also on network operators. Based on our model, we show that the cost of selfish routing depends on the network topology, the perspective (users versus network operators), and the information that users have. Surprisingly, we show analytically and empirically that less information tends to lower the Price of Anarchy, almost to the optimum. Our results hence suggest that selfish routing has modest social cost even without the dissemination of path-load information.

cs.GT↗

arXiv2018

CLEF: Limiting the Damage Caused by Large Flows in the Internet Core (Technical Report)

The detection of network flows that send excessive amounts of traffic is of increasing importance to enforce QoS and to counter DDoS attacks. Large-flow detection has been previously explored, but the proposed approaches can be used on high-capacity core routers only at the cost of significantly reduced accuracy, due to their otherwise too high memory and processing overhead. We propose CLEF, a new large-flow detection scheme with low memory requirements, which maintains high accuracy under the strict conditions of high-capacity core routers. We compare our scheme with previous proposals through extensive theoretical analysis, and with an evaluation based on worst-case-scenario attack traffic. We show that CLEF outperforms previously proposed systems in settings with limited memory.

cs.NI↗