Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems最新文献_第5页

Property-based routing in clustered message brokers for CPS: Doctoral Symposium CPS集群消息代理中基于属性的路由:博士研讨会

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3096475

Ole Meyer, Julius Ollesch, Stefan Gries, F. Wessling, V. Gruhn

引用次数: 0

FlinkMan: Anomaly Detection in Manufacturing Equipment with Apache Flink: Grand Challenge FlinkMan:异常检测在制造设备与Apache Flink:大挑战

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3095099

Nicolo Rivetti, Yann Busnel, A. Gal

引用次数: 5

Real-time High Performance Anomaly Detection over Data Streams: Grand Challenge 数据流上的实时高性能异常检测:重大挑战

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3095102

Dimitrije Jankov, Sourav Sikdar, Rohan Mukherjee, Kia Teymourian, C. Jermaine

引用次数: 22

Reflections on Almost Two Decades of Research into Stream Processing: Tutorial 近二十年来对流处理研究的反思:教程

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3095110

K. S. Esmaili

引用次数: 1

Blockchain: Distributed Event-based Processing in a Data-Centric World: Extended Abstract 区块链:以数据为中心的分布式事件处理:扩展摘要

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3097982

R. Hull

引用次数: 45

The Requirements Engineering Perspective on Events in Cyber-Physical Systems: Poster 网络物理系统中事件的需求工程视角:海报

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3095097

Julius Ollesch, M. Hesenius, V. Gruhn, C. Alias

引用次数: 4

StreamLearner: Distributed Incremental Machine Learning on Event Streams: Grand Challenge 流学习者:事件流上的分布式增量机器学习:大挑战

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3095103

C. Mayer, R. Mayer, M. Abdo

引用次数: 9

An Event-based Capture-and-Compare Approach to Support the Evolution of Systems of Systems 支持系统的系统演化的基于事件的捕获和比较方法

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3093909

Jürgen Thanhofer-Pilisch, Rick Rabiser, Thomas Krismayer, Michael Vierhauser, P. Grünbacher, Stefan Wallner, Klaus Seyerlehner, H. Zeisel

{"title":"An Event-based Capture-and-Compare Approach to Support the Evolution of Systems of Systems","authors":"Jürgen Thanhofer-Pilisch, Rick Rabiser, Thomas Krismayer, Michael Vierhauser, P. Grünbacher, Stefan Wallner, Klaus Seyerlehner, H. Zeisel","doi":"10.1145/3093742.3093909","DOIUrl":"https://doi.org/10.1145/3093742.3093909","url":null,"abstract":"Industrial software systems are often systems of systems (SoS) that evolve continuously to meet new customer requirements or to address technological changes. Despite thorough testing of the different contributing parts, the full behavior of SoS only emerges at runtime. The systems in the SoS and their interactions thus need to be continuously monitored and checked during operation to determine compliance with requirements. In particular, after changes to one system, it is necessary to check whether the overall SoS still behaves correctly and as intended. Based on an existing monitoring framework we have been developing support for capturing and comparing event traces in SoS. Our approach facilitates and partly automates the identification of differences in event traces, which often indicate undesirable behavior introduced during evolution. In this paper we motivate the need for monitoring and evolution support in SoS using an industrial example and describe our event-based capture-and-compare approach. We evaluate the applicability and scalability of our tool-supported approach, demonstrating that it can cope with comparing event traces from an industrial SoS. We present our experiences and findings intended for researchers and practitioners working on maintenance and evolution of large-scale software systems.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129090947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Kafka versus RabbitMQ: A comparative study of two industry reference publish/subscribe implementations: Industry Paper Kafka与RabbitMQ:两种行业参考发布/订阅实现的比较研究

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3093908

P. Dobbelaere, K. S. Esmaili

{"title":"Kafka versus RabbitMQ: A comparative study of two industry reference publish/subscribe implementations: Industry Paper","authors":"P. Dobbelaere, K. S. Esmaili","doi":"10.1145/3093742.3093908","DOIUrl":"https://doi.org/10.1145/3093742.3093908","url":null,"abstract":"Publish/subscribe is a distributed interaction paradigm well adapted to the deployment of scalable and loosely coupled systems. Apache Kafka and RabbitMQ are two popular open-source and commercially-supported pub/sub systems that have been around for almost a decade and have seen wide adoption. Given the popularity of these two systems and the fact that both are branded as pub/sub systems, two frequently asked questions in the relevant online forums are: how do they compare against each other and which one to use? In this paper, we frame the arguments in a holistic approach by establishing a common comparison framework based on the core functionalities of pub/sub systems. Using this framework, we then venture into a qualitative and quantitative (i.e. empirical) comparison of the common features of the two systems. Additionally, we also highlight the distinct features that each of these systems has. After enumerating a set of use cases that are best suited for RabbitMQ or Kafka, we try to guide the reader through a determination table to choose the best architecture given his/her particular set of requirements.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117212963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 121

A New Application Benchmark for Data Stream Processing Architectures in an Enterprise Context: Doctoral Symposium 企业环境下数据流处理体系结构的新应用基准:博士研讨会

Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems Pub Date : 2017-06-08 DOI: 10.1145/3093742.3093902

Guenter Hesse, Christoph Matthies, Benjamin Reissaus, M. Uflacker

{"title":"A New Application Benchmark for Data Stream Processing Architectures in an Enterprise Context: Doctoral Symposium","authors":"Guenter Hesse, Christoph Matthies, Benjamin Reissaus, M. Uflacker","doi":"10.1145/3093742.3093902","DOIUrl":"https://doi.org/10.1145/3093742.3093902","url":null,"abstract":"Against the backdrop of ever-growing data volumes and trends like the Internet of Things (IoT) or Industry 4.0, Data Stream Processing Systems (DSPSs) or data stream processing architectures in general receive a greater interest. Continuously analyzing streams of data allows immediate responses to environmental changes. A challenging task in that context is assessing and comparing data stream processing architectures in order to identify the most suitable one for certain settings. The present paper provides an overview about performance benchmarks that can be used for analyzing data stream processing applications. By describing shortcomings of these benchmarks, the need for a new application benchmark in this area, especially for a benchmark covering enterprise architectures, is highlighted. A key role in such an enterprise context is the combination of streaming data and business data, which is barely covered in current data stream processing benchmarks. Furthermore, first ideas towards the development of a solution, i.e., a new application benchmark that is able to fill the existing gap, are depicted.","PeriodicalId":325666,"journal":{"name":"Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130884436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6