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Stefan Schulte

Publications and source records attributed to Stefan Schulte.

At least 19 recordsLinked to original sources

A Two-Step Chemical Vapor Deposition Process for the Synthesis of an Ir(111)/Borophene/2D-Hexagonal Boron Nitride Heterostructure by Intrinsic Segregation

We report on a two-step ultrahigh vacuum chemical vapor deposition synthesis of a vertical Ir(111)/borophene/hexagonal boron nitride heterostructure, using borazine as a single-source precursor. The process takes advantage of the finite solubility of boron in Ir: low precursor pressure at high temperature first establishes a boron reservoir in the near-surface region of the substrate, whereas subsequent growth at higher precursor pressure promotes the formation of a closed hexagonal boron nitride monolayer. During cooldown, the reduced boron solubility drives segregation to the surface, resulting in the formation of a borophene monolayer beneath the hexagonal boron nitride overlayer. The heterostructure, with micron sized grains, homogeneously covers the entire Ir substrate. The study is performed by complementary spot profile analysis low-energy electron diffraction, low-energy electron microscopy, and scanning tunneling microscopy measurements. This intrinsic segregation-assisted growth concept provides a promising route toward scalable synthesis of high-quality, vertical heterostructures of two-dimensional materials.

cond-mat.mtrl-sci

ContinuumConductor : Decentralized Process Mining on the Edge-Cloud Continuum

Process mining traditionally assumes centralized event data collection and analysis. However, modern Industrial Internet of Things systems increasingly operate over distributed, resource-constrained edge-cloud infrastructures. This paper proposes a structured approach for decentralizing process mining by enabling event data to be mined directly within the IoT systems edge-cloud continuum. We introduce ContinuumConductor a layered decision framework that guides when to perform process mining tasks such as preprocessing, correlation, and discovery centrally or decentrally. Thus, enabling privacy, responsive and resource-efficient process mining. For each step in the process mining pipeline, we analyze the trade-offs of decentralization versus centralization across these layers and propose decision criteria. We demonstrate ContinuumConductor at a real-world use-case of process optimazition in inland ports. Our contributions lay the foundation for computing-aware process mining in cyber-physical and IIoT systems.

cs.DC

SoK: Towards Security and Safety of Edge AI

Advanced AI applications have become increasingly available to a broad audience, e.g., as centrally managed large language models (LLMs). Such centralization is both a risk and a performance bottleneck - Edge AI promises to be a solution to these problems. However, its decentralized approach raises additional challenges regarding security and safety. In this paper, we argue that both of these aspects are critical for Edge AI, and even more so, their integration. Concretely, we survey security and safety threats, summarize existing countermeasures, and collect open challenges as a call for more research in this area.

cs.CR

Cross-Blockchain Communication Using Oracles With an Off-Chain Aggregation Mechanism Based on zk-SNARKs

The closed architecture of prevailing blockchain systems renders the usage of this technology mostly infeasible for a wide range of real-world problems. Most blockchains trap users and applications in their isolated space without the possibility of cooperating or switching to other blockchains. Therefore, blockchains need additional mechanisms for seamless communication and arbitrary data exchange between each other and external systems. Unfortunately, current approaches for cross-blockchain communication are resource-intensive or require additional blockchains or tailored solutions depending on the applied consensus mechanisms of the connected blockchains. Therefore, we propose an oracle with an off-chain aggregation mechanism based on ZeroKnowledge Succinct Non-interactive Arguments of Knowledge (zk-SNARKs) to facilitate cross-blockchain communication. The oracle queries data from another blockchain and applies a rollup-like mechanism to move state and computation off-chain. The zkOracle contract only expects the transferred data, an updated state root, and proof of the correct execution of the aggregation mechanism. The proposed solution only requires constant 378 kgas to submit data on the Ethereum blockchain and is primarily independent of the underlying technology of the queried blockchains.

