Auflistung nach Schlagwort "scalability"
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- KonferenzbeitragCloud-Native Scalability Benchmarking with Theodolite: Applied to the TeaStore Benchmark(Softwaretechnik-Trends Band 43, Heft 1, 2023) Henning, Sören; Wetzel, Benedikt; Hasselbring, WilhelmTheodolite is a framework for benchmarking the scalability of cloud-native applications such as microservices. It automates deployment and monitoring of a cloud-native application for different load intensities and provisioned cloud resources and assesses whether specified service level objectives (SLOs) are fulfilled. Provided as a Kubernetes Operator, Theodolite integrates with the cloud-native ecosystem and runs existing deployment configurations of various systems under-test, load generators, and benchmarks. We givea presentation on Theodolite and exemplify its usage by benchmarking the scalability of the TeaStore microservice reference application.
- KonferenzbeitragDerivation of Categories for Interoperability of Blockchain- and Distributed Ledger Systems(INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft, 2019) Zeuch, Katharina; Wöhnert, Kai Hendrik; Skwarek, VolkerDue to increasing security requirements e. g. for transaction based smart-x-technologies in distributed systems, blockchain technologies are predestined for secure data exchange and keeping in distributed systems. Although the underlying principle of almost every blockchain is the Byzantine fault tolerance (BFT), its implementation differs significantly between the technologies so that migration or interoperability between systems is nearly impossible. Additionally, this missing interoperability also reduces the chance for scalability between different extents of implementation as there is usually not a one-size-fits-all-blockchain: Different technologies have their advantages for different systems. Therefore scalability and interoperability are tightly coupled. As a basis for further research on and the derivation of generally scalable and interoperable architectures of blockchains, current technologies have to be made comparable and interoperability criteria have to be developed. This paper analyses current literature and introduces technical criteria for the comparison of blockchainand distributed ledger technologies (BC/DLT).With a list of eleven criteria popular BC/DLTs such as Bitcoin, Ethereum, Hyperledger Fabric, Ripple and Corda are compared regarding general features.
- Konferenzbeitragn-dimensional border growth(10th International Conferenceon Innovative Internet Community Systems (I2CS) – Jubilee Edition 2010 –, 2010) Berg, Daniel; Unger, HerwigPeer-To-Peer (P2P) networks become more and more present in the consumer area as well as in industrial applications. Especially in the industrialand the business area, reliable and scalable protocols are needed, that produce low networkoverhead and react quickly on any network-changes. In this paper a generalization of the Border-Growth-algorithm is introduced, that improves the network's scalability, its connectivity, and decreases its diameter by providing multiple dimensions, rather than just two of them.
- KonferenzbeitragPerformance Evaluation of BaSyx based Asset Administration Shells for Industry 4.0 Applications(Softwaretechnik-Trends Band 43, Heft 1, 2023) Sauer, Christian; Eichelberger, HolgerThe Asset Administration Shell (AAS) is an upcoming information model standard, which aims at interoperable modeling of “assets”, i.e., products, machines, services or digital twins in IIoT/Industry 4.0. Currently, a number of IIoT-platforms use proprietary information models similar to AAS, but not a common standard, which affects interoperability. A key question for a broad uptake is if AAS can be applied in a performant and scalable manner. In this paper, we examine this question for the open source Eclipse BaSyx middleware. To explore capabilities and possible performance limitations, we present four experiments measuring the performance of experimental AAS in BaSyx and, within the context set by our experiments, i.e., 10-1000 AAS instances, can conclude good scalability.
- ZeitschriftenartikelScalability Benchmarking of Cloud-Native Applications: The Theodolite Approach(Softwaretechnik-Trends Band 44, Heft 2, 2024) Henning, Sören; Hasselbring, WilhelmScalability is a driving requirement for many software systems, especially for those designed as cloud-native applications and event-driven microservices. Empirically evaluating and comparing the scalability of such applications is therefore of great interest for software engineers, architects, and researchers. In this summary, we outline the thesis Scalability Benchmarking of Cloud-Native Applications Applied to Event Driven Microservices, which presents and evaluates Theodolite, our scalability benchmarking method for cloud-native applications along with specific scalability benchmarks for event-driven microservices.
