arXiv subjects

Philipp Schneider

Publications and source records attributed to Philipp Schneider.

15 recordsLinked to original sources

arXiv2026

Simulations between Strongly Sublinear MPC and Node-Capacitated Clique

We study how the Massively Parallel Computation (MPC) model in the strongly sublinear regime relates to the classic, graph-centric distributed models, focusing on the Node-Capacitated Clique (NCC), a bandwidth-parametrized generalization of the Congested Clique. In MPC, $M$ machines with per-machine memory $S$ hold a partition of the input graph. In NCC, we are given $n$ nodes that are themselves machines that know their full neighborhood but can send/receive only a bounded number of $C$ words per round. We are interested in the strongly sublinear regime where $S=n^δ$, for some constant $0 < δ<1$ and $C = MS/n$, where no simulation results are known. We explore when deterministic round-preserving simulations between these models are possible and when they are provably not, for different model parameters, problem families and graph classes. On the positive side, we provide techniques that allow, under certain restrictions, simulations with only constant overhead. On the negative side, we prove simulation impossibility results, which show that the limitations of our simulation results are inherent.

cs.DC↗

arXiv2025

A Lightweight Approach for State Machine Replication

We present a lightweight solution for state machine replication with commitment certificates. Specifically, we adapt and analyze a median rule for the stabilizing consensus problem [Doerr11] to operate in a client-server setting where arbitrary servers may be blocked adaptively based on past system information. We further extend our protocol by compressing information about committed commands, thus keeping the protocol lightweight, while still enabling clients to easily prove that their commands have indeed been committed on the shared state. Our approach guarantees liveness as long as at most a constant fraction of servers are blocked, ensures safety under any number of blocked servers, and supports fast recovery even after all servers are blocked. In addition to offering near-optimal asymptotic performance in several respects, our method is fully decentralized, unlike other near-optimal solutions that rely on leaders. In particular, our solution is robust against adversaries that target key servers (which captures insider-based denial-of-service attacks), whereas leader-based approaches fail under such a blocking model.

cs.DC↗

arXiv2025

Advancing Precision in Multi-Point Cloud Fusion Environments

This research focuses on visual industrial inspection by evaluating point clouds and multi-point cloud matching methods. We also introduce a synthetic dataset for quantitative evaluation of registration method and various distance metrics for point cloud comparison. Additionally, we present a novel CloudCompare plugin for merging multiple point clouds and visualizing surface defects, enhancing the accuracy and efficiency of automated inspection systems.

cs.CV↗

arXiv2025

Byzantine Fault Tolerant Protocols with Near-Constant Work per Node without Signatures

Numerous distributed tasks have to be handled in a setting where a fraction of nodes behaves Byzantine, that is, deviates arbitrarily from the intended protocol. Resilient, deterministic protocols rely on the detection of majorities to avoid inconsistencies if there is a Byzantine minority, which requires individual nodes to handle a communication workload that is proportional to the size of the network -- an intolerable disadvantage in large networks. Randomized protocols circumvent this by probing only small parts of the network, thus allowing for consistent decisions quickly and with a high level of confidence with communication that is near-constant in the network size. However, such protocols usually come with the drawback of limiting the fault tolerance of the protocol, for instance, by severely restricting the number or type of failures that the protocol can tolerate. We present randomized protocols to reliably aggregate and broadcast information, form consensus and compute common coins that tolerate a constant fraction of Byzantine failures, do not require cryptographic signatures and have a near-constant time and message complexity per node. Our main technique is to compute a system of witness committees as a pre-computation step almost optimally. This pre-computation step allows to solve the aforementioned distributed tasks repeatedly and efficiently, but may have far reaching further applications, e.g., for sharding of distributed data structures.

cs.DC↗

arXiv2025

NER4all or Context is All You Need: Using LLMs for low-effort, high-performance NER on historical texts. A humanities informed approach

Named entity recognition (NER) is a core task for historical research in automatically establishing all references to people, places, events and the like. Yet, do to the high linguistic and genre diversity of sources, only limited canonisation of spellings, the level of required historical domain knowledge, and the scarcity of annotated training data, established approaches to natural language processing (NLP) have been both extremely expensive and yielded only unsatisfactory results in terms of recall and precision. Our paper introduces a new approach. We demonstrate how readily-available, state-of-the-art LLMs significantly outperform two leading NLP frameworks, spaCy and flair, for NER in historical documents by seven to twentytwo percent higher F1-Scores. Our ablation study shows how providing historical context to the task and a bit of persona modelling that turns focus away from a purely linguistic approach are core to a successful prompting strategy. We also demonstrate that, contrary to our expectations, providing increasing numbers of examples in few-shot approaches does not improve recall or precision below a threshold of 16-shot. In consequence, our approach democratises access to NER for all historians by removing the barrier of scripting languages and computational skills required for established NLP tools and instead leveraging natural language prompts and consumer-grade tools and frontends.