cs.CR

Assessing Routing Algorithms for PCNs: Full Evaluation Results

Within this Technical Report, we present the full analysis of 61 routing protocols for Wireless Sensor Networks (WSNs) for the purposes of routing in Payment Channel Networks (PCNs). In addition, we present the full results of the implementation of the three algorithms E-TORA, TERP, and M-DART.

cs.DC

Horizontal Scaling of Transaction-Creating Machines

Blockchain technology has become one of the most popular trends in IT over the last few years. Its increasing popularity and the discovery of ever more use cases raises the question of how to improve scalability. While researchers are exploring ways to scale the on-chain processing of transactions, the scalability of the off-chain creation of transactions has not been investigated yet. This is relevant for organizations wishing to send a high volume of transactions in a short time frame, or continuously, e.g., manufacturers of high-volume products. Especially for blockchain implementations such as Ethereum, which require transactions to include so-called nonces (essentially a sequence number), horizontally scaling transaction creation is non-trivial. In this paper, we propose four different approaches for horizontal scaling of transaction creation in Ethereum. Our experimental evaluation examines the performance of the different approaches in terms of scalability and latency and finds two of the four proposed approaches feasible to scale transaction creation horizontally.

cs.SE

Drell-Yan production in third-generation gauge vector leptoquark models at NLO+PS in QCD

Motivated by the long-standing hints of lepton-flavour non-universality in the $b \to c \ell ν$ and $b \to s \ell^+ \ell^-$ channels, we study Drell-Yan ditau production at the Large Hadron Collider (LHC). In the context of models with third-generation gauge vector leptoquarks (LQs), we calculate the complete ${\cal O} (α_s)$ corrections to the $pp \to τ^+ τ^-$ process, achieving next-to-leading order (NLO) plus parton shower (NLO$+$PS) accuracy using the POWHEG method. We provide a dedicated Monte Carlo code that evaluates the NLO QCD corrections on-the-fly in the event generation and use it to study the numerical impact of NLO$+$PS corrections on the kinematic distributions that enter the existing experimental searches for non-resonant ditau final states. Based on our phenomenological analysis we derive NLO accurate constraints on the masses and couplings of third-generation gauge vector LQs using the latest LHC ditau search results corresponding to an integrated luminosity of around $140 \, {\rm fb}^{-1}$ of proton-proton collisions at $\sqrt{s} = 13 \, {\rm TeV}$. The presented NLO$+$PS generator allows for an improved signal modelling, making it an essential tool for future ATLAS and CMS searches for vector LQs in $τ^+ τ^-$ final states at LHC Run III and beyond.

hep-ph

Distributed Key Generation with Smart Contracts using zk-SNARKs

Distributed Key Generation (DKG) is an extensively researched topic as it is fundamental to threshold cryptosystems. Emerging technologies such as blockchains benefit massively from applying threshold cryptography in consensus protocols, randomness beacons, and threshold signatures. However, blockchains and smart contracts also enable further improvements of DKG protocols by providing a decentralized computation and communication platform. For that reason, we propose a DKG protocol that uses smart contracts to ensure the correct execution of the protocol, allow dynamic participation, and provide crypto-economic incentives to encourage honest behavior. The DKG protocol uses a dispute and key derivation mechanism based on Zero-Knowledge Succinct Non-interactive Arguments of Knowledge (zk-SNARKs) to reduce the costs of applying smart contracts by moving the computations off-chain, where the smart contract only verifies the correctness of the computation.