- ZeitschriftenartikelSentiStorm: Echtzeit-Stimmungserkennung von Tweets(HMD Praxis der Wirtschaftsinformatik: Vol. 53, No. 4, 2016) Zangerle, Eva; Illecker, Martin; Specht, GüntherDas automatisierte Erkennen der Stimmung von Texten hat in den letzten Jahren stark an Bedeutung gewonnen. Insbesondere durch die rapide Zunahme der Geschwindigkeit, mit der in sozialen Medien Informationen verbreitet werden, ist eine Echtzeit-Bestimmung der Stimmung von Texten ein herausforderndes Problem. Der Mikroblogging-Dienst Twitter verzeichnet im Durchschnitt über 8000 versendete Nachrichten pro Sekunde. In dieser Arbeit stellen wir mit dem SentiStorm-Ansatz einen Ansatz zur Stimmungserkennung von Tweets vor. Dabei erzeugen wir in einem ersten Schritt Merkmalsvektoren für die Tweets, die sowohl linguistische Informationen über den Tweet (Wichtigkeit der Wörter, Wortarten), wie auch über Sentiment-Lexika gewonnene Stimmungsinformationen beinhalten. In einem zweiten Schritt führen wir mittels der Merkmalsvektoren eine Stimmungsklassifikation durch, die eine Einteilung in positive, negative oder neutrale Tweets ermöglicht. Die durchgeführten Evaluationen zeigen, dass der präsentierte Ansatz bezüglich der Qualität der erkannten Stimmung sehr gute Erkennungsraten garantiert. Weiter zeigen wir, dass der Ansatz mittels der Apache Storm Plattform problemlos für die Echtzeit-Stimmungserkennung von Tweets skaliert werden kann.AbstractThe automatic detection of the sentiment of texts has become more and more important throughout the last years. Particularly, the rapid increase of the speed at which information is spread in social media makes real-time sentiment detection a challenging task. On the microblogging platform Twitter, more than 8,000 messages are sent every second. In this work, we present the SentiStorm approach, an approach for sentiment detection within tweets. We base the approach on feature vectors which contain linguistic information about the tweet content (weighting of words, word categories), as well as sentiment information which we gather based on sentiment lexica. Subsequently, we facilitate these feature vectors for a sentiment classification task which allows for distinguishing positive, negative and neutral tweets. Our conducted evaluations show that the proposed approach shows high classification accuracy. At the same time, we show that utilizing the Apache Storm platform we are able to easily scale the approach towards a real-time sentiment classification of tweets.
- ZeitschriftenartikelSwarm robotics: Robustness, scalability, and self-X features in industrial applications(it - Information Technology: Vol. 61, No. 4, 2019) Heinrich, Mary Katherine; Soorati, Mohammad Divband; Kaiser, Tanja Katharina; Wahby, Mostafa; Hamann, HeikoApplying principles of swarm intelligence to the control of autonomous systems in industry can advance our ability to manage complexity in prominent and high-cost sectors—such as transportation, logistics, and construction. In swarm robotics, the exclusive use of decentralized control relying on local communication and information provides the key advantage first of scalability, and second of robustness against failure points. These are directly useful in certain applied tasks that can be studied in laboratory environments, such as self-assembly and self-organized construction. In this article, we give a brief introduction to swarm robotics for a broad audience, with the intention of targeting future industrial applications. We then present a summary of four examples of our recently published research results with simple models. First, we present our approach to self-reconfiguration, which uses collective adjustment of swarm density in a dynamic setting. Second, we describe our robot experiments for self-organized material deployment in structured and semi-structured environments, applicable to braided composites. Third, we present our machine learning approach for self-assembly, motivated as a simple model developing foundational methods, which generates self-organizing robot behaviors to form emergent patterns. Fourth, we describe our experiments implementing a bioinspired model in a robot swarm, where we show self-healing of damage as the robots collectively locate a resource. Overall, the four examples we present concern robustness, scalability, and self-X features, which we propose as potentially relevant to future research in swarm robotics applied to industry sectors. We summarize these approaches as an introduction to our recent research, targeting the broad audience of this journal.
- KonferenzbeitragToward Efficient Scalability Benchmarking of Event-Driven Microservice Architectures at Large Scale(Softwaretechnik-Trends Band 40, Heft 3, 2020) Henning, Sören; Hasselbring, WilhelmOver the past years, an increase in software architectures containing microservices, which process data streams of a messaging system, can be observed. We present Theodolite, a method accompanied by an open source implementation for benchmarking the scalability of such microservices as well as their employed stream processing frameworks and deployment options. According to common scalability definitions, Theodolite provides detailed insights into how resource demands evolve with increasing load intensity. However, accurate and statistically rigorous insights come at the cost of long execution times, making it impracticable to execute benchmarks for large sets of systems under test. To overcome this limitation, we raise three research questions and propose a research agenda for executing scalability benchmarks more time-efficiently and, thus, for running scalability benchmarks at large scale.