cs.CL↗

arXiv2024

Universally Optimal Information Dissemination and Shortest Paths in the HYBRID Distributed Model

In this work we consider the HYBRID model of distributed computing, introduced recently by Augustine, Hinnenthal, Kuhn, Scheideler, and Schneider (SODA 2020), where nodes have access to two different communication modes: high-bandwidth local communication along the edges of the graph and low-bandwidth all-to-all communication, capturing the non-uniform nature of modern communication networks. Prior work in HYBRID has focused on showing existentially optimal algorithms, meaning there exists a pathological family of instances on which no algorithm can do better. This neglects the fact that such worst-case instances often do not appear or can be actively avoided in practice. In this work, we focus on the notion of universal optimality, first raised by Garay, Kutten, and Peleg (FOCS 1993). Roughly speaking, a universally optimal algorithm is one that, given any input graph, runs as fast as the best algorithm designed specifically for that graph. We show the first universally optimal algorithms in HYBRID. We present universally optimal solutions for fundamental information dissemination tasks, such as broadcasting and unicasting multiple messages in HYBRID. Furthermore, we apply these tools to obtain universally optimal solutions for various shortest paths problems in HYBRID. A main conceptual contribution of this work is the conception of a new graph parameter called neighborhood quality that captures the inherent complexity of many fundamental graph problems in HYBRID. We also show new existentially optimal shortest paths algorithms in HYBRID, which are utilized as key subroutines in our universally optimal algorithms and are of independent interest. Our new algorithms for $k$-source shortest paths match the existing $\tildeΩ(\sqrt{k})$ lower bound for all $k$. Previously, the lower bound was only known to be tight when $k \in \tildeΩ(n^{2/3})$.

cs.DC↗

arXiv2024

An Analysis of Avalanche Consensus

A family of leaderless, decentralized consensus protocols, called Snow consensus was introduced in a recent whitepaper by Yin et al. These protocols address limitations of existing consensus methods, such as those using proof-of-work or quorums, by utilizing randomization and maintaining some level of resilience against Byzantine participants. Crucially, Snow consensus underpins the Avalanche blockchain, which provides a popular cryptocurrency and a platform for running smart contracts. Snow consensus algorithms are built on a natural, randomized routine, whereby participants continuously sample subsets of others and adopt an observed majority value until consensus is achieved. Additionally, Snow consensus defines conditions based on participants' local views and security parameters. These conditions indicate when a party can confidently finalize its local value, knowing it will be adopted by honest participants. Although Snow consensus algorithms can be formulated concisely, there is a complex interaction between randomization, adversarial influence, and security parameters, which requires a formal analysis of their security and liveness. Snow protocols form the foundation for Avalanche-type blockchains, and this work aims to increase our understanding of such protocols by providing insights into their liveness and safety characteristics. First, we analyze these Snow protocols in terms of latency and security. Second, we expose a design issue where the trade-off between these two is unfavorable. Third, we propose a modification of the original protocol where this trade-off is much more favorable.

cs.DC↗

arXiv2023

Near Tight Shortest Paths in the Hybrid Model

Shortest paths problems are subject to extensive studies in classic distributed models such as the CONGEST or Congested Clique. These models dictate how nodes may communicate in order to determine shortest paths in a distributed input graph. This article focuses on shortest paths problems in the HYBRID model, which combines local communication along edges of the input graph with global communication between arbitrary pairs of nodes that is restricted in terms of bandwidth. Previous work showed that it takes $\tilde Ω(\!\sqrt{k})$ rounds in the \hybrid model for each node to learn its distance to $k$ dedicated source nodes (aka the $k$-SSP problem), even for crude approximations. This lower bound was also matched with algorithmic solutions for $k \geq n^{2/3}$. However, as $k$ gets smaller, the gap between the known upper and lower bounds diverges and even becomes exponential for a single source. In this work we close this gap for the whole range of $k$ (up to terms that are polylogarithmic in $n$), by giving algorithmic solutions for $k$-SSP in $\tilde O\big(\!\sqrt k\big)$ rounds for any $k$.