cs.CR

On Drell-Yan production of scalar leptoquarks coupling to heavy-quark flavours

Given the hints of lepton-flavour non-universality in semi-leptonic $B$ decays, leptoquark (LQ) models with sizeable couplings to heavy-quark flavours are enjoying a renaissance. While such models are subject to stringent constraints from low-energy experiments also bounds from non-resonant dilepton searches at the Large Hadron Collider (LHC) turn out to be phenomenologically relevant. Based on the latest LHC dilepton analyses corresponding to an integrated luminosity of around $140 \, {\rm fb}^{-1}$ of proton-proton collisions at $\sqrt{s} = 13 \, {\rm TeV}$, we present improved limits on the scalar LQ couplings that involve heavy-quark flavours and light or heavy dileptons. In particular, we show that effects beyond the leading order that are related to real QCD emissions are relevant in this context, since the inclusion of additional heavy-flavoured jets notably improves the exclusion limits that derive from the high-mass dilepton tails. The impact of electroweak corrections and interference effects between signal and background is also analysed. Within the POWHEG-BOX framework we provide a dedicated Monte Carlo code that allows for an on-the-fly signal event generation including all the LQ corrections considered in this article.

hep-ph

Cost-efficient Auto-scaling of Container-based Elastic Processes

In business process landscapes, a common challenge is to provide the necessary computational resources to enact the single process steps. One well-known approach to solve this issue in a cost-efficient way is to use the notion of elasticity, i.e., to provide cloud-based computational resources in a rapid fashion and to enact the single process steps on these resources. Existing approaches to provide elastic processes are mostly based on Virtual Machines (VMs). Utilizing container technologies could enable a more fine-grained allocation of process steps to computational resources, leading to a better resource utilization and improved cost efficiency. In this paper, we propose an approach to optimize resource allocation for elastic processes by applying a four-fold auto-scaling approach. The main goal is to minimize the cost of process enactments by using containers. To this end, we formulate and implement a multi-objective optimization problem applying Mixed-Integer Linear Programming and use a transformation step to allocate software services to containers. We thoroughly evaluate the optimization problem and show that it can lead to significant cost savings while maintaining Service Lev

cs.DC

Advancing Blockchain-based Federated Learning through Verifiable Off-chain Computations

Federated learning may be subject to both global aggregation attacks and distributed poisoning attacks. Blockchain technology along with incentive and penalty mechanisms have been suggested to counter these. In this paper, we explore verifiable off-chain computations using zero-knowledge proofs as an alternative to incentive and penalty mechanisms in blockchain-based federated learning. In our solution, learning nodes, in addition to their computational duties, act as off-chain provers submitting proofs to attest computational correctness of parameters that can be verified on the blockchain. We demonstrate and evaluate our solution through a health monitoring use case and proof-of-concept implementation leveraging the ZoKrates language and tools for smart contract-based on-chain model management. Our research introduces verifiability of correctness of learning processes, thus advancing blockchain-based federated learning.

cs.CR

Roadmap for Edge AI: A Dagstuhl Perspective

Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimization, and deployment of distributed AI/ML pipelines with given quality of experience, trust, security and privacy targets. The Edge AI community investigates novel ML methods for the edge computing environment, spanning multiple sub-fields of computer science, engineering and ICT. The goal is to share an envisioned roadmap that can bring together key actors and enablers to further advance the domain of Edge AI.

cs.DC

A Voting-Based Blockchain Interoperability Oracle

Today's blockchain landscape is severely fragmented as more and more heterogeneous blockchain platforms have been developed in recent years. These blockchain platforms are not able to interact with each other or with the outside world since only little emphasis is placed on the interoperability between them. Already proposed solutions for blockchain interoperability such as naive relay or oracle solutions are usually not broadly applicable since they are either too expensive to operate or very resource-intensive. For that reason, we propose a blockchain interoperability oracle that follows a voting-based approach based on threshold signatures. The oracle nodes generate a distributed private key to execute an off-chain aggregation mechanism to collectively respond to requests. Compared to state-of-the-art relay schemes, our approach does not incur any ongoing costs and since the on-chain component only needs to verify a single signature, we can achieve remarkable cost savings compared to conventional oracle solutions.

cs.CR

Blockchain-based Result Verification for Computation Offloading

Offloading of computation, e.g., to the cloud, is today a major task in distributed systems. Usually, consumers which apply offloading have to trust that a particular functionality offered by a service provider is delivering correct results. While redundancy (i.e., offloading a task to more than one service provider) or (partial) reprocessing help to identify correct results, they also lead to significantly higher cost. Hence, within this paper, we present an approach to verify the results of offchain computations via the blockchain. For this, we apply zero-knowledge proofs to provide evidence that results are correct. Using our approach, it is possible to establish trust between a service consumer and arbitrary service providers. We evaluate our approach using a very well-known example task, i.e., the Traveling Salesman Problem.

cs.DC

Decentralized Cross-Blockchain Asset Transfers

Today, several solutions for cross-blockchain asset transfers exist. However, these solutions are either tailored to specific assets or neglect finality guarantees that prevent assets from getting lost in transit. In this paper, we present a cross-blockchain asset transfer protocol that supports arbitrary assets and adheres to finality requirements. The ability to freely transfer assets between blockchains may increase transaction throughput and provide developers with more flexibility by allowing them to design digital assets that leverage the capacities and capabilities of multiple blockchains.

cs.CR

Searching for pseudo Nambu-Goldstone boson dark matter production in association with top quarks

Pseudo Nambu-Goldstone bosons (pNGBs) are attractive dark matter (DM) candidates, since they couple to the Standard Model (SM) predominantly through derivative interactions. Thereby they naturally evade the strong existing limits inferred from DM direct detection experiments. Working in an effective field theory that includes both derivative and non-derivative DM-SM operators, we perform a detailed phenomenological study of the Large Hadron Collider reach for pNGB DM production in association with top quarks. Drawing on motivated benchmark scenarios as examples, we compare our results to other collider limits as well as the constraints imposed by DM (in)direct detection experiments and the relic abundance. We furthermore explore implications on the viable parameter space of pNGB DM. In particular, we demonstrate that DM direct detection experiments become sensitive to many pNGB DM realisations once loop-induced interactions are taken into account. The search strategies and pNGB DM benchmark models that we discuss can serve as a starting point for dedicated experimental analyses by the ATLAS and the CMS collaborations.

hep-ph

Towards Cross-Blockchain Smart Contracts

In recent years, manifold blockchain protocols have been proposed by researchers and industrial companies alike. This has led to a very heterogeneous blockchain landscape. Accordingly, it would be desirable if blockchains could interact with each other. However, current blockchain technologies offer only limited support for interoperability, thus preventing tokens or smart contracts from leaving the scope of a particular blockchain. As a first step towards a solution for cross-chain smart contract interactions, we introduce a framework which allows to invoke a smart contract from another blockchain. We offer support for continuing a smart contract after receiving a result from a different blockchain, and for calling smart contracts recursively across blockchains. We provide a reference implementation for Ethereum-based blockchains using Solidity and evaluate the performance regarding time and cost overheads.

cs.CR

The FORA Fog Computing Platform for Industrial IoT

Industry 4.0 will only become a reality through the convergence of Operational and Information Technologies (OT & IT), which use different computation and communication technologies. Cloud Computing cannot be used for OT involving industrial applications, since it cannot guar-antee stringent non-functional requirements, e.g., dependability, trustworthiness and timeliness. Instead, a new computing paradigm, called Fog Computing, is envisioned as an architectural means to realize the IT/OT convergence. In this paper we propose a Fog Computing Platform (FCP) reference architecture targeting Industrial IoT applications. The FCP is based on: deter-ministic virtualization that reduces the effort required for safety and security assurance; middle-ware for supporting both critical control and dynamic Fog applications; deterministic networking and interoperability, using open standards such as IEEE 802.1 Time-Sensitive Networking (TSN) and OPC Unified Architecture (OPC UA); mechanisms for resource management and or-chestration; and services for security, fault tolerance and distributed machine learning. We pro-pose a methodology for the definition and the evaluation of the reference architecture. We use the Architecture Analysis Design Language (AADL) to model the FCP reference architecture, and a set of industrial use cases to evaluate its suitability for the Industrial IoT area.

cs.DC