cs.DS↗

arXiv2023

Towards Universally Optimal Shortest Paths Algorithms in the Hybrid Model

A drawback of the classic approach for complexity analysis of distributed graph problems is that it mostly informs about the complexity of notorious classes of ``worst case'' graphs. Algorithms that are used to prove a tight (existential) bound are essentially optimized to perform well on such worst case graphs. However, such graphs are often either unlikely or actively avoided in practice, where benign graph instances usually admit much faster solutions. To circumnavigate these drawbacks, the concept of universal complexity analysis in the distributed setting was suggested by [Kutten and Peleg, PODC'95] and actively pursued by [Haeupler et al., STOC'21]. Here, the aim is to gauge the complexity of a distributed graph problem depending on the given graph instance. The challenge is to identify and understand the graph property that allows to accurately quantify the complexity of a distributed problem on a given graph. In the present work, we consider distributed shortest paths problems in the HYBRID model of distributed computing, where nodes have simultaneous access to two different modes of communication: one is restricted by locality and the other is restricted by congestion. We identify the graph parameter of neighborhood quality and show that it accurately describes a universal bound for the complexity of certain class of shortest paths problems in the HYBRID model.

cs.DC↗

arXiv2023

Routing Schemes for Hybrid Communication Networks

We consider the problem of computing routing schemes in the $\mathsf{HYBRID}$ model of distributed computing where nodes have access to two fundamentally different communication modes. In this problem nodes have to compute small labels and routing tables that allow for efficient routing of messages in the local network, which typically offers the majority of the throughput. Recent work has shown that using the $\mathsf{HYBRID}$ model admits a significant speed-up compared to what would be possible if either communication mode were used in isolation. Nonetheless, if general graphs are used as the input graph the computation of routing schemes still takes polynomial rounds in the $\mathsf{HYBRID}$ model. We bypass this lower bound by restricting the local graph to unit-disc-graphs and solve the problem deterministically with running time $O(|\mathcal H|^2 \!+\! \log n)$, label size $O(\log n)$, and size of routing tables $O(|\mathcal H|^2 \!\cdot\! \log n)$ where $|\mathcal H|$ is the number of ``radio holes'' in the network. Our work builds on recent work by Coy et al., who obtain this result in the much simpler setting where the input graph has no radio holes. We develop new techniques to achieve this, including a decomposition of the local graph into path-convex regions, where each region contains a shortest path for any pair of nodes in it.

cs.DC↗

arXiv2022

Near-Shortest Path Routing in Hybrid Communication Networks

Hybrid networks, i.e., networks that leverage different means of communication, become ever more widespread. To allow theoretical study of such networks, [Augustine et al., SODA'20] introduced the $\mathsf{HYBRID}$ model, which is based on the concept of synchronous message passing and uses two fundamentally different principles of communication: a local mode, which allows every node to exchange one message per round with each neighbor in a local communication graph; and a global mode where any pair of nodes can exchange messages, but only few such exchanges can take place per round. A sizable portion of the previous research for the $\mathsf{HYBRID}$ model revolves around basic communication primitives and computing distances or shortest paths in networks. In this paper, we extend this study to a related fundamental problem of computing compact routing schemes for near-shortest paths in the local communication graph. We demonstrate that, for the case where the local communication graph is a unit-disc graph with $n$ nodes that is realized in the plane and has no radio holes, we can deterministically compute a routing scheme that has constant stretch and uses labels and local routing tables of size $O(\log n)$ bits in only $O(\log n)$ rounds.

cs.DC↗

arXiv2022

Routing Schemes and Distance Oracles in the Hybrid Model

The $\mathsf{HYBRID}$ model was introduced as a means for theoretical study of distributed networks that use various communication modes. Conceptually, it is a synchronous message passing model with a local communication mode, where in each round each node can send large messages to all its neighbors in a local network (a graph), and a global communication mode, where each node is allotted limited (polylogarithmic) bandwidth per round which it can use to communicate with any node in the network. Prior work has often focused on shortest paths problems in the local network, as their global nature makes these an interesting case study how combining communication modes in the $\mathsf{HYBRID}$ model can overcome the individual lower bounds of either mode. In this work we consider a similar problem, namely computation of distance oracles and routing schemes. In the former, all nodes have to compute local tables, which allows them to look up the distance (estimates) to any target node in the local network when provided with the label of the target. In the latter, it suffices that nodes give the next node on an (approximately) shortest path to the target. Our goal is to compute these local tables as fast as possible with labels as small as possible. We show that this can be done exactly in $\widetilde O(n^{1/3})$ communication rounds and labels of size $Θ(n^{2/3})$ bits. For constant stretch approximations we achieve labels of size $O(\log n)$ in the same time. Further, as our main technical contribution, we provide computational lower bounds for a variety of problem parameters. For instance, we show that computing solutions with stretch below a certain constant takes $\widetilde Ω(n^{1/3})$ rounds even for labels of size $O(n^{2/3})$.

cs.DC↗

arXiv2021

Grazing incidence X-ray fluorescence based characterization of nanostructures for element sensitive profile reconstruction

For the reliable fabrication of the current and next generation of nanostructures it is essential to be able to determine their material composition and dimensional parameters. Using the grazing incidence X-ray fluoresence technique, which is taking advantage of the X-ray standing wave field effect, nanostructures can be investigated with a high sensitivity with respect to the structural and elemental composition. This is demonstrated using lamellar gratings made of Si$_3$N$_4$. Rigorous field simulations obtained from a Maxwell solver based on the finite element method allow to determine the spatial distribution of elemental species and the geometrical shape with sub-nm resolution. The increasing complexity of nanostructures and demanded sensitivity for small changes quickly turn the curse of dimensionality for numerical simulation into a problem which can no longer be solved rationally even with massive parallelisation. New optimization schemes, e.g. machine learning, are required to satisfy the metrological requirements. We present reconstruction results obtained with a Bayesian optimization approach to reduce the computational effort.

physics.app-ph↗

arXiv2020

Computing Shortest Paths and Diameter in the Hybrid Network Model

The $\mathsf{HYBRID}$ model, introduced in [Augustine et al., SODA '20], provides a theoretical foundation for networks that allow multiple communication modes. The model follows the principles of synchronous message passing, whereas nodes are allowed to use \textit{two} fundamentally different communication modes. First, a local mode where nodes may exchange arbitrary information per round over edges of a local communication graph $G$ (akin to the $\mathsf{LOCAL}$ model). Second, a global mode where every node may exchange $O(\log n)$ messages of size $O(\log n)$ bits per round with arbitrary nodes in the network. The $\mathsf{HYBRID}$ model intends to reflect the conditions of many real hybrid networks, where high-bandwidth but inherently local communication is combined with highly flexible global communication with restricted bandwidth. We continue to explore the power and limitations of the $\mathsf{HYBRID}$ model by investigating the complexity of computing shortest paths and diameter of the local communication graph $G$. We improve on the known upper bound for the exact all pairs shortest paths problem (APSP) from [Augustine et al., SODA '20] and provide algorithms to approximate solutions for the $k$ source shortest paths problem ($k$-SSSP). We demonstrate that our results for APSP and $k$-SSP are almost tight (up to poly-logarithmic factors). Furthermore, we give an improved algorithm for the exact single source shortest paths problem for graphs with large diameter. For the problem of approximating the diameter of the local communication network we give the first non-trivial upper bound. This upper bound is complemented by a lower bound for the exact diameter problem.

cs.DC↗

arXiv2019

Shortest Paths in a Hybrid Network Model

We introduce a communication model for hybrid networks, where nodes have access to two different communication modes: a local mode where communication is only possible between specific pairs of nodes, and a global mode where communication between any pair of nodes is possible. This can be motivated, for instance, by wireless networks in which we combine direct device-to-device communication (e.g., using WiFi) with communication via a shared infrastructure (like base stations, the cellular network, or satellites). Typically, communication over short-range connections is cheaper and can be done at a much higher rate. Hence, we are focusing here on the LOCAL model (in which the nodes can exchange an unbounded amount of information in each round) for the local connections while for the global communication we assume the so-called node-capacitated clique model, where in each round every node can exchange only $O(\log n)$-bit messages with just $O(\log n)$ other nodes. In order to explore the power of combining local and global communication, we study the impact of hybrid communication on the complexity of computing shortest paths in the graph given by the local connections. Specifically, for the all-pairs shortest paths problem (APSP), we show that an exact solution can be computed in time $\tilde O\big(n^{2/3}\big)$ and that approximate solutions can be computed in time $\tilde Θ\big(\!\sqrt{n}\big)$. For the single-source shortest paths problem (SSSP), we show that an exact solution can be computed in time $\tilde O\big(\!\sqrt{\mathsf{SPD}}\big)$, where $\mathsf{SPD}$ denotes the shortest path diameter. We further show that a $\big(1\!+\!o(1)\big)$-approximate solution can be computed in time $\tilde O\big(n^{1/3}\big)$. Additionally, we show that for every constant $\varepsilon>0$, it is possible to compute an $O(1)$-approximate solution in time $\tilde O(n^\varepsilon)$.

cs.DC↗